diff --git a/.github/workflows/test-dream-conda.yml b/.github/workflows/test-invoke-conda.yml similarity index 92% rename from .github/workflows/test-dream-conda.yml rename to .github/workflows/test-invoke-conda.yml index b426275b26..b5314cfd6b 100644 --- a/.github/workflows/test-dream-conda.yml +++ b/.github/workflows/test-invoke-conda.yml @@ -1,4 +1,4 @@ -name: Test Dream with Conda +name: Test Invoke with Conda on: push: branches: @@ -9,7 +9,7 @@ jobs: strategy: matrix: os: [ ubuntu-latest, macos-12 ] - name: Test dream.py on ${{ matrix.os }} with conda + name: Test invoke.py on ${{ matrix.os }} with conda runs-on: ${{ matrix.os }} steps: - run: | @@ -85,9 +85,9 @@ jobs: fi # Utterly hacky, but I don't know how else to do this if [[ ${{ github.ref }} == 'refs/heads/master' ]]; then - time ${{ steps.vars.outputs.PYTHON_BIN }} scripts/dream.py --from_file tests/preflight_prompts.txt + time ${{ steps.vars.outputs.PYTHON_BIN }} scripts/invoke.py --from_file tests/preflight_prompts.txt elif [[ ${{ github.ref }} == 'refs/heads/development' ]]; then - time ${{ steps.vars.outputs.PYTHON_BIN }} scripts/dream.py --from_file tests/dev_prompts.txt + time ${{ steps.vars.outputs.PYTHON_BIN }} scripts/invoke.py --from_file tests/dev_prompts.txt fi mkdir -p outputs/img-samples - name: Archive results diff --git a/.gitignore b/.gitignore index da74df3a1a..0c3bd66d95 100644 --- a/.gitignore +++ b/.gitignore @@ -196,3 +196,6 @@ checkpoints .vscode/ gfpgan/ models/ldm/stable-diffusion-v1/model.sha256 + +# GFPGAN model files +gfpgan/ diff --git a/README.md b/README.md index ffd2e0c542..9606d30b9c 100644 --- a/README.md +++ b/README.md @@ -24,7 +24,7 @@ _This repository was formally known as lstein/stable-diffusion_ [CI checks on dev badge]: https://flat.badgen.net/github/checks/invoke-ai/InvokeAI/development?label=CI%20status%20on%20dev&cache=900&icon=github [CI checks on dev link]: https://github.com/invoke-ai/InvokeAI/actions?query=branch%3Adevelopment [CI checks on main badge]: https://flat.badgen.net/github/checks/invoke-ai/InvokeAI/main?label=CI%20status%20on%20main&cache=900&icon=github -[CI checks on main link]: https://github.com/invoke-ai/InvokeAI/actions/workflows/test-dream-conda.yml +[CI checks on main link]: https://github.com/invoke-ai/InvokeAI/actions/workflows/test-invoke-conda.yml [discord badge]: https://flat.badgen.net/discord/members/ZmtBAhwWhy?icon=discord [discord link]: https://discord.gg/ZmtBAhwWhy [github forks badge]: https://flat.badgen.net/github/forks/invoke-ai/InvokeAI?icon=github @@ -41,10 +41,13 @@ _This repository was formally known as lstein/stable-diffusion_ [latest release link]: https://github.com/invoke-ai/InvokeAI/releases -This is a fork of [CompVis/stable-diffusion](https://github.com/CompVis/stable-diffusion), the open -source text-to-image generator. It provides a streamlined process with various new features and -options to aid the image generation process. It runs on Windows, Mac and Linux machines, and runs on -GPU cards with as little as 4 GB or RAM. +This is a fork of +[CompVis/stable-diffusion](https://github.com/CompVis/stable-diffusion), +the open source text-to-image generator. It provides a streamlined +process with various new features and options to aid the image +generation process. It runs on Windows, Mac and Linux machines, with +GPU cards with as little as 4 GB or RAM. It provides both a polished +Web interface, and an easy-to-use command-line interface. _Note: This fork is rapidly evolving. Please use the [Issues](https://github.com/invoke-ai/InvokeAI/issues) tab to report bugs and make feature @@ -90,20 +93,26 @@ You wil need one of the following: - At least 6 GB of free disk space for the machine learning model, Python, and all its dependencies. -#### Note +**Note** + +If you have a Nvidia 10xx series card (e.g. the 1080ti), please +run the dream script in full-precision mode as shown below. + +Similarly, specify full-precision mode on Apple M1 hardware. Precision is auto configured based on the device. If however you encounter errors like 'expected type Float but found Half' or 'not implemented for Half' -you can try starting `dream.py` with the `--precision=float32` flag: +you can try starting `invoke.py` with the `--precision=float32` flag: ```bash -(ldm) ~/stable-diffusion$ python scripts/dream.py --precision=float32 +(ldm) ~/stable-diffusion$ python scripts/invoke.py --precision=float32 ``` ### Features #### Major Features +- [Web Server](docs/features/WEB.md) - [Interactive Command Line Interface](docs/features/CLI.md) - [Image To Image](docs/features/IMG2IMG.md) - [Inpainting Support](docs/features/INPAINTING.md) @@ -111,10 +120,9 @@ you can try starting `dream.py` with the `--precision=float32` flag: - [Upscaling, face-restoration and outpainting](docs/features/POSTPROCESS.md) - [Seamless Tiling](docs/features/OTHER.md#seamless-tiling) - [Google Colab](docs/features/OTHER.md#google-colab) -- [Web Server](docs/features/WEB.md) - [Reading Prompts From File](docs/features/PROMPTS.md#reading-prompts-from-a-file) - [Shortcut: Reusing Seeds](docs/features/OTHER.md#shortcuts-reusing-seeds) -- [Weighted Prompts](docs/features/PROMPTS.md#weighted-prompts) +- [Prompt Blending](docs/features/PROMPTS.md#prompt-blending) - [Thresholding and Perlin Noise Initialization Options](/docs/features/OTHER.md#thresholding-and-perlin-noise-initialization-options) - [Negative/Unconditioned Prompts](docs/features/PROMPTS.md#negative-and-unconditioned-prompts) - [Variations](docs/features/VARIATIONS.md) @@ -130,7 +138,7 @@ you can try starting `dream.py` with the `--precision=float32` flag: - vNEXT (TODO 2022) - - Deprecated `--full_precision` / `-F`. Simply omit it and `dream.py` will auto + - Deprecated `--full_precision` / `-F`. Simply omit it and `invoke.py` will auto configure. To switch away from auto use the new flag like `--precision=float32`. - v1.14 (11 September 2022) @@ -156,7 +164,7 @@ you can try starting `dream.py` with the `--precision=float32` flag: - A new configuration file scheme that allows new models (including upcoming stable-diffusion-v1.5) to be added without altering the code. ([David Wager](https://github.com/maddavid12)) - - Can specify --grid on dream.py command line as the default. + - Can specify --grid on invoke.py command line as the default. - Miscellaneous internal bug and stability fixes. - Works on M1 Apple hardware. - Multiple bug fixes. diff --git a/backend/invoke_ai_web_server.py b/backend/invoke_ai_web_server.py index d12f68a2e3..ddff39a7bc 100644 --- a/backend/invoke_ai_web_server.py +++ b/backend/invoke_ai_web_server.py @@ -12,9 +12,9 @@ from PIL import Image from uuid import uuid4 from threading import Event -from ldm.dream.args import Args, APP_ID, APP_VERSION, calculate_init_img_hash -from ldm.dream.pngwriter import PngWriter, retrieve_metadata -from ldm.dream.conditioning import split_weighted_subprompts +from ldm.invoke.args import Args, APP_ID, APP_VERSION, calculate_init_img_hash +from ldm.invoke.pngwriter import PngWriter, retrieve_metadata +from ldm.invoke.conditioning import split_weighted_subprompts from backend.modules.parameters import parameters_to_command @@ -147,7 +147,7 @@ class InvokeAIWebServer: self.init_image_path = os.path.join(self.result_path, 'init-images/') self.mask_image_path = os.path.join(self.result_path, 'mask-images/') # txt log - self.log_path = os.path.join(self.result_path, 'dream_log.txt') + self.log_path = os.path.join(self.result_path, 'invoke_log.txt') # make all output paths [ os.makedirs(path, exist_ok=True) diff --git a/backend/modules/create_cmd_parser.py b/backend/modules/create_cmd_parser.py index a82f2a80f5..919caeda91 100644 --- a/backend/modules/create_cmd_parser.py +++ b/backend/modules/create_cmd_parser.py @@ -1,6 +1,6 @@ import argparse import os -from ldm.dream.args import PRECISION_CHOICES +from ldm.invoke.args import PRECISION_CHOICES def create_cmd_parser(): diff --git a/backend/modules/parameters.py b/backend/modules/parameters.py index d15167e792..0fae7ef729 100644 --- a/backend/modules/parameters.py +++ b/backend/modules/parameters.py @@ -15,7 +15,7 @@ SAMPLER_CHOICES = [ def parameters_to_command(params): """ - Converts dict of parameters into a `dream.py` REPL command. + Converts dict of parameters into a `invoke.py` REPL command. """ switches = list() diff --git a/backend/server.py b/backend/server.py index d0977b9dc3..cc0996dc66 100644 --- a/backend/server.py +++ b/backend/server.py @@ -30,10 +30,10 @@ from send2trash import send2trash from ldm.generate import Generate -from ldm.dream.restoration import Restoration -from ldm.dream.pngwriter import PngWriter, retrieve_metadata -from ldm.dream.args import APP_ID, APP_VERSION, calculate_init_img_hash -from ldm.dream.conditioning import split_weighted_subprompts +from ldm.invoke.restoration import Restoration +from ldm.invoke.pngwriter import PngWriter, retrieve_metadata +from ldm.invoke.args import APP_ID, APP_VERSION, calculate_init_img_hash +from ldm.invoke.conditioning import split_weighted_subprompts from modules.parameters import parameters_to_command @@ -125,7 +125,7 @@ class CanceledException(Exception): try: gfpgan, codeformer, esrgan = None, None, None - from ldm.dream.restoration.base import Restoration + from ldm.invoke.restoration.base import Restoration restoration = Restoration() gfpgan, codeformer = restoration.load_face_restore_models() @@ -164,7 +164,7 @@ init_image_path = os.path.join(result_path, "init-images/") mask_image_path = os.path.join(result_path, "mask-images/") # txt log -log_path = os.path.join(result_path, "dream_log.txt") +log_path = os.path.join(result_path, "invoke_log.txt") # make all output paths [ diff --git a/docs/CHANGELOG.md b/docs/CHANGELOG.md index f0d61aeb97..3628e5e245 100644 --- a/docs/CHANGELOG.md +++ b/docs/CHANGELOG.md @@ -5,9 +5,9 @@ - Supports a Google Colab notebook for a standalone server running on Google hardware [Arturo Mendivil](https://github.com/artmen1516) - WebUI supports GFPGAN/ESRGAN facial reconstruction and upscaling [Kevin Gibbons](https://github.com/bakkot) - WebUI supports incremental display of in-progress images during generation [Kevin Gibbons](https://github.com/bakkot) -- Output directory can be specified on the dream> command line. +- Output directory can be specified on the invoke> command line. - The grid was displaying duplicated images when not enough images to fill the final row [Muhammad Usama](https://github.com/SMUsamaShah) -- Can specify --grid on dream.py command line as the default. +- Can specify --grid on invoke.py command line as the default. - Miscellaneous internal bug and stability fixes. --- @@ -16,13 +16,13 @@ - Improved file handling, including ability to read prompts from standard input. (kudos to [Yunsaki](https://github.com/yunsaki) -- The web server is now integrated with the dream.py script. Invoke by adding --web to - the dream.py command arguments. +- The web server is now integrated with the invoke.py script. Invoke by adding --web to + the invoke.py command arguments. - Face restoration and upscaling via GFPGAN and Real-ESGAN are now automatically enabled if the GFPGAN directory is located as a sibling to Stable Diffusion. VRAM requirements are modestly reduced. Thanks to both [Blessedcoolant](https://github.com/blessedcoolant) and [Oceanswave](https://github.com/oceanswave) for their work on this. -- You can now swap samplers on the dream> command line. [Blessedcoolant](https://github.com/blessedcoolant) +- You can now swap samplers on the invoke> command line. [Blessedcoolant](https://github.com/blessedcoolant) --- @@ -32,7 +32,7 @@ - You now can specify a seed of -1 to use the previous image's seed, -2 to use the seed for the image generated before that, etc. Seed memory only extends back to the previous command, but will work on all images generated with the -n# switch. - Variant generation support temporarily disabled pending more general solution. -- Created a feature branch named **yunsaki-morphing-dream** which adds experimental support for +- Created a feature branch named **yunsaki-morphing-invoke** which adds experimental support for iteratively modifying the prompt and its parameters. Please see[ Pull Request #86](https://github.com/lstein/stable-diffusion/pull/86) for a synopsis of how this works. Note that when this feature is eventually added to the main branch, it will may be modified significantly. @@ -57,7 +57,7 @@ ## v1.08 (24 August 2022) -- Escape single quotes on the dream> command before trying to parse. This avoids +- Escape single quotes on the invoke> command before trying to parse. This avoids parse errors. - Removed instruction to get Python3.8 as first step in Windows install. Anaconda3 does it for you. @@ -94,7 +94,7 @@ be regenerated with the indicated key - It should no longer be possible for one image to overwrite another -- You can use the "cd" and "pwd" commands at the dream> prompt to set and retrieve +- You can use the "cd" and "pwd" commands at the invoke> prompt to set and retrieve the path of the output directory. --- @@ -128,7 +128,7 @@ - added k_lms sampling. **Please run "conda env update" to load the k_lms dependencies!!** - use half precision arithmetic by default, resulting in faster execution and lower memory requirements - Pass argument --full_precision to dream.py to get slower but more accurate image generation + Pass argument --full_precision to invoke.py to get slower but more accurate image generation --- diff --git a/docs/assets/Lincoln-and-Parrot-512-transparent.png b/docs/assets/Lincoln-and-Parrot-512-transparent.png new file mode 100755 index 0000000000..363f3cced3 Binary files /dev/null and b/docs/assets/Lincoln-and-Parrot-512-transparent.png differ diff --git a/docs/assets/Lincoln-and-Parrot-512.png b/docs/assets/Lincoln-and-Parrot-512.png new file mode 100644 index 0000000000..acabe0f27c Binary files /dev/null and b/docs/assets/Lincoln-and-Parrot-512.png differ diff --git a/docs/assets/invoke-web-server-1.png b/docs/assets/invoke-web-server-1.png new file mode 100644 index 0000000000..e97697ba70 Binary files /dev/null and b/docs/assets/invoke-web-server-1.png differ diff --git a/docs/assets/invoke-web-server-2.png b/docs/assets/invoke-web-server-2.png new file mode 100644 index 0000000000..a3348d6853 Binary files /dev/null and b/docs/assets/invoke-web-server-2.png differ diff --git a/docs/assets/invoke-web-server-3.png b/docs/assets/invoke-web-server-3.png new file mode 100644 index 0000000000..7d392cfecc Binary files /dev/null and b/docs/assets/invoke-web-server-3.png differ diff --git a/docs/assets/invoke-web-server-4.png b/docs/assets/invoke-web-server-4.png new file mode 100644 index 0000000000..2690356b8a Binary files /dev/null and b/docs/assets/invoke-web-server-4.png differ diff --git a/docs/assets/invoke-web-server-5.png b/docs/assets/invoke-web-server-5.png new file mode 100644 index 0000000000..eb451c9b9c Binary files /dev/null and b/docs/assets/invoke-web-server-5.png differ diff --git a/docs/assets/invoke-web-server-6.png b/docs/assets/invoke-web-server-6.png new file mode 100644 index 0000000000..4daf4cfd78 Binary files /dev/null and b/docs/assets/invoke-web-server-6.png differ diff --git a/docs/assets/invoke-web-server-7.png b/docs/assets/invoke-web-server-7.png new file mode 100644 index 0000000000..154d45e987 Binary files /dev/null and b/docs/assets/invoke-web-server-7.png differ diff --git a/docs/assets/invoke-web-server-8.png b/docs/assets/invoke-web-server-8.png new file mode 100644 index 0000000000..dc708b1117 Binary files /dev/null and b/docs/assets/invoke-web-server-8.png differ diff --git a/docs/assets/invoke_web_server.png b/docs/assets/invoke_web_server.png new file mode 100644 index 0000000000..cdb34a0835 Binary files /dev/null and b/docs/assets/invoke_web_server.png differ diff --git a/docs/assets/prompt-blending/blue-sphere-0.25-red-cube-0.75-hybrid.png b/docs/assets/prompt-blending/blue-sphere-0.25-red-cube-0.75-hybrid.png new file mode 100644 index 0000000000..854c804639 Binary files /dev/null and b/docs/assets/prompt-blending/blue-sphere-0.25-red-cube-0.75-hybrid.png differ diff --git a/docs/assets/prompt-blending/blue-sphere-0.5-red-cube-0.5-hybrid.png b/docs/assets/prompt-blending/blue-sphere-0.5-red-cube-0.5-hybrid.png new file mode 100644 index 0000000000..80d75aa84d Binary files /dev/null and b/docs/assets/prompt-blending/blue-sphere-0.5-red-cube-0.5-hybrid.png differ diff --git a/docs/assets/prompt-blending/blue-sphere-0.5-red-cube-0.5.png b/docs/assets/prompt-blending/blue-sphere-0.5-red-cube-0.5.png new file mode 100644 index 0000000000..d0cb8e389e Binary files /dev/null and b/docs/assets/prompt-blending/blue-sphere-0.5-red-cube-0.5.png differ diff --git a/docs/assets/prompt-blending/blue-sphere-0.75-red-cube-0.25-hybrid.png b/docs/assets/prompt-blending/blue-sphere-0.75-red-cube-0.25-hybrid.png new file mode 100644 index 0000000000..29b5a7fdcf Binary files /dev/null and b/docs/assets/prompt-blending/blue-sphere-0.75-red-cube-0.25-hybrid.png differ diff --git a/docs/assets/prompt-blending/blue-sphere-red-cube-hybrid.png b/docs/assets/prompt-blending/blue-sphere-red-cube-hybrid.png new file mode 100644 index 0000000000..f844e5937a Binary files /dev/null and b/docs/assets/prompt-blending/blue-sphere-red-cube-hybrid.png differ diff --git a/docs/features/CHANGELOG.md b/docs/features/CHANGELOG.md index a6258f6a56..80ec5cf3a2 100644 --- a/docs/features/CHANGELOG.md +++ b/docs/features/CHANGELOG.md @@ -4,7 +4,7 @@ title: Changelog # :octicons-log-16: Changelog -## v1.13 (in process) +## v1.13 - Supports a Google Colab notebook for a standalone server running on Google hardware [Arturo Mendivil](https://github.com/artmen1516) @@ -12,10 +12,10 @@ title: Changelog [Kevin Gibbons](https://github.com/bakkot) - WebUI supports incremental display of in-progress images during generation [Kevin Gibbons](https://github.com/bakkot) -- Output directory can be specified on the dream> command line. +- Output directory can be specified on the invoke> command line. - The grid was displaying duplicated images when not enough images to fill the final row [Muhammad Usama](https://github.com/SMUsamaShah) -- Can specify --grid on dream.py command line as the default. +- Can specify --grid on invoke.py command line as the default. - Miscellaneous internal bug and stability fixes. --- @@ -24,14 +24,14 @@ title: Changelog - Improved file handling, including ability to read prompts from standard input. (kudos to [Yunsaki](https://github.com/yunsaki) -- The web server is now integrated with the dream.py script. Invoke by adding - --web to the dream.py command arguments. +- The web server is now integrated with the invoke.py script. Invoke by adding + --web to the invoke.py command arguments. - Face restoration and upscaling via GFPGAN and Real-ESGAN are now automatically enabled if the GFPGAN directory is located as a sibling to Stable Diffusion. VRAM requirements are modestly reduced. Thanks to both [Blessedcoolant](https://github.com/blessedcoolant) and [Oceanswave](https://github.com/oceanswave) for their work on this. -- You can now swap samplers on the dream> command line. +- You can now swap samplers on the invoke> command line. [Blessedcoolant](https://github.com/blessedcoolant) --- @@ -45,7 +45,7 @@ title: Changelog back to the previous command, but will work on all images generated with the -n# switch. - Variant generation support temporarily disabled pending more general solution. -- Created a feature branch named **yunsaki-morphing-dream** which adds +- Created a feature branch named **yunsaki-morphing-invoke** which adds experimental support for iteratively modifying the prompt and its parameters. Please see[ Pull Request #86](https://github.com/lstein/stable-diffusion/pull/86) for @@ -75,7 +75,7 @@ title: Changelog ## v1.08 (24 August 2022) -- Escape single quotes on the dream> command before trying to parse. This avoids +- Escape single quotes on the invoke> command before trying to parse. This avoids parse errors. - Removed instruction to get Python3.8 as first step in Windows install. Anaconda3 does it for you. @@ -112,7 +112,7 @@ title: Changelog can be regenerated with the indicated key - It should no longer be possible for one image to overwrite another -- You can use the "cd" and "pwd" commands at the dream> prompt to set and +- You can use the "cd" and "pwd" commands at the invoke> prompt to set and retrieve the path of the output directory. ## v1.04 (22 August 2022 - after the drop) @@ -139,5 +139,5 @@ title: Changelog - added k_lms sampling. **Please run "conda env update -f environment.yaml" to load the k_lms dependencies!!** - use half precision arithmetic by default, resulting in faster execution and - lower memory requirements Pass argument --full_precision to dream.py to get + lower memory requirements Pass argument --full_precision to invoke.py to get slower but more accurate image generation diff --git a/docs/features/CLI.md b/docs/features/CLI.md index 312614c348..cf86b0cd64 100644 --- a/docs/features/CLI.md +++ b/docs/features/CLI.md @@ -8,8 +8,8 @@ hide: ## **Interactive Command Line Interface** -The `dream.py` script, located in `scripts/dream.py`, provides an interactive -interface to image generation similar to the "dream mothership" bot that Stable +The `invoke.py` script, located in `scripts/dream.py`, provides an interactive +interface to image generation similar to the "invoke mothership" bot that Stable AI provided on its Discord server. Unlike the `txt2img.py` and `img2img.py` scripts provided in the original @@ -34,21 +34,21 @@ The script is confirmed to work on Linux, Windows and Mac systems. currently rudimentary, but a much better replacement is on its way. ```bash -(ldm) ~/stable-diffusion$ python3 ./scripts/dream.py +(ldm) ~/stable-diffusion$ python3 ./scripts/invoke.py * Initializing, be patient... Loading model from models/ldm/text2img-large/model.ckpt (...more initialization messages...) * Initialization done! Awaiting your command... -dream> ashley judd riding a camel -n2 -s150 +invoke> ashley judd riding a camel -n2 -s150 Outputs: outputs/img-samples/00009.png: "ashley judd riding a camel" -n2 -s150 -S 416354203 outputs/img-samples/00010.png: "ashley judd riding a camel" -n2 -s150 -S 1362479620 -dream> "there's a fly in my soup" -n6 -g +invoke> "there's a fly in my soup" -n6 -g outputs/img-samples/00011.png: "there's a fly in my soup" -n6 -g -S 2685670268 seeds for individual rows: [2685670268, 1216708065, 2335773498, 822223658, 714542046, 3395302430] -dream> q +invoke> q # this shows how to retrieve the prompt stored in the saved image's metadata (ldm) ~/stable-diffusion$ python ./scripts/images2prompt.py outputs/img_samples/*.png @@ -57,10 +57,10 @@ dream> q 00011.png: "there's a fly in my soup" -n6 -g -S 2685670268 ``` -![dream-py-demo](../assets/dream-py-demo.png) +![invoke-py-demo](../assets/dream-py-demo.png) -The `dream>` prompt's arguments are pretty much identical to those used in the -Discord bot, except you don't need to type "!dream" (it doesn't hurt if you do). +The `invoke>` prompt's arguments are pretty much identical to those used in the +Discord bot, except you don't need to type "!invoke" (it doesn't hurt if you do). A significant change is that creation of individual images is now the default unless `--grid` (`-g`) is given. A full list is given in [List of prompt arguments](#list-of-prompt-arguments). @@ -73,7 +73,7 @@ the location of the model weight files. ### List of arguments recognized at the command line -These command-line arguments can be passed to `dream.py` when you first run it +These command-line arguments can be passed to `invoke.py` when you first run it from the Windows, Mac or Linux command line. Some set defaults that can be overridden on a per-prompt basis (see [List of prompt arguments] (#list-of-prompt-arguments). Others @@ -112,15 +112,15 @@ These arguments are deprecated but still work: | --laion400m | -l | False | Use older LAION400m weights; use `--model=laion400m` instead | **A note on path names:** On Windows systems, you may run into - problems when passing the dream script standard backslashed path + problems when passing the invoke script standard backslashed path names because the Python interpreter treats "\" as an escape. You can either double your slashes (ick): C:\\\\path\\\\to\\\\my\\\\file, or use Linux/Mac style forward slashes (better): C:/path/to/my/file. ## List of prompt arguments -After the dream.py script initializes, it will present you with a -**dream>** prompt. Here you can enter information to generate images +After the invoke.py script initializes, it will present you with a +**invoke>** prompt. Here you can enter information to generate images from text (txt2img), to embellish an existing image or sketch (img2img), or to selectively alter chosen regions of the image (inpainting). @@ -128,13 +128,13 @@ from text (txt2img), to embellish an existing image or sketch ### This is an example of txt2img: ~~~~ -dream> waterfall and rainbow -W640 -H480 +invoke> waterfall and rainbow -W640 -H480 ~~~~ This will create the requested image with the dimensions 640 (width) and 480 (height). -Here are the dream> command that apply to txt2img: +Here are the invoke> command that apply to txt2img: | Argument | Shortcut | Default | Description | |--------------------|------------|---------------------|--------------| @@ -167,7 +167,7 @@ the nearest multiple of 64. ### This is an example of img2img: ~~~~ -dream> waterfall and rainbow -I./vacation-photo.png -W640 -H480 --fit +invoke> waterfall and rainbow -I./vacation-photo.png -W640 -H480 --fit ~~~~ This will modify the indicated vacation photograph by making it more @@ -188,7 +188,7 @@ accepts additional options: ### This is an example of inpainting: ~~~~ -dream> waterfall and rainbow -I./vacation-photo.png -M./vacation-mask.png -W640 -H480 --fit +invoke> waterfall and rainbow -I./vacation-photo.png -M./vacation-mask.png -W640 -H480 --fit ~~~~ This will do the same thing as img2img, but image alterations will @@ -224,20 +224,20 @@ Some examples: Upscale to 4X its original size and fix faces using codeformer: ~~~ -dream> !fix 0000045.4829112.png -G1 -U4 -ft codeformer +invoke> !fix 0000045.4829112.png -G1 -U4 -ft codeformer ~~~ Use the GFPGAN algorithm to fix faces, then upscale to 3X using --embiggen: ~~~ -dream> !fix 0000045.4829112.png -G0.8 -ft gfpgan +invoke> !fix 0000045.4829112.png -G0.8 -ft gfpgan >> fixing outputs/img-samples/0000045.4829112.png >> retrieved seed 4829112 and prompt "boy enjoying a banana split" >> GFPGAN - Restoring Faces for image seed:4829112 Outputs: [1] outputs/img-samples/000017.4829112.gfpgan-00.png: !fix "outputs/img-samples/0000045.4829112.png" -s 50 -S -W 512 -H 512 -C 7.5 -A k_lms -G 0.8 -dream> !fix 000017.4829112.gfpgan-00.png --embiggen 3 +invoke> !fix 000017.4829112.gfpgan-00.png --embiggen 3 ...lots of text... Outputs: [2] outputs/img-samples/000018.2273800735.embiggen-00.png: !fix "outputs/img-samples/000017.243781548.gfpgan-00.png" -s 50 -S 2273800735 -W 512 -H 512 -C 7.5 -A k_lms --embiggen 3.0 0.75 0.25 @@ -251,9 +251,9 @@ provide either the name of a file in the current output directory, or a full file path. ~~~ -dream> !fetch 0000015.8929913.png +invoke> !fetch 0000015.8929913.png # the script returns the next line, ready for editing and running: -dream> a fantastic alien landscape -W 576 -H 512 -s 60 -A plms -C 7.5 +invoke> a fantastic alien landscape -W 576 -H 512 -s 60 -A plms -C 7.5 ~~~ Note that this command may behave unexpectedly if given a PNG file that @@ -261,7 +261,7 @@ was not generated by InvokeAI. ## !history -The dream script keeps track of all the commands you issue during a +The invoke script keeps track of all the commands you issue during a session, allowing you to re-run them. On Mac and Linux systems, it also writes the command-line history out to disk, giving you access to the most recent 1000 commands issued. @@ -272,7 +272,7 @@ issued during the session (Windows), or the most recent 1000 commands where "NNN" is the history line number. For example: ~~~ -dream> !history +invoke> !history ... [14] happy woman sitting under tree wearing broad hat and flowing garment [15] beautiful woman sitting under tree wearing broad hat and flowing garment @@ -280,8 +280,8 @@ dream> !history [20] watercolor of beautiful woman sitting under tree wearing broad hat and flowing garment -v0.2 -n6 -S2878767194 [21] surrealist painting of beautiful woman sitting under tree wearing broad hat and flowing garment -v0.2 -n6 -S2878767194 ... -dream> !20 -dream> watercolor of beautiful woman sitting under tree wearing broad hat and flowing garment -v0.2 -n6 -S2878767194 +invoke> !20 +invoke> watercolor of beautiful woman sitting under tree wearing broad hat and flowing garment -v0.2 -n6 -S2878767194 ~~~ ## !search @@ -290,7 +290,7 @@ This is similar to !history but it only returns lines that contain `search string`. For example: ~~~ -dream> !search surreal +invoke> !search surreal [21] surrealist painting of beautiful woman sitting under tree wearing broad hat and flowing garment -v0.2 -n6 -S2878767194 ~~~ @@ -312,16 +312,16 @@ command completion. - To paste a cut section back in, position the cursor where you want to paste, and type CTRL-Y Windows users can get similar, but more limited, functionality if they -launch dream.py with the "winpty" program and have the `pyreadline3` +launch invoke.py with the "winpty" program and have the `pyreadline3` library installed: ~~~ -> winpty python scripts\dream.py +> winpty python scripts\invoke.py ~~~ -On the Mac and Linux platforms, when you exit dream.py, the last 1000 +On the Mac and Linux platforms, when you exit invoke.py, the last 1000 lines of your command-line history will be saved. When you restart -dream.py, you can access the saved history using the up-arrow key. +invoke.py, you can access the saved history using the up-arrow key. In addition, limited command-line completion is installed. In various contexts, you can start typing your command and press tab. A list of @@ -334,7 +334,7 @@ will attempt to complete pathnames for you. This is most handy for the the path with a slash ("/") or "./". For example: ~~~ -dream> zebra with a mustache -I./test-pictures +invoke> zebra with a mustache -I./test-pictures -I./test-pictures/Lincoln-and-Parrot.png -I./test-pictures/zebra.jpg -I./test-pictures/madonna.png -I./test-pictures/bad-sketch.png -I./test-pictures/man_with_eagle/ ``` diff --git a/docs/features/EMBIGGEN.md b/docs/features/EMBIGGEN.md index 92b379b64b..6d74822a66 100644 --- a/docs/features/EMBIGGEN.md +++ b/docs/features/EMBIGGEN.md @@ -106,8 +106,8 @@ Running Embiggen with 512x512 tiles on an existing image, scaling up by a factor and doing the same again (default ESRGAN strength is 0.75, default overlap between tiles is 0.25): ```bash -dream > a photo of a forest at sunset -s 100 -W 512 -H 512 -I outputs/forest.png -f 0.4 -embiggen 2.5 -dream > a photo of a forest at sunset -s 100 -W 512 -H 512 -I outputs/forest.png -f 0.4 -embiggen 2.5 0.75 0.25 +invoke > a photo of a forest at sunset -s 100 -W 512 -H 512 -I outputs/forest.png -f 0.4 -embiggen 2.5 +invoke > a photo of a forest at sunset -s 100 -W 512 -H 512 -I outputs/forest.png -f 0.4 -embiggen 2.5 0.75 0.25 ``` If your starting image was also 512x512 this should have taken 9 tiles. @@ -118,7 +118,7 @@ If there weren't enough clouds in the sky of that forest you just made tiles: ```bash -dream> a photo of puffy clouds over a forest at sunset -s 100 -W 512 -H 512 -I outputs/000002.seed.png -f 0.5 -embiggen_tiles 1 2 3 +invoke> a photo of puffy clouds over a forest at sunset -s 100 -W 512 -H 512 -I outputs/000002.seed.png -f 0.5 -embiggen_tiles 1 2 3 ``` ## Fixing Previously-Generated Images @@ -129,7 +129,7 @@ syntax `!fix path/to/file.png `. For example, you can rewrite the previous command to look like this: ~~~~ -dream> !fix ./outputs/000002.seed.png -embiggen_tiles 1 2 3 +invoke> !fix ./outputs/000002.seed.png -embiggen_tiles 1 2 3 ~~~~ A new file named `000002.seed.fixed.png` will be created in the output directory. Note that diff --git a/docs/features/IMG2IMG.md b/docs/features/IMG2IMG.md index 47e8317a39..4f9b417ab6 100644 --- a/docs/features/IMG2IMG.md +++ b/docs/features/IMG2IMG.md @@ -10,18 +10,39 @@ top of the image you provide, preserving the original's basic shape and layout. the `--init_img` option as shown here: ```commandline -dream> "waterfall and rainbow" --init_img=./init-images/crude_drawing.png --strength=0.5 -s100 -n4 +tree on a hill with a river, nature photograph, national geographic -I./test-pictures/tree-and-river-sketch.png -f 0.85 ``` +This will take the original image shown here: + + + +and generate a new image based on it as shown here: + + + The `--init_img (-I)` option gives the path to the seed picture. `--strength (-f)` controls how much the original will be modified, ranging from `0.0` (keep the original intact), to `1.0` (ignore the -original completely). The default is `0.75`, and ranges from `0.25-0.75` give interesting results. +original completely). The default is `0.75`, and ranges from `0.25-0.90` give interesting results. +Other relevant options include `-C` (classification free guidance scale), and `-s` (steps). Unlike `txt2img`, +adding steps will continuously change the resulting image and it will not converge. You may also pass a `-v` option to generate `-n` count variants on the original image. This is done by passing the first generated image back into img2img the requested number of times. It generates interesting variants. +Note that the prompt makes a big difference. For example, this slight variation on the prompt produces +a very different image: + +`photograph of a tree on a hill with a river` + + + +(When designing prompts, think about how the images scraped from the internet were captioned. Very few photographs will +be labeled "photograph" or "photorealistic." They will, however, be captioned with the publication, photographer, camera +model, or film settings.) + If the initial image contains transparent regions, then Stable Diffusion will only draw within the transparent regions, a process called "inpainting". However, for this to work correctly, the color information underneath the transparent needs to be preserved, not erased. @@ -29,6 +50,17 @@ information underneath the transparent needs to be preserved, not erased. More details can be found here: [Creating Transparent Images For Inpainting](./INPAINTING.md#creating-transparent-regions-for-inpainting) +<<<<<<< HEAD +======= +**IMPORTANT ISSUE** `img2img` does not work properly on initial images smaller than 512x512. Please scale your +image to at least 512x512 before using it. Larger images are not a problem, but may run out of VRAM on your +GPU card. To fix this, use the --fit option, which downscales the initial image to fit within the box specified +by width x height: +~~~ +tree on a hill with a river, national geographic -I./test-pictures/big-sketch.png -H512 -W512 --fit +~~~ + +>>>>>>> main ## How does it actually work, though? The main difference between `img2img` and `prompt2img` is the starting point. While `prompt2img` always starts with pure @@ -38,7 +70,11 @@ gaussian noise and progressively refines it over the requested number of steps, **Let's start** by thinking about vanilla `prompt2img`, just generating an image from a prompt. If the step count is 10, then the "latent space" (Stable Diffusion's internal representation of the image) for the prompt "fire" with seed `1592514025` develops something like this: ```commandline +<<<<<<< HEAD dream> "fire" -s10 -W384 -H384 -S1592514025 +======= +invoke> "fire" -s10 -W384 -H384 -S1592514025 +>>>>>>> main ``` ![latent steps](../assets/img2img/000019.steps.png) @@ -66,7 +102,11 @@ Notice how much more fuzzy the starting image is for strength `0.7` compared to | | strength = 0.7 | strength = 0.4 | | -- | -- | -- | | initial image that SD sees | ![](../assets/img2img/000032.step-0.png) | ![](../assets/img2img/000030.step-0.png) | +<<<<<<< HEAD | steps argument to `dream>` | `-S10` | `-S10` | +======= +| steps argument to `invoke>` | `-S10` | `-S10` | +>>>>>>> main | steps actually taken | 7 | 4 | | latent space at each step | ![](../assets/img2img/000032.steps.gravity.png) | ![](../assets/img2img/000030.steps.gravity.png) | | output | ![](../assets/img2img/000032.1592514025.png) | ![](../assets/img2img/000030.1592514025.png) | @@ -77,10 +117,17 @@ Both of the outputs look kind of like what I was thinking of. With the strength If you want to try this out yourself, all of these are using a seed of `1592514025` with a width/height of `384`, step count `10`, the default sampler (`k_lms`), and the single-word prompt `fire`: ```commandline +<<<<<<< HEAD dream> "fire" -s10 -W384 -H384 -S1592514025 -I /tmp/fire-drawing.png --strength 0.7 ``` The code for rendering intermediates is on my (damian0815's) branch [document-img2img](https://github.com/damian0815/InvokeAI/tree/document-img2img) - run `dream.py` and check your `outputs/img-samples/intermediates` folder while generating an image. +======= +invoke> "fire" -s10 -W384 -H384 -S1592514025 -I /tmp/fire-drawing.png --strength 0.7 +``` + +The code for rendering intermediates is on my (damian0815's) branch [document-img2img](https://github.com/damian0815/InvokeAI/tree/document-img2img) - run `invoke.py` and check your `outputs/img-samples/intermediates` folder while generating an image. +>>>>>>> main ### Compensating for the reduced step count @@ -89,7 +136,11 @@ After putting this guide together I was curious to see how the difference would Here's strength `0.4` (note step count `50`, which is `20 ÷ 0.4` to make sure SD does `20` steps from my image): ```commandline +<<<<<<< HEAD dream> "fire" -s50 -W384 -H384 -S1592514025 -I /tmp/fire-drawing.png -f 0.4 +======= +invoke> "fire" -s50 -W384 -H384 -S1592514025 -I /tmp/fire-drawing.png -f 0.4 +>>>>>>> main ``` ![](../assets/img2img/000035.1592514025.png) @@ -97,7 +148,11 @@ dream> "fire" -s50 -W384 -H384 -S1592514025 -I /tmp/fire-drawing.png -f 0.4 and strength `0.7` (note step count `30`, which is roughly `20 ÷ 0.7` to make sure SD does `20` steps from my image): ```commandline +<<<<<<< HEAD dream> "fire" -s30 -W384 -H384 -S1592514025 -I /tmp/fire-drawing.png -f 0.7 +======= +invoke> "fire" -s30 -W384 -H384 -S1592514025 -I /tmp/fire-drawing.png -f 0.7 +>>>>>>> main ``` ![](../assets/img2img/000046.1592514025.png) diff --git a/docs/features/INPAINTING.md b/docs/features/INPAINTING.md index 497bbc7a48..38c7c8d397 100644 --- a/docs/features/INPAINTING.md +++ b/docs/features/INPAINTING.md @@ -8,7 +8,7 @@ title: Inpainting Inpainting is really cool. To do it, you start with an initial image and use a photoeditor to make one or more regions transparent (i.e. they have a "hole" in them). You then provide the path to this -image at the dream> command line using the `-I` switch. Stable Diffusion will only paint within the +image at the invoke> command line using the `-I` switch. Stable Diffusion will only paint within the transparent region. There's a catch. In the current implementation, you have to prepare the initial image correctly so @@ -17,13 +17,13 @@ applications will by default erase the color information under the transparent p them with white or black, which will lead to suboptimal inpainting. You also must take care to export the PNG file in such a way that the color information is preserved. -If your photoeditor is erasing the underlying color information, `dream.py` will give you a big fat +If your photoeditor is erasing the underlying color information, `invoke.py` will give you a big fat warning. If you can't find a way to coax your photoeditor to retain color values under transparent areas, then you can combine the `-I` and `-M` switches to provide both the original unedited image and the masked (partially transparent) image: ```bash -dream> "man with cat on shoulder" -I./images/man.png -M./images/man-transparent.png +invoke> "man with cat on shoulder" -I./images/man.png -M./images/man-transparent.png ``` We are hoping to get rid of the need for this workaround in an upcoming release. @@ -38,8 +38,8 @@ We are hoping to get rid of the need for this workaround in an upcoming release. 2. Layer->Transparency->Add Alpha Channel 3. Use lasoo tool to select region to mask 4. Choose Select -> Float to create a floating selection -5. Open the Layers toolbar (++ctrl+l++) and select "Floating Selection" -6. Set opacity to 0% +5. Open the Layers toolbar (^L) and select "Floating Selection" +6. Set opacity to a value between 0% and 99% 7. Export as PNG 8. In the export dialogue, Make sure the "Save colour values from transparent pixels" checkbox is selected. @@ -69,7 +69,7 @@ We are hoping to get rid of the need for this workaround in an upcoming release. ![step6](../assets/step6.png) -7. After following the inpainting instructions above (either through the CLI or the Web UI), marvel at your newfound ability to selectively dream. Lookin' good! +7. After following the inpainting instructions above (either through the CLI or the Web UI), marvel at your newfound ability to selectively invoke. Lookin' good! ![step7](../assets/step7.png) diff --git a/docs/features/OTHER.md b/docs/features/OTHER.md index 6aab528275..820b46c32d 100644 --- a/docs/features/OTHER.md +++ b/docs/features/OTHER.md @@ -22,10 +22,10 @@ Output Example: ![Colab Notebook](../assets/colab_notebook.png) The seamless tiling mode causes generated images to seamlessly tile with itself. To use it, add the `--seamless` option when starting the script which will result in all generated images to tile, or -for each `dream>` prompt as shown here: +for each `invoke>` prompt as shown here: ```python -dream> "pond garden with lotus by claude monet" --seamless -s100 -n4 +invoke> "pond garden with lotus by claude monet" --seamless -s100 -n4 ``` --- @@ -42,12 +42,12 @@ Here's an example of using this to do a quick refinement. It also illustrates us switch to turn on upscaling and face enhancement (see previous section): ```bash -dream> a cute child playing hopscotch -G0.5 +invoke> a cute child playing hopscotch -G0.5 [...] outputs/img-samples/000039.3498014304.png: "a cute child playing hopscotch" -s50 -W512 -H512 -C7.5 -mk_lms -S3498014304 # I wonder what it will look like if I bump up the steps and set facial enhancement to full strength? -dream> a cute child playing hopscotch -G1.0 -s100 -S -1 +invoke> a cute child playing hopscotch -G1.0 -s100 -S -1 reusing previous seed 3498014304 [...] outputs/img-samples/000040.3498014304.png: "a cute child playing hopscotch" -G1.0 -s100 -W512 -H512 -C7.5 -mk_lms -S3498014304 diff --git a/docs/features/OUTPAINTING.md b/docs/features/OUTPAINTING.md index 952bbc97fc..7d54f1bfc9 100644 --- a/docs/features/OUTPAINTING.md +++ b/docs/features/OUTPAINTING.md @@ -31,7 +31,7 @@ Pretty nice, but it's annoying that the top of her head is cut off. She's also a bit off center. Let's fix that! ~~~~ -dream> !fix images/curly.png --outcrop top 64 right 64 +invoke> !fix images/curly.png --outcrop top 64 right 64 ~~~~ This is saying to apply the `outcrop` extension by extending the top @@ -67,7 +67,7 @@ differences. Starting with the same image, here is how we would add an additional 64 pixels to the top of the image: ~~~ -dream> !fix images/curly.png --out_direction top 64 +invoke> !fix images/curly.png --out_direction top 64 ~~~ (you can abbreviate ``--out_direction` as `-D`. diff --git a/docs/features/POSTPROCESS.md b/docs/features/POSTPROCESS.md index cd4fd7e9e6..b5156f54f0 100644 --- a/docs/features/POSTPROCESS.md +++ b/docs/features/POSTPROCESS.md @@ -20,39 +20,33 @@ The default face restoration module is GFPGAN. The default upscale is Real-ESRGAN. For an alternative face restoration module, see [CodeFormer Support] below. -As of version 1.14, environment.yaml will install the Real-ESRGAN package into -the standard install location for python packages, and will put GFPGAN into a -subdirectory of "src" in the InvokeAI directory. (The reason for this is -that the standard GFPGAN distribution has a minor bug that adversely affects -image color.) Upscaling with Real-ESRGAN should "just work" without further -intervention. Simply pass the --upscale (-U) option on the dream> command line, -or indicate the desired scale on the popup in the Web GUI. +As of version 1.14, environment.yaml will install the Real-ESRGAN +package into the standard install location for python packages, and +will put GFPGAN into a subdirectory of "src" in the InvokeAI +directory. Upscaling with Real-ESRGAN should "just work" without +further intervention. Simply pass the --upscale (-U) option on the +invoke> command line, or indicate the desired scale on the popup in +the Web GUI. -For **GFPGAN** to work, there is one additional step needed. You will need to -download and copy the GFPGAN -[models file](https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.4.pth) -into **src/gfpgan/experiments/pretrained_models**. On Mac and Linux systems, -here's how you'd do it using **wget**: +**GFPGAN** requires a series of downloadable model files to +work. These are loaded when you run `scripts/preload_models.py`. If +GFPAN is failing with an error, please run the following from the +InvokeAI directory: -```bash -wget https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.4.pth -P src/gfpgan/experiments/pretrained_models/ -``` +~~~~ +python scripts/preload_models.py +~~~~ -Make sure that you're in the InvokeAI directory when you do this. +If you do not run this script in advance, the GFPGAN module will attempt +to download the models files the first time you try to perform facial +reconstruction. -Alternatively, if you have GFPGAN installed elsewhere, or if you are using an -earlier version of this package which asked you to install GFPGAN in a sibling -directory, you may use the `--gfpgan_dir` argument with `dream.py` to set a -custom path to your GFPGAN directory. _There are other GFPGAN related boot -arguments if you wish to customize further._ - -!!! warning "Internet connection needed" - - Users whose GPU machines are isolated from the Internet (e.g. - on a University cluster) should be aware that the first time you run dream.py with GFPGAN and - Real-ESRGAN turned on, it will try to download model files from the Internet. To rectify this, you - may run `python3 scripts/preload_models.py` after you have installed GFPGAN and all its - dependencies. +Alternatively, if you have GFPGAN installed elsewhere, or if you are +using an earlier version of this package which asked you to install +GFPGAN in a sibling directory, you may use the `--gfpgan_dir` argument +with `invoke.py` to set a custom path to your GFPGAN directory. _There +are other GFPGAN related boot arguments if you wish to customize +further._ ## Usage @@ -94,13 +88,13 @@ too. ### Example Usage ```bash -dream> superman dancing with a panda bear -U 2 0.6 -G 0.4 +invoke> superman dancing with a panda bear -U 2 0.6 -G 0.4 ``` This also works with img2img: ```bash -dream> a man wearing a pineapple hat -I path/to/your/file.png -U 2 0.5 -G 0.6 +invoke> a man wearing a pineapple hat -I path/to/your/file.png -U 2 0.5 -G 0.6 ``` !!! note @@ -124,15 +118,15 @@ actions. This repo also allows you to perform face restoration using [CodeFormer](https://github.com/sczhou/CodeFormer). -In order to setup CodeFormer to work, you need to download the models like with -GFPGAN. You can do this either by running `preload_models.py` or by manually -downloading the -[model file](https://github.com/sczhou/CodeFormer/releases/download/v0.1.0/codeformer.pth) +In order to setup CodeFormer to work, you need to download the models +like with GFPGAN. You can do this either by running +`preload_models.py` or by manually downloading the [model +file](https://github.com/sczhou/CodeFormer/releases/download/v0.1.0/codeformer.pth) and saving it to `ldm/restoration/codeformer/weights` folder. -You can use `-ft` prompt argument to swap between CodeFormer and the default -GFPGAN. The above mentioned `-G` prompt argument will allow you to control the -strength of the restoration effect. +You can use `-ft` prompt argument to swap between CodeFormer and the +default GFPGAN. The above mentioned `-G` prompt argument will allow +you to control the strength of the restoration effect. ### Usage: @@ -168,7 +162,7 @@ previously-generated file. Just use the syntax `!fix path/to/file.png just run: ``` -dream> !fix ./outputs/img-samples/000044.2945021133.png -G 0.8 -U 2 +invoke> !fix ./outputs/img-samples/000044.2945021133.png -G 0.8 -U 2 ``` A new file named `000044.2945021133.fixed.png` will be created in the output @@ -178,5 +172,5 @@ unlike the behavior at generate time. ### Disabling: If, for some reason, you do not wish to load the GFPGAN and/or ESRGAN libraries, -you can disable them on the dream.py command line with the `--no_restore` and +you can disable them on the invoke.py command line with the `--no_restore` and `--no_upscale` options, respectively. diff --git a/docs/features/PROMPTS.md b/docs/features/PROMPTS.md index f3bb9cef86..361a2fd5bc 100644 --- a/docs/features/PROMPTS.md +++ b/docs/features/PROMPTS.md @@ -6,9 +6,9 @@ title: Prompting Features ## **Reading Prompts from a File** -You can automate `dream.py` by providing a text file with the prompts you want to run, one line per +You can automate `invoke.py` by providing a text file with the prompts you want to run, one line per prompt. The text file must be composed with a text editor (e.g. Notepad) and not a word processor. -Each line should look like what you would type at the dream> prompt: +Each line should look like what you would type at the invoke> prompt: ```bash a beautiful sunny day in the park, children playing -n4 -C10 @@ -16,39 +16,23 @@ stormy weather on a mountain top, goats grazing -s100 innovative packaging for a squid's dinner -S137038382 ``` -Then pass this file's name to `dream.py` when you invoke it: +Then pass this file's name to `invoke.py` when you invoke it: ```bash -(ldm) ~/stable-diffusion$ python3 scripts/dream.py --from_file "path/to/prompts.txt" +(ldm) ~/stable-diffusion$ python3 scripts/invoke.py --from_file "path/to/prompts.txt" ``` You may read a series of prompts from standard input by providing a filename of `-`: ```bash -(ldm) ~/stable-diffusion$ echo "a beautiful day" | python3 scripts/dream.py --from_file - +(ldm) ~/stable-diffusion$ echo "a beautiful day" | python3 scripts/invoke.py --from_file - ``` - ---- - -## **Weighted Prompts** - -You may weight different sections of the prompt to tell the sampler to attach different levels of -priority to them, by adding `:(number)` to the end of the section you wish to up- or downweight. For -example consider this prompt: - -```bash -tabby cat:0.25 white duck:0.75 hybrid -``` - -This will tell the sampler to invest 25% of its effort on the tabby cat aspect of the image and 75% -on the white duck aspect (surprisingly, this example actually works). The prompt weights can use any -combination of integers and floating point numbers, and they do not need to add up to 1. - --- ## **Negative and Unconditioned Prompts** -Any words between a pair of square brackets will try and be ignored by Stable Diffusion's model during generation of images. +Any words between a pair of square brackets will instruct Stable +Diffusion to attempt to ban the concept from the generated image. ```bash this is a test prompt [not really] to make you understand [cool] how this works. @@ -88,3 +72,78 @@ Getting close - but there's no sense in having a saddle when our horse doesn't h * You can provide multiple words within the same bracket. * You can provide multiple brackets with multiple words in different places of your prompt. That works just fine. * To improve typical anatomy problems, you can add negative prompts like `[bad anatomy, extra legs, extra arms, extra fingers, poorly drawn hands, poorly drawn feet, disfigured, out of frame, tiling, bad art, deformed, mutated]`. + +--- + +## **Prompt Blending** + +You may blend together different sections of the prompt to explore the +AI's latent semantic space and generate interesting (and often +surprising!) variations. The syntax is: + +```bash +blue sphere:0.25 red cube:0.75 hybrid +``` + +This will tell the sampler to blend 25% of the concept of a blue +sphere with 75% of the concept of a red cube. The blend weights can +use any combination of integers and floating point numbers, and they +do not need to add up to 1. Everything to the left of the `:XX` up to +the previous `:XX` is used for merging, so the overall effect is: + +```bash +0.25 * "blue sphere" + 0.75 * "white duck" + hybrid +``` + +Because you are exploring the "mind" of the AI, the AI's way of mixing +two concepts may not match yours, leading to surprising effects. To +illustrate, here are three images generated using various combinations +of blend weights. As usual, unless you fix the seed, the prompts will give you +different results each time you run them. + +### "blue sphere, red cube, hybrid" + +This example doesn't use melding at all and represents the default way +of mixing concepts. + + + +It's interesting to see how the AI expressed the concept of "cube" as +the four quadrants of the enclosing frame. If you look closely, there +is depth there, so the enclosing frame is actually a cube. + +### "blue sphere:0.25 red cube:0.75 hybrid" + + + +Now that's interesting. We get neither a blue sphere nor a red cube, +but a red sphere embedded in a brick wall, which represents a melding +of concepts within the AI's "latent space" of semantic +representations. Where is Ludwig Wittgenstein when you need him? + +### "blue sphere:0.75 red cube:0.25 hybrid" + + + +Definitely more blue-spherey. The cube is gone entirely, but it's +really cool abstract art. + +### "blue sphere:0.5 red cube:0.5 hybrid" + + + +Whoa...! I see blue and red, but no spheres or cubes. Is the word +"hybrid" summoning up the concept of some sort of scifi creature? +Let's find out. + +### "blue sphere:0.5 red cube:0.5" + + + +Indeed, removing the word "hybrid" produces an image that is more like +what we'd expect. + +In conclusion, prompt blending is great for exploring creative space, +but can be difficult to direct. A forthcoming release of InvokeAI will +feature more deterministic prompt weighting. + diff --git a/docs/features/TEXTUAL_INVERSION.md b/docs/features/TEXTUAL_INVERSION.md index 50532968a8..15ac0891ad 100644 --- a/docs/features/TEXTUAL_INVERSION.md +++ b/docs/features/TEXTUAL_INVERSION.md @@ -56,22 +56,22 @@ configs/stable_diffusion/v1-finetune.yaml (currently set to 4000000) ## **Run the Model** Once the model is trained, specify the trained .pt or .bin file when starting -dream using +invoke using ```bash -python3 ./scripts/dream.py --embedding_path /path/to/embedding.pt +python3 ./scripts/invoke.py --embedding_path /path/to/embedding.pt ``` -Then, to utilize your subject at the dream prompt +Then, to utilize your subject at the invoke prompt ```bash -dream> "a photo of *" +invoke> "a photo of *" ``` This also works with image2image ```bash -dream> "waterfall and rainbow in the style of *" --init_img=./init-images/crude_drawing.png --strength=0.5 -s100 -n4 +invoke> "waterfall and rainbow in the style of *" --init_img=./init-images/crude_drawing.png --strength=0.5 -s100 -n4 ``` For .pt files it's also possible to train multiple tokens (modify the diff --git a/docs/features/VARIATIONS.md b/docs/features/VARIATIONS.md index e021c300fb..b8640d3a4f 100644 --- a/docs/features/VARIATIONS.md +++ b/docs/features/VARIATIONS.md @@ -34,7 +34,7 @@ First we let SD create a series of images in the usual way, in this case requesting six iterations: ```bash -dream> lucy lawless as xena, warrior princess, character portrait, high resolution -n6 +invoke> lucy lawless as xena, warrior princess, character portrait, high resolution -n6 ... Outputs: ./outputs/Xena/000001.1579445059.png: "prompt" -s50 -W512 -H512 -C7.5 -Ak_lms -S1579445059 @@ -57,7 +57,7 @@ differing by a variation amount of 0.2. This number ranges from `0` to `1.0`, with higher numbers being larger amounts of variation. ```bash -dream> "prompt" -n6 -S3357757885 -v0.2 +invoke> "prompt" -n6 -S3357757885 -v0.2 ... Outputs: ./outputs/Xena/000002.784039624.png: "prompt" -s50 -W512 -H512 -C7.5 -Ak_lms -V 784039624:0.2 -S3357757885 @@ -89,7 +89,7 @@ We combine the two variations using `-V` (`--with_variations`). Again, we must provide the seed for the originally-chosen image in order for this to work. ```bash -dream> "prompt" -S3357757885 -V3647897225,0.1,1614299449,0.1 +invoke> "prompt" -S3357757885 -V3647897225,0.1,1614299449,0.1 Outputs: ./outputs/Xena/000003.1614299449.png: "prompt" -s50 -W512 -H512 -C7.5 -Ak_lms -V 3647897225:0.1,1614299449:0.1 -S3357757885 ``` @@ -105,7 +105,7 @@ latter, using both the `-V` (combining) and `-v` (variation strength) options. Note that we use `-n6` to generate 6 variations: ```bash -dream> "prompt" -S3357757885 -V3647897225,0.1,1614299449,0.1 -v0.05 -n6 +invoke> "prompt" -S3357757885 -V3647897225,0.1,1614299449,0.1 -v0.05 -n6 Outputs: ./outputs/Xena/000004.3279757577.png: "prompt" -s50 -W512 -H512 -C7.5 -Ak_lms -V 3647897225:0.1,1614299449:0.1,3279757577:0.05 -S3357757885 ./outputs/Xena/000004.2853129515.png: "prompt" -s50 -W512 -H512 -C7.5 -Ak_lms -V 3647897225:0.1,1614299449:0.1,2853129515:0.05 -S3357757885 diff --git a/docs/features/WEB.md b/docs/features/WEB.md index ffc48f47f7..3be5f618e6 100644 --- a/docs/features/WEB.md +++ b/docs/features/WEB.md @@ -1,24 +1,290 @@ --- -title: InvokeAI Web UI & Server +title: InvokeAI Web Server --- -# :material-web: InvokeAI Web Server - -As of version 2.0, this distribution's web server has been updated to include -an all-new UI, with optimizations to improve common workflows for image generation. - -## Getting Started & Initialization Commands - -To start the web server, run the `dream.py` script by adding the `--web` parameter. +As of version 2.0.0, this distribution comes with a full-featured web +server (see screenshot). To use it, run the `invoke.py` script by +adding the `--web` option: ```bash -(ldm) ~/stable-diffusion$ python3 scripts/dream.py --web +(ldm) ~/InvokeAI$ python3 scripts/invoke.py --web ``` You can then connect to the server by pointing your web browser at -http://localhost:9090, or to the network name or IP address of the server. +http://localhost:9090. To reach the server from a different machine on +your LAN, you may launch the web server with the `--host` argument and +either the IP address of the host you are running it on, or the +wildcard `0.0.0.0`. For example: -### Additional Options +```bash +(ldm) ~/InvokeAI$ python3 scripts/invoke.py --web --host 0.0.0.0 +``` + +# Quick guided walkthrough of the WebGUI's features + +While most of the WebGUI's features are intuitive, here is a guided +walkthrough through its various components. + + + +The screenshot above shows the Text to Image tab of the WebGUI. There +are three main sections: + +1. A **control panel** on the left, which contains various settings +for text to image generation. The most important part is the text +field (currently showing `strawberry sushi`) for entering the text +prompt, and the camera icon directly underneath that will render the +image. We'll call this the *Invoke* button from now on. + +2. The **current image** section in the middle, which shows a large +format version of the image you are currently working on. A series of +buttons at the top ("image to image", "Use All", "Use Seed", etc) lets +you modify the image in various ways. + +3. A **gallery* section on the left that contains a history of the +images you have generated. These images are read and written to the +directory specified at launch time in `--outdir`. + +In addition to these three elements, there are a series of icons for +changing global settings, reporting bugs, and changing the theme on +the upper right. + +There are also a series of icons to the left of the control panel (see +highlighted area in the screenshot below) which select among a series +of tabs for performing different types of operations. + + + +From top to bottom, these are: + +1. Text to Image - generate images from text +2. Image to Image - from an uploaded starting image (drawing or photograph) generate a new one, modified by the text prompt +3. Inpainting (pending) - Interactively erase portions of a starting image and have the AI fill in the erased region from a text prompt. +4. Outpainting (pending) - Interactively add blank space to the borders of a starting image and fill in the background from a text prompt. +5. Postprocessing (pending) - Interactively postprocess generated images using a variety of filters. + +The inpainting, outpainting and postprocessing tabs are currently in +development. However, limited versions of their features can already +be accessed through the Text to Image and Image to Image tabs. + +## Walkthrough + +The following walkthrough will exercise most (but not all) of the +WebGUI's feature set. + +### Text to Image + +1. Launch the WebGUI using `python scripts/invoke.py --web` and +connect to it with your browser by accessing +`http://localhost:9090`. If the browser and server are running on +different machines on your LAN, add the option `--host 0.0.0.0` to the +launch command line and connect to the machine hosting the web server +using its IP address or domain name. + +2. If all goes well, the WebGUI should come up and you'll see a green +`connected` message on the upper right. + +#### Basics + +3. Generate an image by typing *strawberry sushi* into the large +prompt field on the upper left and then clicking on the Invoke button +(the one with the Camera icon). After a short wait, you'll see a large +image of sushi in the image panel, and a new thumbnail in the gallery +on the right. + +If you need more room on the screen, you can turn the gallery off +by clicking on the **x** to the right of "Your Invocations". You can +turn it back on later by clicking the image icon that appears in the +gallery's place. + +The images are written into the directory indicated by the `--outdir` +option provided at script launch time. By default, this is +`outputs/img-samples` under the InvokeAI directory. + +4. Generate a bunch of strawberry sushi images by increasing the +number of requested images by adjusting the Images counter just below +the Camera button. As each is generated, it will be added to the +gallery. You can switch the active image by clicking on the gallery +thumbnails. + +5. Try playing with different settings, including image width and +height, the Sampler, the Steps and the CFG scale. + +Image *Width* and *Height* do what you'd expect. However, be aware that +larger images consume more VRAM memory and take longer to generate. + +The *Sampler* controls how the AI selects the image to display. Some +samplers are more "creative" than others and will produce a wider +range of variations (see next section). Some samplers run faster than +others. + +*Steps* controls how many noising/denoising/sampling steps the AI will +take. The higher this value, the more refined the image will be, but +the longer the image will take to generate. A typical strategy is to +generate images with a low number of steps in order to select one to +work on further, and then regenerate it using a higher number of +steps. + +The *CFG Scale* controls how hard the AI tries to match the generated +image to the input prompt. You can go as high or low as you like, but +generally values greater than 20 won't improve things much, and values +lower than 5 will produce unexpected images. There are complex +interactions between *Steps*, *CFG Scale* and the *Sampler*, so +experiment to find out what works for you. + +6. To regenerate a previously-generated image, select the image you +want and click *Use All*. This loads the text prompt and other +original settings into the control panel. If you then press *Invoke* +it will regenerate the image exactly. You can also selectively modify +the prompt or other settings to tweak the image. + +Alternatively, you may click on *Use Seed* to load just the image's +seed, and leave other settings unchanged. + +7. To regenerate a Stable Diffusion image that was generated by +another SD package, you need to know its text prompt and its +*Seed*. Copy-paste the prompt into the prompt box, unset the +*Randomize Seed* control in the control panel, and copy-paste the +desired *Seed* into its text field. When you Invoke, you will get +something similar to the original image. It will not be exact unless +you also set the correct values for the original sampler, CFG, +steps and dimensions, but it will (usually) be close. + +#### Variations on a theme + +5. Let's try generating some variations. Select your favorite sushi +image from the gallery to load it. Then select "Use All" from the list +of buttons above. This will load up all the settings used to generate +this image, including its unique seed. + +Go down to the Variations section of the Control Panel and set the +button to On. Set Variation Amount to 0.2 to generate a modest +number of variations on the image, and also set the Image counter to +4. Press the `invoke` button. This will generate a series of related +images. To obtain smaller variations, just lower the Variation +Amount. You may also experiment with changing the Sampler. Some +samplers generate more variability than others. *k_euler_a* is +particularly creative, while *ddim* is pretty conservative. + +6. For even more variations, experiment with increasing the setting +for *Perlin*. This adds a bit of noise to the image generation +process. Note that values of Perlin noise greater than 0.15 produce +poor images for several of the samplers. + +#### Facial reconstruction and upscaling + +Stable Diffusion frequently produces mangled faces, particularly when +there are multiple figures in the same scene. Stable Diffusion has +particular issues with generating reallistic eyes. InvokeAI provides +the ability to reconstruct faces using either the GFPGAN or CodeFormer +libraries. For more information see [POSTPROCESS](POSTPROCESS.md). + +7. Invoke a prompt that generates a mangled face. A prompt that often +gives this is "portrait of a lawyer, 3/4 shot" (this is not intended +as a slur against lawyers!) Once you have an image that needs some +touching up, load it into the Image panel, and press the button with +the face icon (highlighted in the first screenshot below). A dialog +box will appear. Leave *Strength* at 0.8 and press *Restore Faces". If +all goes well, the eyes and other aspects of the face will be improved +(see the second screenshot) + + + + +The facial reconstruction *Strength* field adjusts how aggressively +the face library will try to alter the face. It can be as high as 1.0, +but be aware that this often softens the face airbrush style, losing +some details. The default 0.8 is usually sufficient. + +8. "Upscaling" is the process of increasing the size of an image while +retaining the sharpness. InvokeAI uses an external library called +"ESRGAN" to do this. To invoke upscaling, simply select an image and +press the *HD* button above it. You can select between 2X and 4X +upscaling, and adjust the upscaling strength, which has much the same +meaning as in facial reconstruction. Try running this on one of your +previously-generated images. + +9. Finally, you can run facial reconstruction and/or upscaling +automatically after each Invocation. Go to the Advanced Options +section of the Control Panel and turn on *Restore Face* and/or +*Upscale*. + +### Image to Image + +InvokeAI lets you take an existing image and use it as the basis for a +new creation. You can use any sort of image, including a photograph, a +scanned sketch, or a digital drawing, as long as it is in PNG or JPEG +format. + +For this tutorial, we'll use files named +[Lincoln-and-Parrot-512.png](../assets/Lincoln-and-Parrot-512.png), +and +[Lincoln-and-Parrot-512-transparent.png](../assets/Lincoln-and-Parrot-512-transparent.png). +Download these images to your local machine now to continue with the walkthrough. + +10. Click on the *Image to Image* tab icon, which is the second icon +from the top on the left-hand side of the screen: + + + +This will bring you to a screen similar to the one shown here: + + + +Drag-and-drop the Lincoln-and-Parrot image into the Image panel, or +click the blank area to get an upload dialog. The image will load into +an area marked *Initial Image*. (The WebGUI will also load the most +recently-generated image from the gallery into a section on the left, +but this image will be replaced in the next step.) + +11. Go to the prompt box and type *old sea captain with raven on +shoulder* and press Invoke. A derived image will appear to the right +of the original one: + + + +12. Experiment with the different settings. The most influential one +in Image to Image is *Image to Image Strength* located about midway +down the control panel. By default it is set to 0.75, but can range +from 0.0 to 0.99. The higher the value, the more of the original image +the AI will replace. A value of 0 will leave the initial image +completely unchanged, while 0.99 will replace it completely. However, +the Sampler and CFG Scale also influence the final result. You can +also generate variations in the same way as described in Text to +Image. + +13. What if we only want to change certain part(s) of the image and +leave the rest intact? This is called Inpainting, and a future version +of the InvokeAI web server will provide an interactive painting canvas +on which you can directly draw the areas you wish to Inpaint into. For +now, you can achieve this effect by using an external photoeditor tool +to make one or more regions of the image transparent as described in +[INPAINTING.md] and uploading that. + +The file +[Lincoln-and-Parrot-512-transparent.png](../assets/Lincoln-and-Parrot-512-transparent.png) +is a version of the earlier image in which the area around the parrot +has been replaced with transparency. Click on the "x" in the upper +right of the Initial Image and upload the transparent version. Using +the same prompt "old sea captain with raven on shoulder" try Invoking +an image. This time, only the parrot will be replaced, leaving the +rest of the original image intact: + + + +## Parting remarks + +This concludes the walkthrough, but there are several more features that you +can explore. Please check out the [Command Line Interface](CLI.md) +documentation for further explanation of the advanced features that +were not covered here. + +The WebGUI is only rapid development. Check back regularly for +updates! + +# Reference + +## Additional Options `--web_develop` - Starts the web server in development mode. `--web_verbose` - Enables verbose logging @@ -72,4 +338,3 @@ When an image from the Invocation Gallery is selected, or is generated, the imag ## Acknowledgements A huge shout-out to the core team working to make this vision a reality, including [psychedelicious](https://github.com/psychedelicious), [Kyle0654](https://github.com/Kyle0654) and [blessedcoolant](https://github.com/blessedcoolant). [hipsterusername](https://github.com/hipsterusername) was the team's unofficial cheerleader and added tooltips/docs. - diff --git a/docs/help/TROUBLESHOOT.md b/docs/help/TROUBLESHOOT.md index 22dc364556..8ff92f5be0 100644 --- a/docs/help/TROUBLESHOOT.md +++ b/docs/help/TROUBLESHOOT.md @@ -51,7 +51,7 @@ rm ${PIP_LOG} ### **QUESTION** -`dream.py` crashes with the complaint that it can't find `ldm.simplet2i.py`. Or it complains that +`invoke.py` crashes with the complaint that it can't find `ldm.simplet2i.py`. Or it complains that function is being passed incorrect parameters. ### **SOLUTION** @@ -63,7 +63,7 @@ Reinstall the stable diffusion modules. Enter the `stable-diffusion` directory a ### **QUESTION** -`dream.py` dies, complaining of various missing modules, none of which starts with `ldm``. +`invoke.py` dies, complaining of various missing modules, none of which starts with `ldm``. ### **SOLUTION** diff --git a/docs/index.md b/docs/index.md index c356c2cee5..bd04545904 100644 --- a/docs/index.md +++ b/docs/index.md @@ -28,7 +28,7 @@ template: main.html [CI checks on dev badge]: https://flat.badgen.net/github/checks/lstein/stable-diffusion/development?label=CI%20status%20on%20dev&cache=900&icon=github [CI checks on dev link]: https://github.com/lstein/stable-diffusion/actions?query=branch%3Adevelopment [CI checks on main badge]: https://flat.badgen.net/github/checks/lstein/stable-diffusion/main?label=CI%20status%20on%20main&cache=900&icon=github -[CI checks on main link]: https://github.com/lstein/stable-diffusion/actions/workflows/test-dream-conda.yml +[CI checks on main link]: https://github.com/lstein/stable-diffusion/actions/workflows/test-invoke-conda.yml [discord badge]: https://flat.badgen.net/discord/members/htRgbc7e?icon=discord [discord link]: https://discord.com/invite/htRgbc7e [github forks badge]: https://flat.badgen.net/github/forks/lstein/stable-diffusion?icon=github @@ -85,21 +85,21 @@ You wil need one of the following: !!! note - If you are have a Nvidia 10xx series card (e.g. the 1080ti), please run the dream script in + If you are have a Nvidia 10xx series card (e.g. the 1080ti), please run the invoke script in full-precision mode as shown below. Similarly, specify full-precision mode on Apple M1 hardware. - To run in full-precision mode, start `dream.py` with the `--full_precision` flag: + To run in full-precision mode, start `invoke.py` with the `--full_precision` flag: ```bash - (ldm) ~/stable-diffusion$ python scripts/dream.py --full_precision + (ldm) ~/stable-diffusion$ python scripts/invoke.py --full_precision ``` ## :octicons-log-16: Latest Changes ### vNEXT (TODO 2022) - - Deprecated `--full_precision` / `-F`. Simply omit it and `dream.py` will auto + - Deprecated `--full_precision` / `-F`. Simply omit it and `invoke.py` will auto configure. To switch away from auto use the new flag like `--precision=float32`. ### v1.14 (11 September 2022) @@ -124,7 +124,7 @@ You wil need one of the following: [Kevin Gibbons](https://github.com/bakkot) - A new configuration file scheme that allows new models (including upcoming stable-diffusion-v1.5) to be added without altering the code. ([David Wager](https://github.com/maddavid12)) -- Can specify --grid on dream.py command line as the default. +- Can specify --grid on invoke.py command line as the default. - Miscellaneous internal bug and stability fixes. - Works on M1 Apple hardware. - Multiple bug fixes. diff --git a/docs/installation/INSTALL_DOCKER.md b/docs/installation/INSTALL_DOCKER.md index c7dd3582d5..880b216f3c 100644 --- a/docs/installation/INSTALL_DOCKER.md +++ b/docs/installation/INSTALL_DOCKER.md @@ -136,7 +136,7 @@ $TAG_STABLE_DIFFUSION ## Startup -If you're on a **Linux container** the `dream` script is **automatically +If you're on a **Linux container** the `invoke` script is **automatically started** and the output dir set to the Docker volume you created earlier. If you're **directly on macOS follow these startup instructions**. @@ -148,14 +148,14 @@ half-precision requires autocast and won't work. By default the images are saved in `outputs/img-samples/`. ```Shell -python3 scripts/dream.py --full_precision +python3 scripts/invoke.py --full_precision ``` You'll get the script's prompt. You can see available options or quit. ```Shell -dream> -h -dream> q +invoke> -h +invoke> q ``` ## Text to Image @@ -166,10 +166,10 @@ Then increase steps to 100 or more for good (but slower) results. The prompt can be in quotes or not. ```Shell -dream> The hulk fighting with sheldon cooper -s5 -n1 -dream> "woman closeup highly detailed" -s 150 +invoke> The hulk fighting with sheldon cooper -s5 -n1 +invoke> "woman closeup highly detailed" -s 150 # Reuse previous seed and apply face restoration -dream> "woman closeup highly detailed" --steps 150 --seed -1 -G 0.75 +invoke> "woman closeup highly detailed" --steps 150 --seed -1 -G 0.75 ``` You'll need to experiment to see if face restoration is making it better or @@ -210,28 +210,28 @@ If you're on a Docker container, copy your input image into the Docker volume docker cp /Users//Pictures/sketch-mountains-input.jpg dummy:/data/ ``` -Try it out generating an image (or more). The `dream` script needs absolute +Try it out generating an image (or more). The `invoke` script needs absolute paths to find the image so don't use `~`. If you're on your Mac ```Shell -dream> "A fantasy landscape, trending on artstation" -I /Users//Pictures/sketch-mountains-input.jpg --strength 0.75 --steps 100 -n4 +invoke> "A fantasy landscape, trending on artstation" -I /Users//Pictures/sketch-mountains-input.jpg --strength 0.75 --steps 100 -n4 ``` If you're on a Linux container on your Mac ```Shell -dream> "A fantasy landscape, trending on artstation" -I /data/sketch-mountains-input.jpg --strength 0.75 --steps 50 -n1 +invoke> "A fantasy landscape, trending on artstation" -I /data/sketch-mountains-input.jpg --strength 0.75 --steps 50 -n1 ``` ## Web Interface -You can use the `dream` script with a graphical web interface. Start the web +You can use the `invoke` script with a graphical web interface. Start the web server with: ```Shell -python3 scripts/dream.py --full_precision --web +python3 scripts/invoke.py --full_precision --web ``` If it's running on your Mac point your Mac web browser to http://127.0.0.1:9090 diff --git a/docs/installation/INSTALL_LINUX.md b/docs/installation/INSTALL_LINUX.md index 88f327c734..56c2f91246 100644 --- a/docs/installation/INSTALL_LINUX.md +++ b/docs/installation/INSTALL_LINUX.md @@ -89,16 +89,16 @@ This will create InvokeAI folder where you will follow the rest of the steps. ``` # for the pre-release weights use the -l or --liaon400m switch -(ldm) ~/InvokeAI$ python3 scripts/dream.py -l +(ldm) ~/InvokeAI$ python3 scripts/invoke.py -l # for the post-release weights do not use the switch -(ldm) ~/InvokeAI$ python3 scripts/dream.py +(ldm) ~/InvokeAI$ python3 scripts/invoke.py # for additional configuration switches and arguments, use -h or --help -(ldm) ~/InvokeAI$ python3 scripts/dream.py -h +(ldm) ~/InvokeAI$ python3 scripts/invoke.py -h ``` -9. Subsequently, to relaunch the script, be sure to run "conda activate ldm" (step 5, second command), enter the `InvokeAI` directory, and then launch the dream script (step 8). If you forget to activate the ldm environment, the script will fail with multiple `ModuleNotFound` errors. +9. Subsequently, to relaunch the script, be sure to run "conda activate ldm" (step 5, second command), enter the `InvokeAI` directory, and then launch the invoke script (step 8). If you forget to activate the ldm environment, the script will fail with multiple `ModuleNotFound` errors. ## Updating to newer versions of the script diff --git a/docs/installation/INSTALL_MAC.md b/docs/installation/INSTALL_MAC.md index 972943f674..60ab3dc40d 100644 --- a/docs/installation/INSTALL_MAC.md +++ b/docs/installation/INSTALL_MAC.md @@ -2,145 +2,113 @@ title: macOS --- -# :fontawesome-brands-apple: macOS +Invoke AI runs quite well on M1 Macs and we have a number of M1 users +in the community. + +While the repo does run on Intel Macs, we only have a couple +reports. If you have an Intel Mac and run into issues, please create +an issue on Github and we will do our best to help. ## Requirements - macOS 12.3 Monterey or later -- Python -- Patience -- Apple Silicon or Intel Mac +- About 10GB of storage (and 10GB of data if your internet connection has data caps) +- Any M1 Macs or an Intel Macs with 4GB+ of VRAM (ideally more) -Things have moved really fast and so these instructions change often which makes -them outdated pretty fast. One of the problems is that there are so many -different ways to run this. +## Installation -We are trying to build a testing setup so that when we make changes it doesn't -always break. +First you need to download a large checkpoint file. -## How to +1. Sign up at https://huggingface.co +2. Go to the [Stable diffusion diffusion model page](https://huggingface.co/CompVis/stable-diffusion-v-1-4-original) +3. Accept the terms and click Access Repository +4. Download [sd-v1-4.ckpt (4.27 GB)](https://huggingface.co/CompVis/stable-diffusion-v-1-4-original/blob/main/sd-v1-4.ckpt) and note where you have saved it (probably the Downloads folder). You may want to move it somewhere else for longer term storage - SD needs this file to run. -(this hasn't been 100% tested yet) +While that is downloading, open Terminal and run the following +commands one at a time, reading the comments and taking care to run +the appropriate command for your Mac's architecture (Intel or M1). -First get the weights checkpoint download started since it's big and will take -some time: +Do not just copy and paste the whole thing into your terminal! -1. Sign up at [huggingface.co](https://huggingface.co) -2. Go to the - [Stable diffusion diffusion model page](https://huggingface.co/CompVis/stable-diffusion-v-1-4-original) -3. Accept the terms and click Access Repository: -4. Download - [sd-v1-4.ckpt (4.27 GB)](https://huggingface.co/CompVis/stable-diffusion-v-1-4-original/blob/main/sd-v1-4.ckpt) - and note where you have saved it (probably the Downloads folder) +```bash +# Install brew (and Xcode command line tools): +/bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)" -While that is downloading, open a Terminal and run the following commands: +# Now there are two options to get the Python (miniconda) environment up and running: +# 1. Alongside pyenv +# 2. Standalone +# +# If you don't know what we are talking about, choose 2. +# +# If you are familiar with python environments, you'll know there are other options +# for setting up the environment - you are on your own if you go one of those routes. +##### BEGIN TWO DIFFERENT OPTIONS ##### -!!! todo "Homebrew" +### BEGIN OPTION 1: Installing alongside pyenv ### +brew install pyenv-virtualenv # you might have this from before, no problem +pyenv install anaconda3-2022.05 +pyenv virtualenv anaconda3-2022.05 +eval "$(pyenv init -)" +pyenv activate anaconda3-2022.05 +### END OPTION 1 ### - === "no brew installation yet" - ```bash title="install brew (and Xcode command line tools)" - /bin/bash -c \ - "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)" - ``` +### BEGIN OPTION 2: Installing standalone ### +# Install cmake, protobuf, and rust: +brew install cmake protobuf rust - === "brew is already installed" - - Only if you installed protobuf in a previous version of this tutorial, otherwise skip +# BEGIN ARCHITECTURE-DEPENDENT STEP # +# For M1: install miniconda (M1 arm64 version): +curl https://repo.anaconda.com/miniconda/Miniconda3-latest-MacOSX-arm64.sh -o Miniconda3-latest-MacOSX-arm64.sh +/bin/bash Miniconda3-latest-MacOSX-arm64.sh - `#!bash brew uninstall protobuf` +# For Intel: install miniconda (Intel x86-64 version): +curl https://repo.anaconda.com/miniconda/Miniconda3-latest-MacOSX-x86_64.sh -o Miniconda3-latest-MacOSX-x86_64.sh +/bin/bash Miniconda3-latest-MacOSX-x86_64.sh +# END ARCHITECTURE-DEPENDENT STEP # -!!! todo "Conda Installation" +### END OPTION 2 ### - Now there are two different ways to set up the Python (miniconda) environment: - 1. Standalone - 2. with pyenv - If you don't know what we are talking about, choose Standalone +##### END TWO DIFFERENT OPTIONS ##### - === "Standalone" - - ```bash - # install cmake and rust: - brew install cmake rust - ``` - - === "M1 arm64" - - ```bash title="Install miniconda for M1 arm64" - curl https://repo.anaconda.com/miniconda/Miniconda3-latest-MacOSX-arm64.sh \ - -o Miniconda3-latest-MacOSX-arm64.sh - /bin/bash Miniconda3-latest-MacOSX-arm64.sh - ``` - - === "Intel x86_64" - - ```bash title="Install miniconda for Intel" - curl https://repo.anaconda.com/miniconda/Miniconda3-latest-MacOSX-x86_64.sh \ - -o Miniconda3-latest-MacOSX-x86_64.sh - /bin/bash Miniconda3-latest-MacOSX-x86_64.sh - ``` - - === "with pyenv" - - ```{.bash .annotate} - brew install rust pyenv-virtualenv # (1)! - pyenv install anaconda3-2022.05 - pyenv virtualenv anaconda3-2022.05 - eval "$(pyenv init -)" - pyenv activate anaconda3-2022.05 - ``` - - 1. You might already have this installed, if that is the case just continue. - -```{.bash .annotate title="local repo setup"} -# clone the repo +# Clone the Invoke AI repo git clone https://github.com/invoke-ai/InvokeAI.git - cd InvokeAI +<<<<<<< HEAD -# wait until the checkpoint file has downloaded, then proceed +### WAIT FOR THE CHECKPOINT FILE TO DOWNLOAD, THEN PROCEED ### +# We will leave the big checkpoint wherever you stashed it for long-term storage, +# and make a link to it from the repo's folder. This allows you to use it for +# other repos, and if you need to delete Invoke AI, you won't have to download it again. -# create symlink to checkpoint +# Make the directory in the repo for the symlink mkdir -p models/ldm/stable-diffusion-v1/ -PATH_TO_CKPT="$HOME/Downloads" # (1)! +# This is the folder where you put the checkpoint file `sd-v1-4.ckpt` +PATH_TO_CKPT="$HOME/Downloads" -ln -s "$PATH_TO_CKPT/sd-v1-4.ckpt" \ - models/ldm/stable-diffusion-v1/model.ckpt -``` +# Create a link to the checkpoint +ln -s "$PATH_TO_CKPT/sd-v1-4.ckpt" models/ldm/stable-diffusion-v1/model.ckpt -1. or wherever you saved sd-v1-4.ckpt +# BEGIN ARCHITECTURE-DEPENDENT STEP # +# For M1: Create the environment & install packages +PIP_EXISTS_ACTION=w CONDA_SUBDIR=osx-arm64 conda env create -f environment-mac.yaml -!!! todo "create Conda Environment" +# For Intel: Create the environment & install packages +PIP_EXISTS_ACTION=w CONDA_SUBDIR=osx-64 conda env create -f environment-mac.yaml +# END ARCHITECTURE-DEPENDENT STEP # - === "M1 arm64" +# Activate the environment (you need to do this every time you want to run SD) +conda activate ldm - ```bash - PIP_EXISTS_ACTION=w CONDA_SUBDIR=osx-arm64 \ - conda env create \ - -f environment-mac.yml \ - && conda activate ldm - ``` - - - === "Intel x86_64" - - ```bash - PIP_EXISTS_ACTION=w CONDA_SUBDIR=osx-64 \ - conda env create \ - -f environment-mac.yml \ - && conda activate ldm - ``` - -```{.bash .annotate title="preload models and run script"} -# only need to do this once +# This will download some bits and pieces and make take a while python scripts/preload_models.py -# now you can run SD in CLI mode -python scripts/dream.py --full_precision # (1)! - +# Run SD! +python scripts/dream.py +``` # or run the web interface! -python scripts/dream.py --web +python scripts/invoke.py --web # The original scripts should work as well. python scripts/orig_scripts/txt2img.py \ @@ -155,7 +123,7 @@ it isn't required but wont hurt. ## Common problems -After you followed all the instructions and try to run dream.py, you might +After you followed all the instructions and try to run invoke.py, you might get several errors. Here's the errors I've seen and found solutions for. ### Is it slow? @@ -172,13 +140,13 @@ python ./scripts/orig_scripts/txt2img.py \ ### Doesn't work anymore? -PyTorch nightly includes support for MPS. Because of this, this setup is -inherently unstable. One morning I woke up and it no longer worked no matter -what I did until I switched to miniforge. However, I have another Mac that works -just fine with Anaconda. If you can't get it to work, please search a little -first because many of the errors will get posted and solved. If you can't find a -solution please -[create an issue](https://github.com/invoke-ai/InvokeAI/issues). +PyTorch nightly includes support for MPS. Because of this, this setup +is inherently unstable. One morning I woke up and it no longer worked +no matter what I did until I switched to miniforge. However, I have +another Mac that works just fine with Anaconda. If you can't get it to +work, please search a little first because many of the errors will get +posted and solved. If you can't find a solution please [create an +issue](https://github.com/invoke-ai/InvokeAI/issues). One debugging step is to update to the latest version of PyTorch nightly. @@ -220,9 +188,9 @@ There are several causes of these errors: "(ldm)" then you activated it. If it begins with "(base)" or something else you haven't. -2. You might've run `./scripts/preload_models.py` or `./scripts/dream.py` +2. You might've run `./scripts/preload_models.py` or `./scripts/invoke.py` instead of `python ./scripts/preload_models.py` or - `python ./scripts/dream.py`. The cause of this error is long so it's below. + `python ./scripts/invoke.py`. The cause of this error is long so it's below. @@ -378,8 +346,8 @@ python scripts/preload_models.py WARNING: this will be slower than running natively on MPS. ``` -This fork already includes a fix for this in -[environment-mac.yml](https://github.com/invoke-ai/InvokeAI/blob/main/environment-mac.yml). +The InvokeAI version includes this fix in +[environment-mac.yaml](https://github.com/invoke-ai/InvokeAI/blob/main/environment-mac.yaml). ### "Could not build wheels for tokenizers" @@ -463,13 +431,10 @@ C. You don't have a virus. It's part of the project. Here's [Rick](https://github.com/invoke-ai/InvokeAI/blob/main/assets/rick.jpeg) -and here's -[the code](https://github.com/invoke-ai/InvokeAI/blob/69ae4b35e0a0f6ee1af8bb9a5d0016ccb27e36dc/scripts/txt2img.py#L79) -that swaps him in. It's a NSFW filter, which IMO, doesn't work very good (and we -call this "computer vision", sheesh). - -Actually, this could be happening because there's not enough RAM. You could try -the `model.half()` suggestion or specify smaller output images. +and here's [the +code](https://github.com/invoke-ai/InvokeAI/blob/69ae4b35e0a0f6ee1af8bb9a5d0016ccb27e36dc/scripts/txt2img.py#L79) +that swaps him in. It's a NSFW filter, which IMO, doesn't work very +good (and we call this "computer vision", sheesh). --- @@ -492,11 +457,9 @@ return torch.layer_norm(input, normalized_shape, weight, bias, eps, torch.backen RuntimeError: view size is not compatible with input tensor's size and stride (at least one dimension spans across two contiguous subspaces). Use .reshape(...) instead. ``` -Update to the latest version of invoke-ai/InvokeAI. We were patching -pytorch but we found a file in stable-diffusion that we could change instead. -This is a 32-bit vs 16-bit problem. - ---- +Update to the latest version of invoke-ai/InvokeAI. We were +patching pytorch but we found a file in stable-diffusion that we could +change instead. This is a 32-bit vs 16-bit problem. ### The processor must support the Intel bla bla bla @@ -519,7 +482,7 @@ use ARM packages, and use `nomkl` as described above. May appear when just starting to generate, e.g.: ```bash -dream> clouds +invoke> clouds Generating: 0%| | 0/1 [00:00' and 'tensor<*xf16>' are not broadcast compatible diff --git a/docs/installation/INSTALL_WINDOWS.md b/docs/installation/INSTALL_WINDOWS.md index eabf3e2ae2..a74275fd62 100644 --- a/docs/installation/INSTALL_WINDOWS.md +++ b/docs/installation/INSTALL_WINDOWS.md @@ -101,13 +101,13 @@ you may instead create a shortcut to it from within `models\ldm\stable-diffusion ```bash # for the pre-release weights - python scripts\dream.py -l + python scripts\invoke.py -l # for the post-release weights - python scripts\dream.py + python scripts\invoke.py ``` -10. Subsequently, to relaunch the script, first activate the Anaconda command window (step 3),enter the InvokeAI directory (step 5, `cd \path\to\InvokeAI`), run `conda activate ldm` (step 6b), and then launch the dream script (step 9). +10. Subsequently, to relaunch the script, first activate the Anaconda command window (step 3),enter the InvokeAI directory (step 5, `cd \path\to\InvokeAI`), run `conda activate ldm` (step 6b), and then launch the invoke script (step 9). **Note:** Tildebyte has written an alternative ["Easy peasy Windows install"](https://github.com/invoke-ai/InvokeAI/wiki/Easy-peasy-Windows-install) diff --git a/environment-mac.yml b/environment-mac.yml index 70df3b8865..ff0ff37d32 100644 --- a/environment-mac.yml +++ b/environment-mac.yml @@ -3,12 +3,12 @@ channels: - pytorch - conda-forge dependencies: - - python==3.10.5 + - python==3.9.13 - pip==22.2.2 - + # pytorch left unpinned - - pytorch - - torchvision + - pytorch==1.12.1 + - torchvision==0.13.1 # I suggest to keep the other deps sorted for convenience. # To determine what the latest versions should be, run: @@ -27,13 +27,12 @@ dependencies: - imgaug==0.4.0 - kornia==0.6.7 - mpmath==1.2.1 - - nomkl + - nomkl=1.0 - numpy==1.23.2 - omegaconf==2.1.1 - openh264==2.3.0 - onnx==1.12.0 - onnxruntime==1.12.1 - - protobuf==3.19.4 - pudb==2022.1 - pytorch-lightning==1.7.5 - scipy==1.9.1 @@ -42,22 +41,22 @@ dependencies: - tensorboard==2.10.0 - torchmetrics==0.9.3 - pip: - - flask==2.1.3 - - flask_socketio==5.3.0 - - flask_cors==3.0.10 - - dependency_injector==4.40.0 - - eventlet - - opencv-python==4.6.0 - - protobuf==3.20.1 - - realesrgan==0.2.5.0 - - send2trash==1.8.0 - - test-tube==0.7.5 - - transformers==4.21.2 - - torch-fidelity==0.3.0 - - -e git+https://github.com/CompVis/taming-transformers.git@master#egg=taming-transformers - - -e git+https://github.com/openai/CLIP.git@main#egg=clip - - -e git+https://github.com/Birch-san/k-diffusion.git@mps#egg=k_diffusion - - -e git+https://github.com/lstein/GFPGAN@fix-dark-cast-images#egg=gfpgan - - -e . + - flask==2.1.3 + - flask_socketio==5.3.0 + - flask_cors==3.0.10 + - dependency_injector==4.40.0 + - eventlet==0.33.1 + - opencv-python==4.6.0 + - protobuf==3.19.5 + - realesrgan==0.2.5.0 + - send2trash==1.8.0 + - test-tube==0.7.5 + - transformers==4.21.2 + - torch-fidelity==0.3.0 + - -e git+https://github.com/CompVis/taming-transformers.git@master#egg=taming-transformers + - -e git+https://github.com/openai/CLIP.git@main#egg=clip + - -e git+https://github.com/Birch-san/k-diffusion.git@mps#egg=k_diffusion + - -e git+https://github.com/TencentARC/GFPGAN.git#egg=gfpgan + - -e . variables: PYTORCH_ENABLE_MPS_FALLBACK: 1 diff --git a/environment.yml b/environment.yml index 621ec024b0..cafd7c64d2 100644 --- a/environment.yml +++ b/environment.yml @@ -36,5 +36,5 @@ dependencies: - -e git+https://github.com/openai/CLIP.git@main#egg=clip - -e git+https://github.com/CompVis/taming-transformers.git@master#egg=taming-transformers - -e git+https://github.com/Birch-san/k-diffusion.git@mps#egg=k_diffusion - - -e git+https://github.com/lstein/GFPGAN@fix-dark-cast-images#egg=gfpgan + - -e git+https://github.com/TencentARC/GFPGAN.git#egg=gfpgan - -e . diff --git 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0?k:h.getDefaultTransition())!==null&&S!==void 0?S:Lq,{onLayoutAnimationStart:R,onLayoutAnimationComplete:N}=h.getProps(),z=!this.targetLayout||!FL(this.targetLayout,x)||b,K=!g&&b;if(((w=this.resumeFrom)===null||w===void 0?void 0:w.instance)||K||g&&(z||!this.currentAnimation)){this.resumeFrom&&(this.resumingFrom=this.resumeFrom,this.resumingFrom.resumingFrom=void 0),this.setAnimationOrigin(m,K);const W={...W3(T,"layout"),onPlay:R,onComplete:N};h.shouldReduceMotion&&(W.delay=0,W.type=!1),this.startAnimation(W)}else!g&&this.animationProgress===0&&this.finishAnimation(),this.isLead()&&((L=(_=this.options).onExitComplete)===null||L===void 0||L.call(_));this.targetLayout=x})}unmount(){var s,u;this.options.layoutId&&this.willUpdate(),this.root.nodes.remove(this),(s=this.getStack())===null||s===void 0||s.remove(this),(u=this.parent)===null||u===void 0||u.children.delete(this),this.instance=void 0,Uf.preRender(this.updateProjection)}blockUpdate(){this.updateManuallyBlocked=!0}unblockUpdate(){this.updateManuallyBlocked=!1}isUpdateBlocked(){return this.updateManuallyBlocked||this.updateBlockedByResize}isTreeAnimationBlocked(){var s;return this.isAnimationBlocked||((s=this.parent)===null||s===void 0?void 0:s.isTreeAnimationBlocked())||!1}startUpdate(){var s;this.isUpdateBlocked()||(this.isUpdating=!0,(s=this.nodes)===null||s===void 0||s.forEach(Cq))}willUpdate(s=!0){var u,c,f;if(this.root.isUpdateBlocked()){(c=(u=this.options).onExitComplete)===null||c===void 0||c.call(u);return}if(!this.root.isUpdating&&this.root.startUpdate(),this.isLayoutDirty)return;this.isLayoutDirty=!0;for(let g=0;g{this.isLayoutDirty?this.root.didUpdate():this.root.checkUpdateFailed()})}updateSnapshot(){if(this.snapshot||!this.instance)return;const s=this.measure(),u=this.removeTransform(this.removeElementScroll(s));QS(u),this.snapshot={measured:s,layout:u,latestValues:{}}}updateLayout(){var s;if(!this.instance||(this.updateScroll(),!(this.options.alwaysMeasureLayout&&this.isLead())&&!this.isLayoutDirty))return;if(this.resumeFrom&&!this.resumeFrom.instance)for(let f=0;f{var w;const _=S/1e3;qS(m.x,s.x,_),qS(m.y,s.y,_),this.setTargetDelta(m),this.relativeTarget&&this.relativeTargetOrigin&&this.layout&&((w=this.relativeParent)===null||w===void 0?void 0:w.layout)&&(sf(g,this.layout.actual,this.relativeParent.layout.actual),kq(this.relativeTarget,this.relativeTargetOrigin,g,_)),b&&(this.animationValues=h,iq(h,d,this.latestValues,_,k,x)),this.root.scheduleUpdateProjection(),this.scheduleRender(),this.animationProgress=_},this.mixTargetDelta(0)}startAnimation(s){var u,c;this.notifyListeners("animationStart"),(u=this.currentAnimation)===null||u===void 0||u.stop(),this.resumingFrom&&((c=this.resumingFrom.currentAnimation)===null||c===void 0||c.stop()),this.pendingAnimation&&(Uf.update(this.pendingAnimation),this.pendingAnimation=void 0),this.pendingAnimation=ui.update(()=>{tf.hasAnimatedSinceResize=!0,this.currentAnimation=rq(0,ZS,{...s,onUpdate:f=>{var d;this.mixTargetDelta(f),(d=s.onUpdate)===null||d===void 0||d.call(s,f)},onComplete:()=>{var f;(f=s.onComplete)===null||f===void 0||f.call(s),this.completeAnimation()}}),this.resumingFrom&&(this.resumingFrom.currentAnimation=this.currentAnimation),this.pendingAnimation=void 0})}completeAnimation(){var s;this.resumingFrom&&(this.resumingFrom.currentAnimation=void 0,this.resumingFrom.preserveOpacity=void 0),(s=this.getStack())===null||s===void 0||s.exitAnimationComplete(),this.resumingFrom=this.currentAnimation=this.animationValues=void 0,this.notifyListeners("animationComplete")}finishAnimation(){var s;this.currentAnimation&&((s=this.mixTargetDelta)===null||s===void 0||s.call(this,ZS),this.currentAnimation.stop()),this.completeAnimation()}applyTransformsToTarget(){const s=this.getLead();let{targetWithTransforms:u,target:c,layout:f,latestValues:d}=s;if(!(!u||!c||!f)){if(this!==s&&this.layout&&f&&$L(this.options.animationType,this.layout.actual,f.actual)){c=this.target||In();const h=jr(this.layout.actual.x);c.x.min=s.target.x.min,c.x.max=c.x.min+h;const m=jr(this.layout.actual.y);c.y.min=s.target.y.min,c.y.max=c.y.min+m}Lo(u,c),Zl(u,d),af(this.projectionDeltaWithTransform,this.layoutCorrected,u,d)}}registerSharedNode(s,u){var c,f,d;this.sharedNodes.has(s)||this.sharedNodes.set(s,new dq),this.sharedNodes.get(s).add(u),u.promote({transition:(c=u.options.initialPromotionConfig)===null||c===void 0?void 0:c.transition,preserveFollowOpacity:(d=(f=u.options.initialPromotionConfig)===null||f===void 0?void 0:f.shouldPreserveFollowOpacity)===null||d===void 0?void 0:d.call(f,u)})}isLead(){const s=this.getStack();return s?s.lead===this:!0}getLead(){var s;const{layoutId:u}=this.options;return u?((s=this.getStack())===null||s===void 0?void 0:s.lead)||this:this}getPrevLead(){var s;const{layoutId:u}=this.options;return u?(s=this.getStack())===null||s===void 0?void 0:s.prevLead:void 0}getStack(){const{layoutId:s}=this.options;if(s)return this.root.sharedNodes.get(s)}promote({needsReset:s,transition:u,preserveFollowOpacity:c}={}){const f=this.getStack();f&&f.promote(this,c),s&&(this.projectionDelta=void 0,this.needsReset=!0),u&&this.setOptions({transition:u})}relegate(){const s=this.getStack();return s?s.relegate(this):!1}resetRotation(){const{visualElement:s}=this.options;if(!s)return;let u=!1;const c={};for(let f=0;f{var u;return(u=s.currentAnimation)===null||u===void 0?void 0:u.stop()}),this.root.nodes.forEach(KS),this.root.sharedNodes.clear()}}}function gq(e){e.updateLayout()}function vq(e){var t,n,r;const o=((t=e.resumeFrom)===null||t===void 0?void 0:t.snapshot)||e.snapshot;if(e.isLead()&&e.layout&&o&&e.hasListeners("didUpdate")){const{actual:i,measured:s}=e.layout,{animationType:u}=e.options;u==="size"?Yo(m=>{const g=o.isShared?o.measured[m]:o.layout[m],b=jr(g);g.min=i[m].min,g.max=g.min+b}):$L(u,o.layout,i)&&Yo(m=>{const g=o.isShared?o.measured[m]:o.layout[m],b=jr(i[m]);g.max=g.min+b});const c=lf();af(c,i,o.layout);const f=lf();o.isShared?af(f,e.applyTransform(s,!0),o.measured):af(f,i,o.layout);const d=!zL(c);let h=!1;if(!e.resumeFrom&&(e.relativeParent=e.getClosestProjectingParent(),e.relativeParent&&!e.relativeParent.resumeFrom)){const{snapshot:m,layout:g}=e.relativeParent;if(m&&g){const b=In();sf(b,o.layout,m.layout);const x=In();sf(x,i,g.actual),FL(b,x)||(h=!0)}}e.notifyListeners("didUpdate",{layout:i,snapshot:o,delta:f,layoutDelta:c,hasLayoutChanged:d,hasRelativeTargetChanged:h})}else e.isLead()&&((r=(n=e.options).onExitComplete)===null||r===void 0||r.call(n));e.options.transition=void 0}function yq(e){e.clearSnapshot()}function KS(e){e.clearMeasurements()}function bq(e){const{visualElement:t}=e.options;t?.getProps().onBeforeLayoutMeasure&&t.notifyBeforeLayoutMeasure(),e.resetTransform()}function xq(e){e.finishAnimation(),e.targetDelta=e.relativeTarget=e.target=void 0}function wq(e){e.resolveTargetDelta()}function Sq(e){e.calcProjection()}function Cq(e){e.resetRotation()}function _q(e){e.removeLeadSnapshot()}function qS(e,t,n){e.translate=Yt(t.translate,0,n),e.scale=Yt(t.scale,1,n),e.origin=t.origin,e.originPoint=t.originPoint}function YS(e,t,n,r){e.min=Yt(t.min,n.min,r),e.max=Yt(t.max,n.max,r)}function kq(e,t,n,r){YS(e.x,t.x,n.x,r),YS(e.y,t.y,n.y,r)}function Eq(e){return e.animationValues&&e.animationValues.opacityExit!==void 0}const Lq={duration:.45,ease:[.4,0,.1,1]};function Pq(e,t){let n=e.root;for(let i=e.path.length-1;i>=0;i--)if(Boolean(e.path[i].instance)){n=e.path[i];break}const o=(n&&n!==e.root?n.instance:document).querySelector(`[data-projection-id="${t}"]`);o&&e.mount(o,!0)}function XS(e){e.min=Math.round(e.min),e.max=Math.round(e.max)}function QS(e){XS(e.x),XS(e.y)}function $L(e,t,n){return e==="position"||e==="preserve-aspect"&&!fq(HS(t),HS(n))}const Aq=BL({attachResizeListener:(e,t)=>sm(e,"resize",t),measureScroll:()=>({x:document.documentElement.scrollLeft||document.body.scrollLeft,y:document.documentElement.scrollTop||document.body.scrollTop}),checkIsScrollRoot:()=>!0}),l2={current:void 0},Tq=BL({measureScroll:e=>({x:e.scrollLeft,y:e.scrollTop}),defaultParent:()=>{if(!l2.current){const e=new Aq(0,{});e.mount(window),e.setOptions({layoutScroll:!0}),l2.current=e}return l2.current},resetTransform:(e,t)=>{e.style.transform=t!==void 0?t:"none"},checkIsScrollRoot:e=>Boolean(window.getComputedStyle(e).position==="fixed")}),Iq={...cK,...xZ,...IK,...nq},go=uU((e,t)=>KU(e,t,Iq,XK,Tq));function VL(){const e=C.exports.useRef(!1);return H1(()=>(e.current=!0,()=>{e.current=!1}),[]),e}function Oq(){const e=VL(),[t,n]=C.exports.useState(0),r=C.exports.useCallback(()=>{e.current&&n(t+1)},[t]);return[C.exports.useCallback(()=>ui.postRender(r),[r]),t]}class Mq extends C.exports.Component{getSnapshotBeforeUpdate(t){const n=this.props.childRef.current;if(n&&t.isPresent&&!this.props.isPresent){const r=this.props.sizeRef.current;r.height=n.offsetHeight||0,r.width=n.offsetWidth||0,r.top=n.offsetTop,r.left=n.offsetLeft}return null}componentDidUpdate(){}render(){return this.props.children}}function Rq({children:e,isPresent:t}){const n=C.exports.useId(),r=C.exports.useRef(null),o=C.exports.useRef({width:0,height:0,top:0,left:0});return C.exports.useInsertionEffect(()=>{const{width:i,height:s,top:u,left:c}=o.current;if(t||!r.current||!i||!s)return;r.current.dataset.motionPopId=n;const f=document.createElement("style");return document.head.appendChild(f),f.sheet&&f.sheet.insertRule(` + [data-motion-pop-id="${n}"] { + position: absolute !important; + width: ${i}px !important; + height: ${s}px !important; + top: ${u}px !important; + left: ${c}px !important; + } + `),()=>{document.head.removeChild(f)}},[t]),v(Mq,{isPresent:t,childRef:r,sizeRef:o,children:C.exports.cloneElement(e,{ref:r})})}const u2=({children:e,initial:t,isPresent:n,onExitComplete:r,custom:o,presenceAffectsLayout:i,mode:s})=>{const u=am(Nq),c=C.exports.useId(),f=C.exports.useMemo(()=>({id:c,initial:t,isPresent:n,custom:o,onExitComplete:d=>{u.set(d,!0);for(const h of u.values())if(!h)return;r&&r()},register:d=>(u.set(d,!1),()=>u.delete(d))}),i?void 0:[n]);return C.exports.useMemo(()=>{u.forEach((d,h)=>u.set(h,!1))},[n]),C.exports.useEffect(()=>{!n&&!u.size&&r&&r()},[n]),s==="popLayout"&&(e=v(Rq,{isPresent:n,children:e})),v(Nu.Provider,{value:f,children:e})};function Nq(){return new Map}const Tl=e=>e.key||"";function Dq(e,t){e.forEach(n=>{const r=Tl(n);t.set(r,n)})}function zq(e){const t=[];return C.exports.Children.forEach(e,n=>{C.exports.isValidElement(n)&&t.push(n)}),t}const na=({children:e,custom:t,initial:n=!0,onExitComplete:r,exitBeforeEnter:o,presenceAffectsLayout:i=!0,mode:s="sync"})=>{o&&(s="wait",pL(!1,"Replace exitBeforeEnter with mode='wait'"));let[u]=Oq();const c=C.exports.useContext(C3).forceRender;c&&(u=c);const f=VL(),d=zq(e);let h=d;const m=new Set,g=C.exports.useRef(h),b=C.exports.useRef(new Map).current,x=C.exports.useRef(!0);if(H1(()=>{x.current=!1,Dq(d,b),g.current=h}),I3(()=>{x.current=!0,b.clear(),m.clear()}),x.current)return v(yn,{children:h.map(_=>v(u2,{isPresent:!0,initial:n?void 0:!1,presenceAffectsLayout:i,mode:s,children:_},Tl(_)))});h=[...h];const k=g.current.map(Tl),S=d.map(Tl),w=k.length;for(let _=0;_{if(S.indexOf(_)!==-1)return;const L=b.get(_);if(!L)return;const T=k.indexOf(_),R=()=>{b.delete(_),m.delete(_);const N=g.current.findIndex(z=>z.key===_);if(g.current.splice(N,1),!m.size){if(g.current=d,f.current===!1)return;u(),r&&r()}};h.splice(T,0,v(u2,{isPresent:!1,onExitComplete:R,custom:t,presenceAffectsLayout:i,mode:s,children:L},Tl(L)))}),h=h.map(_=>{const L=_.key;return m.has(L)?_:v(u2,{isPresent:!0,presenceAffectsLayout:i,mode:s,children:_},Tl(_))}),dL!=="production"&&s==="wait"&&h.length>1&&console.warn(`You're attempting to animate multiple children within AnimatePresence, but its mode is set to "wait". 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Wq={enter:({transition:e,transitionEnd:t,delay:n}={})=>({opacity:1,transition:e?.enter??Fo.enter(Is.enter,n),transitionEnd:t?.enter}),exit:({transition:e,transitionEnd:t,delay:n}={})=>({opacity:0,transition:e?.exit??Fo.exit(Is.exit,n),transitionEnd:t?.exit})},jL={initial:"exit",animate:"enter",exit:"exit",variants:Wq},jq=C.exports.forwardRef(function(t,n){const{unmountOnExit:r,in:o,className:i,transition:s,transitionEnd:u,delay:c,...f}=t,d=o||r?"enter":"exit",h=r?o&&r:!0,m={transition:s,transitionEnd:u,delay:c};return v(na,{custom:m,children:h&&X.createElement(go.div,{ref:n,className:xd("chakra-fade",i),custom:m,...jL,animate:d,...f})})});jq.displayName="Fade";var Hq={exit:({reverse:e,initialScale:t,transition:n,transitionEnd:r,delay:o})=>({opacity:0,...e?{scale:t,transitionEnd:r?.exit}:{transitionEnd:{scale:t,...r?.exit}},transition:n?.exit??Fo.exit(Is.exit,o)}),enter:({transitionEnd:e,transition:t,delay:n})=>({opacity:1,scale:1,transition:t?.enter??Fo.enter(Is.enter,n),transitionEnd:e?.enter})},HL={initial:"exit",animate:"enter",exit:"exit",variants:Hq},Uq=C.exports.forwardRef(function(t,n){const{unmountOnExit:r,in:o,reverse:i=!0,initialScale:s=.95,className:u,transition:c,transitionEnd:f,delay:d,...h}=t,m=r?o&&r:!0,g=o||r?"enter":"exit",b={initialScale:s,reverse:i,transition:c,transitionEnd:f,delay:d};return v(na,{custom:b,children:m&&X.createElement(go.div,{ref:n,className:xd("chakra-offset-slide",u),...HL,animate:g,custom:b,...h})})});Uq.displayName="ScaleFade";var 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solid",borderColor:"inherit",my:"2",opacity:.6},aae={transitionProperty:"common",transitionDuration:"normal"},sae=eae(e=>({button:aae,list:on(tae,e),item:on(nae,e),groupTitle:rae,command:oae,divider:iae})),lae=Jie({baseStyle:sae}),{defineMultiStyleConfig:uae,definePartsStyle:z4}=Bt(Qne.keys),cae={bg:"blackAlpha.600",zIndex:"modal"},fae=e=>{const{isCentered:t,scrollBehavior:n}=e;return{display:"flex",zIndex:"modal",justifyContent:"center",alignItems:t?"center":"flex-start",overflow:n==="inside"?"hidden":"auto"}},dae=e=>{const{scrollBehavior:t}=e;return{borderRadius:"md",bg:re("white","gray.700")(e),color:"inherit",my:"16",zIndex:"modal",maxH:t==="inside"?"calc(100% - 7.5rem)":void 0,boxShadow:re("lg","dark-lg")(e)}},pae={px:"6",py:"4",fontSize:"xl",fontWeight:"semibold"},hae={position:"absolute",top:"2",insetEnd:"3"},mae=e=>{const{scrollBehavior:t}=e;return{px:"6",py:"2",flex:"1",overflow:t==="inside"?"auto":void 0}},gae={px:"6",py:"4"},vae=z4(e=>({overlay:cae,dialogContainer:on(fae,e),dialog:on(dae,e),header:pae,closeButton:hae,body:on(mae,e),footer:gae}));function Po(e){return z4(e==="full"?{dialog:{maxW:"100vw",minH:"$100vh",my:"0",borderRadius:"0"}}:{dialog:{maxW:e}})}var yae={xs:Po("xs"),sm:Po("sm"),md:Po("md"),lg:Po("lg"),xl:Po("xl"),"2xl":Po("2xl"),"3xl":Po("3xl"),"4xl":Po("4xl"),"5xl":Po("5xl"),"6xl":Po("6xl"),full:Po("full")},bae=uae({baseStyle:vae,sizes:yae,defaultProps:{size:"md"}}),xae={letterSpacings:{tighter:"-0.05em",tight:"-0.025em",normal:"0",wide:"0.025em",wider:"0.05em",widest:"0.1em"},lineHeights:{normal:"normal",none:1,shorter:1.25,short:1.375,base:1.5,tall:1.625,taller:"2",3:".75rem",4:"1rem",5:"1.25rem",6:"1.5rem",7:"1.75rem",8:"2rem",9:"2.25rem",10:"2.5rem"},fontWeights:{hairline:100,thin:200,light:300,normal:400,medium:500,semibold:600,bold:700,extrabold:800,black:900},fonts:{heading:'-apple-system, BlinkMacSystemFont, "Segoe UI", Helvetica, Arial, sans-serif, "Apple 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0:G8.field,textAlign:"center"},Iae={lg:{fontSize:"lg",w:12,h:12,borderRadius:"md"},md:{fontSize:"md",w:10,h:10,borderRadius:"md"},sm:{fontSize:"sm",w:8,h:8,borderRadius:"sm"},xs:{fontSize:"xs",w:6,h:6,borderRadius:"sm"}},Z8,Oae={outline:e=>{var t,n;return((n=on((t=at.variants)==null?void 0:t.outline,e))==null?void 0:n.field)??{}},flushed:e=>{var t,n;return((n=on((t=at.variants)==null?void 0:t.flushed,e))==null?void 0:n.field)??{}},filled:e=>{var t,n;return((n=on((t=at.variants)==null?void 0:t.filled,e))==null?void 0:n.field)??{}},unstyled:((Z8=at.variants)==null?void 0:Z8.unstyled.field)??{}},Mae={baseStyle:Tae,sizes:Iae,variants:Oae,defaultProps:at.defaultProps},{defineMultiStyleConfig:Rae,definePartsStyle:Nae}=Bt(ere.keys),E2=Er("popper-bg"),Dae=Er("popper-arrow-bg"),zae=Er("popper-arrow-shadow-color"),Fae={zIndex:10},Bae=e=>{const t=re("white","gray.700")(e),n=re("gray.200","whiteAlpha.300")(e);return{[E2.variable]:`colors.${t}`,bg:E2.reference,[Dae.variable]:E2.reference,[zae.variable]:`colors.${n}`,width:"xs",border:"1px solid",borderColor:"inherit",borderRadius:"md",boxShadow:"sm",zIndex:"inherit",_focusVisible:{outline:0,boxShadow:"outline"}}},$ae={px:3,py:2,borderBottomWidth:"1px"},Vae={px:3,py:2},Wae={px:3,py:2,borderTopWidth:"1px"},jae={position:"absolute",borderRadius:"md",top:1,insetEnd:2,padding:2},Hae=Nae(e=>({popper:Fae,content:Bae(e),header:$ae,body:Vae,footer:Wae,closeButton:jae})),Uae=Rae({baseStyle:Hae}),{defineMultiStyleConfig:Gae,definePartsStyle:Wc}=Bt(tre.keys),Zae=e=>{const{colorScheme:t,theme:n,isIndeterminate:r,hasStripe:o}=e,i=re(V8(),V8("1rem","rgba(0,0,0,0.1)"))(e),s=re(`${t}.500`,`${t}.200`)(e),u=`linear-gradient( + to right, + transparent 0%, + ${vn(n,s)} 50%, + transparent 100% + )`;return{...!r&&o&&i,...r?{bgImage:u}:{bgColor:s}}},Kae={lineHeight:"1",fontSize:"0.25em",fontWeight:"bold",color:"white"},qae=e=>({bg:re("gray.100","whiteAlpha.300")(e)}),Yae=e=>({transitionProperty:"common",transitionDuration:"slow",...Zae(e)}),Xae=Wc(e=>({label:Kae,filledTrack:Yae(e),track:qae(e)})),Qae={xs:Wc({track:{h:"1"}}),sm:Wc({track:{h:"2"}}),md:Wc({track:{h:"3"}}),lg:Wc({track:{h:"4"}})},Jae=Gae({sizes:Qae,baseStyle:Xae,defaultProps:{size:"md",colorScheme:"blue"}}),{defineMultiStyleConfig:ese,definePartsStyle:o1}=Bt(nre.keys),tse=e=>{var t;const n=(t=on(c0.baseStyle,e))==null?void 0:t.control;return{...n,borderRadius:"full",_checked:{...n?._checked,_before:{content:'""',display:"inline-block",pos:"relative",w:"50%",h:"50%",borderRadius:"50%",bg:"currentColor"}}}},nse=o1(e=>{var t,n,r,o;return{label:(n=(t=c0).baseStyle)==null?void 0:n.call(t,e).label,container:(o=(r=c0).baseStyle)==null?void 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0:X8.md.field,...Sh}},sm:{...(Q8=at.sizes)==null?void 0:Q8.sm,field:{...(J8=at.sizes)==null?void 0:J8.sm.field,...Sh}},xs:{...(e7=at.sizes)==null?void 0:e7.xs,field:{...(t7=at.sizes)==null?void 0:t7.sm.field,...Sh},icon:{insetEnd:"1"}}},fse=ise({baseStyle:use,sizes:cse,variants:at.variants,defaultProps:at.defaultProps}),dse=ns("skeleton-start-color"),pse=ns("skeleton-end-color"),hse=e=>{const t=re("gray.100","gray.800")(e),n=re("gray.400","gray.600")(e),{startColor:r=t,endColor:o=n,theme:i}=e,s=vn(i,r),u=vn(i,o);return{[dse.variable]:s,[pse.variable]:u,opacity:.7,borderRadius:"2px",borderColor:s,background:u}},mse={baseStyle:hse},gse=e=>({borderRadius:"md",fontWeight:"semibold",_focusVisible:{boxShadow:"outline",padding:"4",position:"fixed",top:"6",insetStart:"6",bg:re("white","gray.700")(e)}}),vse={baseStyle:gse},{defineMultiStyleConfig:yse,definePartsStyle:Am}=Bt(ore.keys),Qf=ns("slider-thumb-size"),Jf=ns("slider-track-size"),bse=e=>{const{orientation:t}=e;return{display:"inline-block",position:"relative",cursor:"pointer",_disabled:{opacity:.6,cursor:"default",pointerEvents:"none"},...Rb({orientation:t,vertical:{h:"100%"},horizontal:{w:"100%"}})}},xse=e=>({...Rb({orientation:e.orientation,horizontal:{h:Jf.reference},vertical:{w:Jf.reference}}),overflow:"hidden",borderRadius:"sm",bg:re("gray.200","whiteAlpha.200")(e),_disabled:{bg:re("gray.300","whiteAlpha.300")(e)}}),wse=e=>{const{orientation:t}=e;return{...Rb({orientation:t,vertical:{left:"50%",transform:"translateX(-50%)",_active:{transform:"translateX(-50%) 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td":{borderBottomWidth:"1px",borderColor:re(`${t}.100`,`${t}.700`)(e)},td:{background:re(`${t}.100`,`${t}.700`)(e)}}}},tfoot:{tr:{"&:last-of-type":{th:{borderBottomWidth:0}}}}}}),Xse={simple:qse,striped:Yse,unstyled:{}},Qse={sm:lu({th:{px:"4",py:"1",lineHeight:"4",fontSize:"xs"},td:{px:"4",py:"2",fontSize:"sm",lineHeight:"4"},caption:{px:"4",py:"2",fontSize:"xs"}}),md:lu({th:{px:"6",py:"3",lineHeight:"4",fontSize:"xs"},td:{px:"6",py:"4",lineHeight:"5"},caption:{px:"6",py:"2",fontSize:"sm"}}),lg:lu({th:{px:"8",py:"4",lineHeight:"5",fontSize:"sm"},td:{px:"8",py:"5",lineHeight:"6"},caption:{px:"6",py:"2",fontSize:"md"}})},Jse=Zse({baseStyle:Kse,variants:Xse,sizes:Qse,defaultProps:{variant:"simple",size:"md",colorScheme:"gray"}}),{defineMultiStyleConfig:ele,definePartsStyle:fi}=Bt(lre.keys),tle=e=>{const{orientation:t}=e;return{display:t==="vertical"?"flex":"block"}},nle=e=>{const{isFitted:t}=e;return{flex:t?1:void 0,transitionProperty:"common",transitionDuration:"normal",_focusVisible:{zIndex:1,boxShadow:"outline"},_disabled:{cursor:"not-allowed",opacity:.4}}},rle=e=>{const{align:t="start",orientation:n}=e;return{justifyContent:{end:"flex-end",center:"center",start:"flex-start"}[t],flexDirection:n==="vertical"?"column":"row"}},ole={p:4},ile=fi(e=>({root:tle(e),tab:nle(e),tablist:rle(e),tabpanel:ole})),ale={sm:fi({tab:{py:1,px:4,fontSize:"sm"}}),md:fi({tab:{fontSize:"md",py:2,px:4}}),lg:fi({tab:{fontSize:"lg",py:3,px:4}})},sle=fi(e=>{const{colorScheme:t,orientation:n}=e,r=n==="vertical",o=n==="vertical"?"borderStart":"borderBottom",i=r?"marginStart":"marginBottom";return{tablist:{[o]:"2px solid",borderColor:"inherit"},tab:{[o]:"2px 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r=0;this.polling&&(r++,this.once("pollComplete",function(){--r||n()})),this.writable||(r++,this.once("drain",function(){--r||n()}))}else n()}poll(){this.polling=!0,this.doPoll(),this.emitReserved("poll")}onData(t){const n=r=>{if(this.readyState==="opening"&&r.type==="open"&&this.onOpen(),r.type==="close")return this.onClose({description:"transport closed by the server"}),!1;this.onPacket(r)};ode(t,this.socket.binaryType).forEach(n),this.readyState!=="closed"&&(this.polling=!1,this.emitReserved("pollComplete"),this.readyState==="open"&&this.poll())}doClose(){const t=()=>{this.write([{type:"close"}])};this.readyState==="open"?t():this.once("open",t)}write(t){this.writable=!1,rde(t,n=>{this.doWrite(n,()=>{this.writable=!0,this.emitReserved("drain")})})}uri(){let t=this.query||{};const n=this.opts.secure?"https":"http";let r="";this.opts.timestampRequests!==!1&&(t[this.opts.timestampParam]=dI()),!this.supportsBinary&&!t.sid&&(t.b64=1),this.opts.port&&(n==="https"&&Number(this.opts.port)!==443||n==="http"&&Number(this.opts.port)!==80)&&(r=":"+this.opts.port);const o=pI(t),i=this.opts.hostname.indexOf(":")!==-1;return n+"://"+(i?"["+this.opts.hostname+"]":this.opts.hostname)+r+this.opts.path+(o.length?"?"+o:"")}request(t={}){return Object.assign(t,{xd:this.xd,xs:this.xs},this.opts),new pi(this.uri(),t)}doWrite(t,n){const r=this.request({method:"POST",data:t});r.on("success",n),r.on("error",(o,i)=>{this.onError("xhr post error",o,i)})}doPoll(){const t=this.request();t.on("data",this.onData.bind(this)),t.on("error",(n,r)=>{this.onError("xhr poll error",n,r)}),this.pollXhr=t}}class pi extends dn{constructor(t,n){super(),Vm(this,n),this.opts=n,this.method=n.method||"GET",this.uri=t,this.async=n.async!==!1,this.data=n.data!==void 0?n.data:null,this.create()}create(){const t=uI(this.opts,"agent","pfx","key","passphrase","cert","ca","ciphers","rejectUnauthorized","autoUnref");t.xdomain=!!this.opts.xd,t.xscheme=!!this.opts.xs;const n=this.xhr=new mI(t);try{n.open(this.method,this.uri,this.async);try{if(this.opts.extraHeaders){n.setDisableHeaderCheck&&n.setDisableHeaderCheck(!0);for(let r in this.opts.extraHeaders)this.opts.extraHeaders.hasOwnProperty(r)&&n.setRequestHeader(r,this.opts.extraHeaders[r])}}catch{}if(this.method==="POST")try{n.setRequestHeader("Content-type","text/plain;charset=UTF-8")}catch{}try{n.setRequestHeader("Accept","*/*")}catch{}"withCredentials"in n&&(n.withCredentials=this.opts.withCredentials),this.opts.requestTimeout&&(n.timeout=this.opts.requestTimeout),n.onreadystatechange=()=>{n.readyState===4&&(n.status===200||n.status===1223?this.onLoad():this.setTimeoutFn(()=>{this.onError(typeof n.status=="number"?n.status:0)},0))},n.send(this.data)}catch(r){this.setTimeoutFn(()=>{this.onError(r)},0);return}typeof document<"u"&&(this.index=pi.requestsCount++,pi.requests[this.index]=this)}onError(t){this.emitReserved("error",t,this.xhr),this.cleanup(!0)}cleanup(t){if(!(typeof this.xhr>"u"||this.xhr===null)){if(this.xhr.onreadystatechange=mde,t)try{this.xhr.abort()}catch{}typeof document<"u"&&delete pi.requests[this.index],this.xhr=null}}onLoad(){const t=this.xhr.responseText;t!==null&&(this.emitReserved("data",t),this.emitReserved("success"),this.cleanup())}abort(){this.cleanup()}}pi.requestsCount=0;pi.requests={};if(typeof document<"u"){if(typeof attachEvent=="function")attachEvent("onunload",B7);else if(typeof addEventListener=="function"){const e="onpagehide"in Na?"pagehide":"unload";addEventListener(e,B7,!1)}}function B7(){for(let e in pi.requests)pi.requests.hasOwnProperty(e)&&pi.requests[e].abort()}const yde=(()=>typeof Promise=="function"&&typeof Promise.resolve=="function"?t=>Promise.resolve().then(t):(t,n)=>n(t,0))(),kh=Na.WebSocket||Na.MozWebSocket,$7=!0,bde="arraybuffer",V7=typeof navigator<"u"&&typeof navigator.product=="string"&&navigator.product.toLowerCase()==="reactnative";class xde extends cI{constructor(t){super(t),this.supportsBinary=!t.forceBase64}get name(){return"websocket"}doOpen(){if(!this.check())return;const t=this.uri(),n=this.opts.protocols,r=V7?{}:uI(this.opts,"agent","perMessageDeflate","pfx","key","passphrase","cert","ca","ciphers","rejectUnauthorized","localAddress","protocolVersion","origin","maxPayload","family","checkServerIdentity");this.opts.extraHeaders&&(r.headers=this.opts.extraHeaders);try{this.ws=$7&&!V7?n?new kh(t,n):new kh(t):new kh(t,n,r)}catch(o){return this.emitReserved("error",o)}this.ws.binaryType=this.socket.binaryType||bde,this.addEventListeners()}addEventListeners(){this.ws.onopen=()=>{this.opts.autoUnref&&this.ws._socket.unref(),this.onOpen()},this.ws.onclose=t=>this.onClose({description:"websocket connection closed",context:t}),this.ws.onmessage=t=>this.onData(t.data),this.ws.onerror=t=>this.onError("websocket error",t)}write(t){this.writable=!1;for(let n=0;n{const s={};try{$7&&this.ws.send(i)}catch{}o&&yde(()=>{this.writable=!0,this.emitReserved("drain")},this.setTimeoutFn)})}}doClose(){typeof this.ws<"u"&&(this.ws.close(),this.ws=null)}uri(){let t=this.query||{};const n=this.opts.secure?"wss":"ws";let r="";this.opts.port&&(n==="wss"&&Number(this.opts.port)!==443||n==="ws"&&Number(this.opts.port)!==80)&&(r=":"+this.opts.port),this.opts.timestampRequests&&(t[this.opts.timestampParam]=dI()),this.supportsBinary||(t.b64=1);const o=pI(t),i=this.opts.hostname.indexOf(":")!==-1;return n+"://"+(i?"["+this.opts.hostname+"]":this.opts.hostname)+r+this.opts.path+(o.length?"?"+o:"")}check(){return!!kh}}const wde={websocket:xde,polling:vde},Sde=/^(?:(?![^:@]+:[^:@\/]*@)(http|https|ws|wss):\/\/)?((?:(([^:@]*)(?::([^:@]*))?)?@)?((?:[a-f0-9]{0,4}:){2,7}[a-f0-9]{0,4}|[^:\/?#]*)(?::(\d*))?)(((\/(?:[^?#](?![^?#\/]*\.[^?#\/.]+(?:[?#]|$)))*\/?)?([^?#\/]*))(?:\?([^#]*))?(?:#(.*))?)/,Cde=["source","protocol","authority","userInfo","user","password","host","port","relative","path","directory","file","query","anchor"];function n5(e){const t=e,n=e.indexOf("["),r=e.indexOf("]");n!=-1&&r!=-1&&(e=e.substring(0,n)+e.substring(n,r).replace(/:/g,";")+e.substring(r,e.length));let o=Sde.exec(e||""),i={},s=14;for(;s--;)i[Cde[s]]=o[s]||"";return n!=-1&&r!=-1&&(i.source=t,i.host=i.host.substring(1,i.host.length-1).replace(/;/g,":"),i.authority=i.authority.replace("[","").replace("]","").replace(/;/g,":"),i.ipv6uri=!0),i.pathNames=_de(i,i.path),i.queryKey=kde(i,i.query),i}function _de(e,t){const n=/\/{2,9}/g,r=t.replace(n,"/").split("/");return(t.substr(0,1)=="/"||t.length===0)&&r.splice(0,1),t.substr(t.length-1,1)=="/"&&r.splice(r.length-1,1),r}function kde(e,t){const n={};return t.replace(/(?:^|&)([^&=]*)=?([^&]*)/g,function(r,o,i){o&&(n[o]=i)}),n}class Pa extends dn{constructor(t,n={}){super(),t&&typeof t=="object"&&(n=t,t=null),t?(t=n5(t),n.hostname=t.host,n.secure=t.protocol==="https"||t.protocol==="wss",n.port=t.port,t.query&&(n.query=t.query)):n.host&&(n.hostname=n5(n.host).host),Vm(this,n),this.secure=n.secure!=null?n.secure:typeof location<"u"&&location.protocol==="https:",n.hostname&&!n.port&&(n.port=this.secure?"443":"80"),this.hostname=n.hostname||(typeof location<"u"?location.hostname:"localhost"),this.port=n.port||(typeof location<"u"&&location.port?location.port:this.secure?"443":"80"),this.transports=n.transports||["polling","websocket"],this.readyState="",this.writeBuffer=[],this.prevBufferLen=0,this.opts=Object.assign({path:"/engine.io",agent:!1,withCredentials:!1,upgrade:!0,timestampParam:"t",rememberUpgrade:!1,rejectUnauthorized:!0,perMessageDeflate:{threshold:1024},transportOptions:{},closeOnBeforeunload:!0},n),this.opts.path=this.opts.path.replace(/\/$/,"")+"/",typeof this.opts.query=="string"&&(this.opts.query=pde(this.opts.query)),this.id=null,this.upgrades=null,this.pingInterval=null,this.pingTimeout=null,this.pingTimeoutTimer=null,typeof addEventListener=="function"&&(this.opts.closeOnBeforeunload&&addEventListener("beforeunload",()=>{this.transport&&(this.transport.removeAllListeners(),this.transport.close())},!1),this.hostname!=="localhost"&&(this.offlineEventListener=()=>{this.onClose("transport close",{description:"network connection lost"})},addEventListener("offline",this.offlineEventListener,!1))),this.open()}createTransport(t){const n=Object.assign({},this.opts.query);n.EIO=lI,n.transport=t,this.id&&(n.sid=this.id);const r=Object.assign({},this.opts.transportOptions[t],this.opts,{query:n,socket:this,hostname:this.hostname,secure:this.secure,port:this.port});return new wde[t](r)}open(){let t;if(this.opts.rememberUpgrade&&Pa.priorWebsocketSuccess&&this.transports.indexOf("websocket")!==-1)t="websocket";else if(this.transports.length===0){this.setTimeoutFn(()=>{this.emitReserved("error","No transports available")},0);return}else t=this.transports[0];this.readyState="opening";try{t=this.createTransport(t)}catch{this.transports.shift(),this.open();return}t.open(),this.setTransport(t)}setTransport(t){this.transport&&this.transport.removeAllListeners(),this.transport=t,t.on("drain",this.onDrain.bind(this)).on("packet",this.onPacket.bind(this)).on("error",this.onError.bind(this)).on("close",n=>this.onClose("transport close",n))}probe(t){let n=this.createTransport(t),r=!1;Pa.priorWebsocketSuccess=!1;const o=()=>{r||(n.send([{type:"ping",data:"probe"}]),n.once("packet",h=>{if(!r)if(h.type==="pong"&&h.data==="probe"){if(this.upgrading=!0,this.emitReserved("upgrading",n),!n)return;Pa.priorWebsocketSuccess=n.name==="websocket",this.transport.pause(()=>{r||this.readyState!=="closed"&&(d(),this.setTransport(n),n.send([{type:"upgrade"}]),this.emitReserved("upgrade",n),n=null,this.upgrading=!1,this.flush())})}else{const m=new Error("probe error");m.transport=n.name,this.emitReserved("upgradeError",m)}}))};function i(){r||(r=!0,d(),n.close(),n=null)}const s=h=>{const m=new Error("probe error: "+h);m.transport=n.name,i(),this.emitReserved("upgradeError",m)};function u(){s("transport closed")}function c(){s("socket closed")}function f(h){n&&h.name!==n.name&&i()}const d=()=>{n.removeListener("open",o),n.removeListener("error",s),n.removeListener("close",u),this.off("close",c),this.off("upgrading",f)};n.once("open",o),n.once("error",s),n.once("close",u),this.once("close",c),this.once("upgrading",f),n.open()}onOpen(){if(this.readyState="open",Pa.priorWebsocketSuccess=this.transport.name==="websocket",this.emitReserved("open"),this.flush(),this.readyState==="open"&&this.opts.upgrade&&this.transport.pause){let t=0;const n=this.upgrades.length;for(;t{this.onClose("ping timeout")},this.pingInterval+this.pingTimeout),this.opts.autoUnref&&this.pingTimeoutTimer.unref()}onDrain(){this.writeBuffer.splice(0,this.prevBufferLen),this.prevBufferLen=0,this.writeBuffer.length===0?this.emitReserved("drain"):this.flush()}flush(){if(this.readyState!=="closed"&&this.transport.writable&&!this.upgrading&&this.writeBuffer.length){const t=this.getWritablePackets();this.transport.send(t),this.prevBufferLen=t.length,this.emitReserved("flush")}}getWritablePackets(){if(!(this.maxPayload&&this.transport.name==="polling"&&this.writeBuffer.length>1))return this.writeBuffer;let n=1;for(let r=0;r0&&n>this.maxPayload)return this.writeBuffer.slice(0,r);n+=2}return this.writeBuffer}write(t,n,r){return this.sendPacket("message",t,n,r),this}send(t,n,r){return this.sendPacket("message",t,n,r),this}sendPacket(t,n,r,o){if(typeof n=="function"&&(o=n,n=void 0),typeof r=="function"&&(o=r,r=null),this.readyState==="closing"||this.readyState==="closed")return;r=r||{},r.compress=r.compress!==!1;const i={type:t,data:n,options:r};this.emitReserved("packetCreate",i),this.writeBuffer.push(i),o&&this.once("flush",o),this.flush()}close(){const t=()=>{this.onClose("forced close"),this.transport.close()},n=()=>{this.off("upgrade",n),this.off("upgradeError",n),t()},r=()=>{this.once("upgrade",n),this.once("upgradeError",n)};return(this.readyState==="opening"||this.readyState==="open")&&(this.readyState="closing",this.writeBuffer.length?this.once("drain",()=>{this.upgrading?r():t()}):this.upgrading?r():t()),this}onError(t){Pa.priorWebsocketSuccess=!1,this.emitReserved("error",t),this.onClose("transport error",t)}onClose(t,n){(this.readyState==="opening"||this.readyState==="open"||this.readyState==="closing")&&(this.clearTimeoutFn(this.pingTimeoutTimer),this.transport.removeAllListeners("close"),this.transport.close(),this.transport.removeAllListeners(),typeof removeEventListener=="function"&&removeEventListener("offline",this.offlineEventListener,!1),this.readyState="closed",this.id=null,this.emitReserved("close",t,n),this.writeBuffer=[],this.prevBufferLen=0)}filterUpgrades(t){const n=[];let r=0;const o=t.length;for(;rtypeof ArrayBuffer.isView=="function"?ArrayBuffer.isView(e):e.buffer instanceof ArrayBuffer,gI=Object.prototype.toString,Ade=typeof Blob=="function"||typeof Blob<"u"&&gI.call(Blob)==="[object BlobConstructor]",Tde=typeof File=="function"||typeof File<"u"&&gI.call(File)==="[object FileConstructor]";function t6(e){return Lde&&(e instanceof ArrayBuffer||Pde(e))||Ade&&e instanceof Blob||Tde&&e instanceof File}function c1(e,t){if(!e||typeof e!="object")return!1;if(Array.isArray(e)){for(let n=0,r=e.length;n=0&&e.num0;case Qe.ACK:case Qe.BINARY_ACK:return Array.isArray(n)}}destroy(){this.reconstructor&&this.reconstructor.finishedReconstruction()}}class Nde{constructor(t){this.packet=t,this.buffers=[],this.reconPack=t}takeBinaryData(t){if(this.buffers.push(t),this.buffers.length===this.reconPack.attachments){const n=Ode(this.reconPack,this.buffers);return this.finishedReconstruction(),n}return null}finishedReconstruction(){this.reconPack=null,this.buffers=[]}}const Dde=Object.freeze(Object.defineProperty({__proto__:null,protocol:Mde,get PacketType(){return Qe},Encoder:Rde,Decoder:n6},Symbol.toStringTag,{value:"Module"}));function Oo(e,t,n){return e.on(t,n),function(){e.off(t,n)}}const zde=Object.freeze({connect:1,connect_error:1,disconnect:1,disconnecting:1,newListener:1,removeListener:1});class vI extends dn{constructor(t,n,r){super(),this.connected=!1,this.receiveBuffer=[],this.sendBuffer=[],this.ids=0,this.acks={},this.flags={},this.io=t,this.nsp=n,r&&r.auth&&(this.auth=r.auth),this.io._autoConnect&&this.open()}get disconnected(){return!this.connected}subEvents(){if(this.subs)return;const t=this.io;this.subs=[Oo(t,"open",this.onopen.bind(this)),Oo(t,"packet",this.onpacket.bind(this)),Oo(t,"error",this.onerror.bind(this)),Oo(t,"close",this.onclose.bind(this))]}get active(){return!!this.subs}connect(){return this.connected?this:(this.subEvents(),this.io._reconnecting||this.io.open(),this.io._readyState==="open"&&this.onopen(),this)}open(){return this.connect()}send(...t){return t.unshift("message"),this.emit.apply(this,t),this}emit(t,...n){if(zde.hasOwnProperty(t))throw new Error('"'+t.toString()+'" is a reserved event name');n.unshift(t);const r={type:Qe.EVENT,data:n};if(r.options={},r.options.compress=this.flags.compress!==!1,typeof n[n.length-1]=="function"){const s=this.ids++,u=n.pop();this._registerAckCallback(s,u),r.id=s}const o=this.io.engine&&this.io.engine.transport&&this.io.engine.transport.writable;return this.flags.volatile&&(!o||!this.connected)||(this.connected?(this.notifyOutgoingListeners(r),this.packet(r)):this.sendBuffer.push(r)),this.flags={},this}_registerAckCallback(t,n){const r=this.flags.timeout;if(r===void 0){this.acks[t]=n;return}const o=this.io.setTimeoutFn(()=>{delete this.acks[t];for(let i=0;i{this.io.clearTimeoutFn(o),n.apply(this,[null,...i])}}packet(t){t.nsp=this.nsp,this.io._packet(t)}onopen(){typeof this.auth=="function"?this.auth(t=>{this.packet({type:Qe.CONNECT,data:t})}):this.packet({type:Qe.CONNECT,data:this.auth})}onerror(t){this.connected||this.emitReserved("connect_error",t)}onclose(t,n){this.connected=!1,delete this.id,this.emitReserved("disconnect",t,n)}onpacket(t){if(t.nsp===this.nsp)switch(t.type){case Qe.CONNECT:if(t.data&&t.data.sid){const o=t.data.sid;this.onconnect(o)}else this.emitReserved("connect_error",new Error("It seems you are trying to reach a Socket.IO server in v2.x with a v3.x client, but they are not compatible (more information here: https://socket.io/docs/v3/migrating-from-2-x-to-3-0/)"));break;case Qe.EVENT:case Qe.BINARY_EVENT:this.onevent(t);break;case Qe.ACK:case Qe.BINARY_ACK:this.onack(t);break;case Qe.DISCONNECT:this.ondisconnect();break;case Qe.CONNECT_ERROR:this.destroy();const r=new Error(t.data.message);r.data=t.data.data,this.emitReserved("connect_error",r);break}}onevent(t){const n=t.data||[];t.id!=null&&n.push(this.ack(t.id)),this.connected?this.emitEvent(n):this.receiveBuffer.push(Object.freeze(n))}emitEvent(t){if(this._anyListeners&&this._anyListeners.length){const n=this._anyListeners.slice();for(const r of n)r.apply(this,t)}super.emit.apply(this,t)}ack(t){const n=this;let r=!1;return function(...o){r||(r=!0,n.packet({type:Qe.ACK,id:t,data:o}))}}onack(t){const n=this.acks[t.id];typeof n=="function"&&(n.apply(this,t.data),delete this.acks[t.id])}onconnect(t){this.id=t,this.connected=!0,this.emitBuffered(),this.emitReserved("connect")}emitBuffered(){this.receiveBuffer.forEach(t=>this.emitEvent(t)),this.receiveBuffer=[],this.sendBuffer.forEach(t=>{this.notifyOutgoingListeners(t),this.packet(t)}),this.sendBuffer=[]}ondisconnect(){this.destroy(),this.onclose("io server disconnect")}destroy(){this.subs&&(this.subs.forEach(t=>t()),this.subs=void 0),this.io._destroy(this)}disconnect(){return this.connected&&this.packet({type:Qe.DISCONNECT}),this.destroy(),this.connected&&this.onclose("io client disconnect"),this}close(){return this.disconnect()}compress(t){return this.flags.compress=t,this}get volatile(){return this.flags.volatile=!0,this}timeout(t){return this.flags.timeout=t,this}onAny(t){return this._anyListeners=this._anyListeners||[],this._anyListeners.push(t),this}prependAny(t){return this._anyListeners=this._anyListeners||[],this._anyListeners.unshift(t),this}offAny(t){if(!this._anyListeners)return this;if(t){const n=this._anyListeners;for(let r=0;r0&&e.jitter<=1?e.jitter:0,this.attempts=0}Wu.prototype.duration=function(){var e=this.ms*Math.pow(this.factor,this.attempts++);if(this.jitter){var t=Math.random(),n=Math.floor(t*this.jitter*e);e=(Math.floor(t*10)&1)==0?e-n:e+n}return Math.min(e,this.max)|0};Wu.prototype.reset=function(){this.attempts=0};Wu.prototype.setMin=function(e){this.ms=e};Wu.prototype.setMax=function(e){this.max=e};Wu.prototype.setJitter=function(e){this.jitter=e};class i5 extends dn{constructor(t,n){var r;super(),this.nsps={},this.subs=[],t&&typeof t=="object"&&(n=t,t=void 0),n=n||{},n.path=n.path||"/socket.io",this.opts=n,Vm(this,n),this.reconnection(n.reconnection!==!1),this.reconnectionAttempts(n.reconnectionAttempts||1/0),this.reconnectionDelay(n.reconnectionDelay||1e3),this.reconnectionDelayMax(n.reconnectionDelayMax||5e3),this.randomizationFactor((r=n.randomizationFactor)!==null&&r!==void 0?r:.5),this.backoff=new Wu({min:this.reconnectionDelay(),max:this.reconnectionDelayMax(),jitter:this.randomizationFactor()}),this.timeout(n.timeout==null?2e4:n.timeout),this._readyState="closed",this.uri=t;const o=n.parser||Dde;this.encoder=new o.Encoder,this.decoder=new o.Decoder,this._autoConnect=n.autoConnect!==!1,this._autoConnect&&this.open()}reconnection(t){return arguments.length?(this._reconnection=!!t,this):this._reconnection}reconnectionAttempts(t){return t===void 0?this._reconnectionAttempts:(this._reconnectionAttempts=t,this)}reconnectionDelay(t){var n;return t===void 0?this._reconnectionDelay:(this._reconnectionDelay=t,(n=this.backoff)===null||n===void 0||n.setMin(t),this)}randomizationFactor(t){var n;return t===void 0?this._randomizationFactor:(this._randomizationFactor=t,(n=this.backoff)===null||n===void 0||n.setJitter(t),this)}reconnectionDelayMax(t){var n;return t===void 0?this._reconnectionDelayMax:(this._reconnectionDelayMax=t,(n=this.backoff)===null||n===void 0||n.setMax(t),this)}timeout(t){return arguments.length?(this._timeout=t,this):this._timeout}maybeReconnectOnOpen(){!this._reconnecting&&this._reconnection&&this.backoff.attempts===0&&this.reconnect()}open(t){if(~this._readyState.indexOf("open"))return this;this.engine=new Pa(this.uri,this.opts);const n=this.engine,r=this;this._readyState="opening",this.skipReconnect=!1;const o=Oo(n,"open",function(){r.onopen(),t&&t()}),i=Oo(n,"error",s=>{r.cleanup(),r._readyState="closed",this.emitReserved("error",s),t?t(s):r.maybeReconnectOnOpen()});if(this._timeout!==!1){const s=this._timeout;s===0&&o();const u=this.setTimeoutFn(()=>{o(),n.close(),n.emit("error",new Error("timeout"))},s);this.opts.autoUnref&&u.unref(),this.subs.push(function(){clearTimeout(u)})}return this.subs.push(o),this.subs.push(i),this}connect(t){return this.open(t)}onopen(){this.cleanup(),this._readyState="open",this.emitReserved("open");const t=this.engine;this.subs.push(Oo(t,"ping",this.onping.bind(this)),Oo(t,"data",this.ondata.bind(this)),Oo(t,"error",this.onerror.bind(this)),Oo(t,"close",this.onclose.bind(this)),Oo(this.decoder,"decoded",this.ondecoded.bind(this)))}onping(){this.emitReserved("ping")}ondata(t){try{this.decoder.add(t)}catch{this.onclose("parse 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o=this.props,i=o.maxWidth,s=o.maxHeight,u=o.minWidth,c=o.minHeight,f=Oh(n)?n.touches[0].clientX:n.clientX,d=Oh(n)?n.touches[0].clientY:n.clientY,h=this.state,m=h.direction,g=h.original,b=h.width,x=h.height,k=this.getParentSize(),S=z1e(k,this.window.innerWidth,this.window.innerHeight,i,s,u,c);i=S.maxWidth,s=S.maxHeight,u=S.minWidth,c=S.minHeight;var w=this.calculateNewSizeFromDirection(f,d),_=w.newHeight,L=w.newWidth,T=this.calculateNewMaxFromBoundary(i,s);this.props.snap&&this.props.snap.x&&(L=hC(L,this.props.snap.x,this.props.snapGap)),this.props.snap&&this.props.snap.y&&(_=hC(_,this.props.snap.y,this.props.snapGap));var R=this.calculateNewSizeFromAspectRatio(L,_,{width:T.maxWidth,height:T.maxHeight},{width:u,height:c});if(L=R.newWidth,_=R.newHeight,this.props.grid){var N=pC(L,this.props.grid[0]),z=pC(_,this.props.grid[1]),K=this.props.snapGap||0;L=K===0||Math.abs(N-L)<=K?N:L,_=K===0||Math.abs(z-_)<=K?z:_}var W={width:L-g.width,height:_-g.height};if(b&&typeof b=="string"){if(b.endsWith("%")){var J=L/k.width*100;L=J+"%"}else if(b.endsWith("vw")){var ve=L/this.window.innerWidth*100;L=ve+"vw"}else if(b.endsWith("vh")){var xe=L/this.window.innerHeight*100;L=xe+"vh"}}if(x&&typeof x=="string"){if(x.endsWith("%")){var J=_/k.height*100;_=J+"%"}else if(x.endsWith("vw")){var ve=_/this.window.innerWidth*100;_=ve+"vw"}else if(x.endsWith("vh")){var xe=_/this.window.innerHeight*100;_=xe+"vh"}}var he={width:this.createSizeForCssProperty(L,"width"),height:this.createSizeForCssProperty(_,"height")};this.flexDir==="row"?he.flexBasis=he.width:this.flexDir==="column"&&(he.flexBasis=he.height),Tu.exports.flushSync(function(){r.setState(he)}),this.props.onResize&&this.props.onResize(n,m,this.resizable,W)}},t.prototype.onMouseUp=function(n){var r=this.state,o=r.isResizing,i=r.direction,s=r.original;if(!(!o||!this.resizable)){var u={width:this.size.width-s.width,height:this.size.height-s.height};this.props.onResizeStop&&this.props.onResizeStop(n,i,this.resizable,u),this.props.size&&this.setState(this.props.size),this.unbindEvents(),this.setState({isResizing:!1,backgroundStyle:Xo(Xo({},this.state.backgroundStyle),{cursor:"auto"})})}},t.prototype.updateSize=function(n){this.setState({width:n.width,height:n.height})},t.prototype.renderResizer=function(){var n=this,r=this.props,o=r.enable,i=r.handleStyles,s=r.handleClasses,u=r.handleWrapperStyle,c=r.handleWrapperClass,f=r.handleComponent;if(!o)return null;var d=Object.keys(o).map(function(h){return o[h]!==!1?v(M1e,{direction:h,onResizeStart:n.onResizeStart,replaceStyles:i&&i[h],className:s&&s[h],children:f&&f[h]?f[h]:null},h):null});return v("div",{className:c,style:u,children:d})},t.prototype.render=function(){var n=this,r=Object.keys(this.props).reduce(function(s,u){return F1e.indexOf(u)!==-1||(s[u]=n.props[u]),s},{}),o=Xo(Xo(Xo({position:"relative",userSelect:this.state.isResizing?"none":"auto"},this.props.style),this.sizeStyle),{maxWidth:this.props.maxWidth,maxHeight:this.props.maxHeight,minWidth:this.props.minWidth,minHeight:this.props.minHeight,boxSizing:"border-box",flexShrink:0});this.state.flexBasis&&(o.flexBasis=this.state.flexBasis);var i=this.props.as||"div";return q(i,{...Xo({ref:this.ref,style:o,className:this.props.className},r),children:[this.state.isResizing&&v("div",{style:this.state.backgroundStyle}),this.props.children,this.renderResizer()]})},t.defaultProps={as:"div",onResizeStart:function(){},onResize:function(){},onResizeStop:function(){},enable:{top:!0,right:!0,bottom:!0,left:!0,topRight:!0,bottomRight:!0,bottomLeft:!0,topLeft:!0},style:{},grid:[1,1],lockAspectRatio:!1,lockAspectRatioExtraWidth:0,lockAspectRatioExtraHeight:0,scale:1,resizeRatio:1,snapGap:0},t}(C.exports.PureComponent);function B1e(e,t){if(e==null)return{};var n=$1e(e,t),r,o;if(Object.getOwnPropertySymbols){var i=Object.getOwnPropertySymbols(e);for(o=0;o=0)&&(!Object.prototype.propertyIsEnumerable.call(e,r)||(n[r]=e[r]))}return n}function $1e(e,t){if(e==null)return{};var n={},r=Object.keys(e),o,i;for(i=0;i=0)&&(n[o]=e[o]);return n}function gC(e,t){var n=Object.keys(e);if(Object.getOwnPropertySymbols){var r=Object.getOwnPropertySymbols(e);t&&(r=r.filter(function(o){return Object.getOwnPropertyDescriptor(e,o).enumerable})),n.push.apply(n,r)}return n}function Nc(e){for(var t=1;t{this.reCalculateColumnCount()})}reCalculateColumnCount(){const t=window&&window.innerWidth||1/0;let n=this.props.breakpointCols;typeof n!="object"&&(n={default:parseInt(n)||H2});let r=1/0,o=n.default||H2;for(let i in n){const s=parseInt(i);s>0&&t<=s&&s"u"&&(s="my-masonry-grid_column"));const u=Nc(Nc(Nc({},t),n),{},{style:Nc(Nc({},n.style),{},{width:i}),className:s});return o.map((c,f)=>C.exports.createElement("div",{...u,key:f},c))}logDeprecated(t){console.error("[Masonry]",t)}render(){const t=this.props,{children:n,breakpointCols:r,columnClassName:o,columnAttrs:i,column:s,className:u}=t,c=B1e(t,["children","breakpointCols","columnClassName","columnAttrs","column","className"]);let f=u;return typeof u!="string"&&(this.logDeprecated('The property "className" requires a string'),typeof u>"u"&&(f="my-masonry-grid")),v("div",{...c,className:f,children:this.renderColumns()})}}sO.defaultProps=W1e;const j1e=(e,t)=>e.image.uuid===t.image.uuid&&e.isSelected===t.isSelected,H1e=C.exports.memo(e=>{const[t,n]=C.exports.useState(!1),r=Ue(),o=Ee(k=>k.options.activeTab),{image:i,isSelected:s}=e,{url:u,uuid:c,metadata:f}=i,d=()=>n(!0),h=()=>n(!1),m=k=>{k.stopPropagation(),r(XT(f))},g=k=>{k.stopPropagation(),r(Id(i.metadata.image.seed))},b=k=>{k.stopPropagation(),r(Pu(i.url)),o!==1&&r(Bi(1))};return q(po,{position:"relative",className:"hoverable-image",onMouseOver:d,onMouseOut:h,children:[v(ym,{objectFit:"cover",rounded:"md",src:u,loading:"lazy",className:"hoverable-image-image"}),v("div",{className:"hoverable-image-content",onClick:()=>r(Dfe(i)),children:s&&v(Kr,{width:"50%",height:"50%",as:whe,className:"hoverable-image-check"})}),t&&q("div",{className:"hoverable-image-icons",children:[v(Rn,{label:"Delete image",hasArrow:!0,children:v(JI,{image:i,children:v(un,{colorScheme:"red","aria-label":"Delete image",icon:v(Ahe,{}),size:"xs",variant:"imageHoverIconButton",fontSize:14})})}),["txt2img","img2img"].includes(i?.metadata?.image?.type)&&v(Rn,{label:"Use All Parameters",hasArrow:!0,children:v(un,{"aria-label":"Use All Parameters",icon:v(oO,{}),size:"xs",fontSize:18,variant:"imageHoverIconButton",onClickCapture:m})}),i?.metadata?.image?.seed!==void 0&&v(Rn,{label:"Use Seed",hasArrow:!0,children:v(un,{"aria-label":"Use Seed",icon:v(Lhe,{}),size:"xs",fontSize:16,variant:"imageHoverIconButton",onClickCapture:g})}),v(Rn,{label:"Send To Image To Image",hasArrow:!0,children:v(un,{"aria-label":"Send To Image To Image",icon:v(_he,{}),size:"xs",fontSize:16,variant:"imageHoverIconButton",onClickCapture:b})})]})]},c)},j1e);function lO(){const{images:e,currentImageUuid:t,areMoreImagesAvailable:n}=Ee(m=>m.gallery),r=Ee(m=>m.options.shouldShowGallery),o=Ee(m=>m.options.activeTab),i=Ue(),[s,u]=C.exports.useState(),c=m=>{u(Math.floor((window.innerWidth-m.x)/120))},f=()=>{i(A7(!r))},d=()=>{i(A7(!1))},h=()=>{i(yI())};return rn("g",()=>{f()},[r]),rn("left",()=>{i(eI())},[]),rn("right",()=>{i(JT())},[]),q("div",{className:"image-gallery-area",children:[!r&&v(Aa,{tooltip:"Show Gallery",tooltipPlacement:"top","aria-label":"Show Gallery",onClick:f,className:"image-gallery-popup-btn",children:v(Y7,{})}),r&&q(aO,{defaultSize:{width:"300",height:"100%"},minWidth:"300",maxWidth:o==1?"300":"600",className:"image-gallery-popup",onResize:c,children:[q("div",{className:"image-gallery-header",children:[v("h1",{children:"Your Invocations"}),v(un,{size:"sm","aria-label":"Close Gallery",onClick:d,className:"image-gallery-close-btn",icon:v(DI,{})})]}),q("div",{className:"image-gallery-container",children:[e.length?v(sO,{className:"masonry-grid",columnClassName:"masonry-grid_column",breakpointCols:s,children:e.map(m=>{const{uuid:g}=m;return v(H1e,{image:m,isSelected:t===g},g)})}):q("div",{className:"image-gallery-container-placeholder",children:[v(Y7,{}),v("p",{children:"No Images In Gallery"})]}),v(mi,{onClick:h,isDisabled:!n,className:"image-gallery-load-more-btn",children:n?"Load More":"All Images Loaded"})]})]})]})}function U1e(){const e=Ee(t=>t.options.shouldShowGallery);return q("div",{className:"image-to-image-workarea",children:[v(mhe,{}),q("div",{className:"image-to-image-display-area",style:e?{gridTemplateColumns:"auto max-content"}:{gridTemplateColumns:"auto"},children:[v(T1e,{}),v(lO,{})]})]})}function G1e(){const e=Ee(n=>n.options.showAdvancedOptions),t={seed:{header:v(po,{flex:"1",textAlign:"left",children:"Seed"}),feature:No.SEED,options:v(LI,{})},variations:{header:v(AI,{}),feature:No.VARIATIONS,options:v(TI,{})},face_restore:{header:v(EI,{}),feature:No.FACE_CORRECTION,options:v(a6,{})},upscale:{header:v(PI,{}),feature:No.UPSCALE,options:v(s6,{})},other:{header:v(po,{flex:"1",textAlign:"left",children:"Other"}),feature:No.OTHER,options:v(FI,{})}};return q("div",{className:"text-to-image-panel",children:[v(VI,{}),v($I,{}),v(OI,{}),v(II,{}),e?v(zI,{accordionInfo:t}):null]})}const Z1e=()=>{const{currentImage:e,intermediateImage:t}=Ee(o=>o.gallery),n=Ee(o=>o.options.shouldShowImageDetails),r=t||e;return r?q("div",{className:"current-image-display",children:[v("div",{className:"current-image-tools",children:v(eO,{image:r})}),v(tO,{imageToDisplay:r}),n&&v(iO,{image:r,styleClass:"current-image-metadata"})]}):v("div",{className:"current-image-display-placeholder",children:v(ahe,{})})};function K1e(){const e=Ee(t=>t.options.shouldShowGallery);return q("div",{className:"text-to-image-workarea",children:[v(G1e,{}),q("div",{className:"text-to-image-display",style:e?{gridTemplateColumns:"auto max-content"}:{gridTemplateColumns:"auto"},children:[v(Z1e,{}),v(lO,{})]})]})}const Il={txt2img:{title:v(Lpe,{fill:"black",boxSize:"2.5rem"}),panel:v(K1e,{}),tooltip:"Text To Image"},img2img:{title:v(Spe,{fill:"black",boxSize:"2.5rem"}),panel:v(U1e,{}),tooltip:"Image To Image"},inpainting:{title:v(Cpe,{fill:"black",boxSize:"2.5rem"}),panel:v(ype,{}),tooltip:"Inpainting"},outpainting:{title:v(kpe,{fill:"black",boxSize:"2.5rem"}),panel:v(xpe,{}),tooltip:"Outpainting"},nodes:{title:v(_pe,{fill:"black",boxSize:"2.5rem"}),panel:v(bpe,{}),tooltip:"Nodes"},postprocess:{title:v(Epe,{fill:"black",boxSize:"2.5rem"}),panel:v(wpe,{}),tooltip:"Post Processing"}},q1e=rd.map(Il,(e,t)=>t);function Y1e(){const e=Ee(o=>o.options.activeTab),t=Ue();rn("1",()=>{t(Bi(0))}),rn("2",()=>{t(Bi(1))}),rn("3",()=>{t(Bi(2))}),rn("4",()=>{t(Bi(3))}),rn("5",()=>{t(Bi(4))}),rn("6",()=>{t(Bi(5))});const n=()=>{const o=[];return Object.keys(Il).forEach(i=>{o.push(v(Rn,{hasArrow:!0,label:Il[i].tooltip,placement:"right",children:v(ZA,{children:Il[i].title})},i))}),o},r=()=>{const o=[];return Object.keys(Il).forEach(i=>{o.push(v(UA,{className:"app-tabs-panel",children:Il[i].panel},i))}),o};return q(HA,{isLazy:!0,className:"app-tabs",variant:"unstyled",defaultIndex:e,index:e,onChange:o=>{t(Bi(o))},children:[v("div",{className:"app-tabs-list",children:n()}),v(GA,{className:"app-tabs-panels",children:r()})]})}const X1e=(e,t)=>{const{dispatch:n,getState:r}=e;return{emitGenerateImage:()=>{n(l1(!0));const o={...r().options};q1e[o.activeTab]==="txt2img"&&(o.shouldUseInitImage=!1);const{generationParameters:i,esrganParameters:s,gfpganParameters:u}=ape(o,r().system);t.emit("generateImage",i,s,u),n(nr({timestamp:rr(new Date,"isoDateTime"),message:`Image generation requested: ${JSON.stringify({...i,...s,...u})}`}))},emitRunESRGAN:o=>{n(l1(!0));const{upscalingLevel:i,upscalingStrength:s}=r().options,u={upscale:[i,s]};t.emit("runPostprocessing",o,{type:"esrgan",...u}),n(nr({timestamp:rr(new Date,"isoDateTime"),message:`ESRGAN upscale requested: ${JSON.stringify({file:o.url,...u})}`}))},emitRunGFPGAN:o=>{n(l1(!0));const{gfpganStrength:i}=r().options,s={gfpgan_strength:i};t.emit("runPostprocessing",o,{type:"gfpgan",...s}),n(nr({timestamp:rr(new Date,"isoDateTime"),message:`GFPGAN fix faces requested: ${JSON.stringify({file:o.url,...s})}`}))},emitDeleteImage:o=>{const{url:i,uuid:s}=o;t.emit("deleteImage",i,s)},emitRequestImages:()=>{const{earliest_mtime:o}=r().gallery;t.emit("requestImages",o)},emitRequestNewImages:()=>{const{latest_mtime:o}=r().gallery;t.emit("requestLatestImages",o)},emitCancelProcessing:()=>{t.emit("cancel")},emitUploadInitialImage:o=>{t.emit("uploadInitialImage",o,o.name)},emitUploadMaskImage:o=>{t.emit("uploadMaskImage",o,o.name)},emitRequestSystemConfig:()=>{t.emit("requestSystemConfig")}}},Q1e=()=>{const{hostname:e,port:t}=new URL(window.location.href),n=f1(`http://${e}:${t}`,{timeout:6e4});let r=!1;return i=>s=>u=>{const{onConnect:c,onDisconnect:f,onError:d,onPostprocessingResult:h,onGenerationResult:m,onIntermediateResult:g,onProgressUpdate:b,onGalleryImages:x,onProcessingCanceled:k,onImageDeleted:S,onInitialImageUploaded:w,onMaskImageUploaded:_,onSystemConfig:L}=tpe(i),{emitGenerateImage:T,emitRunESRGAN:R,emitRunGFPGAN:N,emitDeleteImage:z,emitRequestImages:K,emitRequestNewImages:W,emitCancelProcessing:J,emitUploadInitialImage:ve,emitUploadMaskImage:xe,emitRequestSystemConfig:he}=X1e(i,n);switch(r||(n.on("connect",()=>c()),n.on("disconnect",()=>f()),n.on("error",fe=>d(fe)),n.on("generationResult",fe=>m(fe)),n.on("postprocessingResult",fe=>h(fe)),n.on("intermediateResult",fe=>g(fe)),n.on("progressUpdate",fe=>b(fe)),n.on("galleryImages",fe=>x(fe)),n.on("processingCanceled",()=>{k()}),n.on("imageDeleted",fe=>{S(fe)}),n.on("initialImageUploaded",fe=>{w(fe)}),n.on("maskImageUploaded",fe=>{_(fe)}),n.on("systemConfig",fe=>{L(fe)}),r=!0),u.type){case"socketio/generateImage":{T();break}case"socketio/runESRGAN":{R(u.payload);break}case"socketio/runGFPGAN":{N(u.payload);break}case"socketio/deleteImage":{z(u.payload);break}case"socketio/requestImages":{K();break}case"socketio/requestNewImages":{W();break}case"socketio/cancelProcessing":{J();break}case"socketio/uploadInitialImage":{ve(u.payload);break}case"socketio/uploadMaskImage":{xe(u.payload);break}case"socketio/requestSystemConfig":{he();break}}s(u)}},J1e={key:"root",storage:Jb,blacklist:["gallery","system"]},e0e={key:"system",storage:Jb,blacklist:["isConnected","isProcessing","currentStep","socketId","isESRGANAvailable","isGFPGANAvailable","currentStep","totalSteps","currentIteration","totalIterations","currentStatus"]},t0e=wT({options:Mfe,gallery:Bfe,system:BT(e0e,qfe)}),n0e=BT(J1e,t0e),uO=oce({reducer:n0e,middleware:e=>e({serializableCheck:!1}).concat(Q1e())}),Ue=jce,Ee=Oce;function d1(e){return typeof Symbol=="function"&&typeof Symbol.iterator=="symbol"?d1=function(n){return typeof n}:d1=function(n){return n&&typeof Symbol=="function"&&n.constructor===Symbol&&n!==Symbol.prototype?"symbol":typeof n},d1(e)}function r0e(e,t){if(!(e instanceof t))throw new TypeError("Cannot call a class as a function")}function vC(e,t){for(var n=0;n({textColor:e.colorMode==="dark"?"gray.800":"gray.100"})},Accordion:{baseStyle:e=>({button:{fontWeight:"bold",_hover:{bgColor:e.colorMode==="dark"?"rgba(255,255,255,0.05)":"rgba(0,0,0,0.05)"}},panel:{paddingBottom:2}})},FormLabel:{baseStyle:{fontWeight:"light"}},Button:{variants:{imageHoverIconButton:e=>({bg:e.colorMode==="dark"?"blackAlpha.700":"whiteAlpha.800",color:e.colorMode==="dark"?"whiteAlpha.700":"blackAlpha.700",_hover:{bg:e.colorMode==="dark"?"blackAlpha.800":"whiteAlpha.800",color:e.colorMode==="dark"?"whiteAlpha.900":"blackAlpha.900"}})}}}}),fO=()=>v(Ft,{width:"100vw",height:"100vh",alignItems:"center",justifyContent:"center",children:v(gm,{thickness:"2px",speed:"1s",emptyColor:"gray.200",color:"gray.400",size:"xl"})}),s0e=qn(e=>e.system,e=>({isProcessing:e.isProcessing,currentStep:e.currentStep,totalSteps:e.totalSteps,currentStatusHasSteps:e.currentStatusHasSteps}),{memoizeOptions:{resultEqualityCheck:Kn.exports.isEqual}}),l0e=()=>{const{isProcessing:e,currentStep:t,totalSteps:n,currentStatusHasSteps:r}=Ee(s0e),o=t?Math.round(t*100/n):0;return v(zA,{height:"4px",value:o,isIndeterminate:e&&!r,className:"progress-bar"})},u0e="/assets/logo.13003d72.png";function c0e(e){const{title:t,hotkey:n,description:r}=e;return q("div",{className:"hotkey-modal-item",children:[q("div",{className:"hotkey-info",children:[v("p",{className:"hotkey-title",children:t}),r&&v("p",{className:"hotkey-description",children:r})]}),v("div",{className:"hotkey-key",children:n})]})}function f0e({children:e}){const{isOpen:t,onOpen:n,onClose:r}=o0(),o=[{title:"Invoke",desc:"Generate an image",hotkey:"Ctrl+Enter"},{title:"Cancel",desc:"Cancel image generation",hotkey:"Shift+X"},{title:"Toggle Gallery",desc:"Open and close the gallery drawer",hotkey:"G"},{title:"Set Seed",desc:"Use the seed of the current image",hotkey:"S"},{title:"Set Parameters",desc:"Use all parameters of the current image",hotkey:"A"},{title:"Restore Faces",desc:"Restore the current image",hotkey:"R"},{title:"Upscale",desc:"Upscale the current image",hotkey:"U"},{title:"Show Info",desc:"Show metadata info of the current image",hotkey:"I"},{title:"Send To Image To Image",desc:"Send the current image to Image to Image module",hotkey:"Shift+I"},{title:"Delete Image",desc:"Delete the current image",hotkey:"Del"},{title:"Focus Prompt",desc:"Focus the prompt input area",hotkey:"Alt+A"},{title:"Previous Image",desc:"Display the previous image in the gallery",hotkey:"Arrow left"},{title:"Next Image",desc:"Display the next image in the gallery",hotkey:"Arrow right"},{title:"Change Tabs",desc:"Switch to another workspace",hotkey:"1-6"},{title:"Theme Toggle",desc:"Switch between dark and light modes",hotkey:"Shift+D"},{title:"Console Toggle",desc:"Open and close console",hotkey:"`"}],i=()=>{const s=[];return o.forEach((u,c)=>{s.push(v(c0e,{title:u.title,description:u.desc,hotkey:u.hotkey},c))}),s};return q(yn,{children:[C.exports.cloneElement(e,{onClick:n}),q(ku,{isOpen:t,onClose:r,children:[v(Xf,{}),q(Yf,{className:"hotkeys-modal",children:[v(kb,{}),v("h1",{children:"Keyboard Shorcuts"}),v("div",{className:"hotkeys-modal-items",children:i()})]})]})]})}function U2({settingTitle:e,isChecked:t,dispatcher:n}){const r=Ue();return q(rs,{className:"settings-modal-item",children:[v(Gs,{marginBottom:1,children:e}),v(Lm,{isChecked:t,onChange:o=>r(n(o.target.checked))})]})}const d0e=qn(e=>e.system,e=>{const{shouldDisplayInProgress:t,shouldConfirmOnDelete:n,shouldDisplayGuides:r}=e;return{shouldDisplayInProgress:t,shouldConfirmOnDelete:n,shouldDisplayGuides:r}},{memoizeOptions:{resultEqualityCheck:Kn.exports.isEqual}}),p0e=({children:e})=>{const{isOpen:t,onOpen:n,onClose:r}=o0(),{isOpen:o,onOpen:i,onClose:s}=o0(),{shouldDisplayInProgress:u,shouldConfirmOnDelete:c,shouldDisplayGuides:f}=Ee(d0e),d=()=>{dO.purge().then(()=>{r(),i()})};return 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diff --git a/frontend/dist/index.html b/frontend/dist/index.html index 16d3460604..7fac16ba9e 100644 --- a/frontend/dist/index.html +++ b/frontend/dist/index.html @@ -6,8 +6,8 @@ InvokeAI - A Stable Diffusion Toolkit - - + + @@ -15,4 +15,4 @@ - \ No newline at end of file + diff --git a/frontend/src/features/gallery/CurrentImageDisplay.scss b/frontend/src/features/gallery/CurrentImageDisplay.scss index 5f1e8c9df5..81103e7d1a 100644 --- a/frontend/src/features/gallery/CurrentImageDisplay.scss +++ b/frontend/src/features/gallery/CurrentImageDisplay.scss @@ -71,7 +71,7 @@ .next-prev-button-trigger-area { width: 7rem; height: 100%; - width: 100%; + width: 15%; display: grid; align-items: center; pointer-events: auto; diff --git a/frontend/src/features/options/AdvancedOptions/Seed/SeedOptions.tsx b/frontend/src/features/options/AdvancedOptions/Seed/SeedOptions.tsx index c18004a4f2..9352466752 100644 --- a/frontend/src/features/options/AdvancedOptions/Seed/SeedOptions.tsx +++ b/frontend/src/features/options/AdvancedOptions/Seed/SeedOptions.tsx @@ -16,8 +16,12 @@ const SeedOptions = () => { - - + + + + + + ); }; diff --git a/frontend/src/features/options/optionsSlice.ts b/frontend/src/features/options/optionsSlice.ts index b979443de5..336a8bbd24 100644 --- a/frontend/src/features/options/optionsSlice.ts +++ b/frontend/src/features/options/optionsSlice.ts @@ -252,7 +252,9 @@ export const optionsSlice = createSlice({ if (steps) state.steps = steps; if (cfg_scale) state.cfgScale = cfg_scale; if (threshold) state.threshold = threshold; + if (typeof threshold === 'undefined') state.threshold = 0; if (perlin) state.perlin = perlin; + if (typeof perlin === 'undefined') state.perlin = 0; if (typeof seamless === 'boolean') state.seamless = seamless; if (width) state.width = width; if (height) state.height = height; diff --git a/frontend/src/features/system/SiteHeader.scss b/frontend/src/features/system/SiteHeader.scss index fa2b9f77df..b83fbc0f64 100644 --- a/frontend/src/features/system/SiteHeader.scss +++ b/frontend/src/features/system/SiteHeader.scss @@ -21,7 +21,7 @@ .site-header-right-side { display: grid; - grid-template-columns: repeat(6, max-content); + grid-template-columns: repeat(7, max-content); align-items: center; column-gap: 0.5rem; } diff --git a/frontend/src/features/system/SiteHeader.tsx b/frontend/src/features/system/SiteHeader.tsx index 761bc176b5..527bb2e8d8 100644 --- a/frontend/src/features/system/SiteHeader.tsx +++ b/frontend/src/features/system/SiteHeader.tsx @@ -1,7 +1,7 @@ import { IconButton, Link, Tooltip, useColorMode } from '@chakra-ui/react'; import { useHotkeys } from 'react-hotkeys-hook'; -import { FaSun, FaMoon, FaGithub } from 'react-icons/fa'; +import { FaSun, FaMoon, FaGithub, FaDiscord } from 'react-icons/fa'; import { MdHelp, MdKeyboard, MdSettings } from 'react-icons/md'; import InvokeAILogo from '../../assets/images/logo.png'; @@ -70,7 +70,7 @@ const SiteHeader = () => { icon={ @@ -85,13 +85,27 @@ const SiteHeader = () => { fontSize={20} size={'sm'} icon={ - + } /> + + + + + } + /> + + > WARNING: img2img and inpainting may produce unexpected results with initial images smaller than {self.width}x{self.height} in both dimensions') + # if image has a transparent area and no mask was provided, then try to generate mask - if self._has_transparency(image) and not mask: - print( - '>> Initial image has transparent areas. Will inpaint in these regions.') - if self._check_for_erasure(image): - print( - '>> WARNING: Colors underneath the transparent region seem to have been erased.\n', - '>> Inpainting will be suboptimal. Please preserve the colors when making\n', - '>> a transparency mask, or provide mask explicitly using --init_mask (-M).' - ) + if self._has_transparency(image): + self._transparency_check_and_warning(image, mask) # this returns a torch tensor - init_mask = self._create_init_mask(image,width,height,fit=fit) + init_mask = self._create_init_mask(image, width, height, fit=fit) if (image.width * image.height) > (self.width * self.height): print(">> This input is larger than your defaults. If you run out of memory, please use a smaller image.") @@ -621,39 +598,39 @@ class Generate: def _make_base(self): if not self.generators.get('base'): - from ldm.dream.generator import Generator + from ldm.invoke.generator import Generator self.generators['base'] = Generator(self.model, self.precision) return self.generators['base'] def _make_img2img(self): if not self.generators.get('img2img'): - from ldm.dream.generator.img2img import Img2Img + from ldm.invoke.generator.img2img import Img2Img self.generators['img2img'] = Img2Img(self.model, self.precision) return self.generators['img2img'] def _make_embiggen(self): if not self.generators.get('embiggen'): - from ldm.dream.generator.embiggen import Embiggen + from ldm.invoke.generator.embiggen import Embiggen self.generators['embiggen'] = Embiggen(self.model, self.precision) return self.generators['embiggen'] def _make_txt2img(self): if not self.generators.get('txt2img'): - from ldm.dream.generator.txt2img import Txt2Img + from ldm.invoke.generator.txt2img import Txt2Img self.generators['txt2img'] = Txt2Img(self.model, self.precision) self.generators['txt2img'].free_gpu_mem = self.free_gpu_mem return self.generators['txt2img'] def _make_txt2img2img(self): if not self.generators.get('txt2img2'): - from ldm.dream.generator.txt2img2img import Txt2Img2Img + from ldm.invoke.generator.txt2img2img import Txt2Img2Img self.generators['txt2img2'] = Txt2Img2Img(self.model, self.precision) self.generators['txt2img2'].free_gpu_mem = self.free_gpu_mem return self.generators['txt2img2'] def _make_inpaint(self): if not self.generators.get('inpaint'): - from ldm.dream.generator.inpaint import Inpaint + from ldm.invoke.generator.inpaint import Inpaint self.generators['inpaint'] = Inpaint(self.model, self.precision) return self.generators['inpaint'] @@ -784,7 +761,7 @@ class Generate: print(msg) - # Be warned: config is the path to the model config file, not the dream conf file! + # Be warned: config is the path to the model config file, not the invoke conf file! # Also note that we can get config and weights from self, so why do we need to # pass them as args? def _load_model_from_config(self, config, weights): @@ -920,6 +897,17 @@ class Generate: colored += 1 return colored == 0 + def _transparency_check_and_warning(self,image, mask): + if not mask: + print( + '>> Initial image has transparent areas. Will inpaint in these regions.') + if self._check_for_erasure(image): + print( + '>> WARNING: Colors underneath the transparent region seem to have been erased.\n', + '>> Inpainting will be suboptimal. Please preserve the colors when making\n', + '>> a transparency mask, or provide mask explicitly using --init_mask (-M).' + ) + def _squeeze_image(self, image): x, y, resize_needed = self._resolution_check(image.width, image.height) if resize_needed: diff --git a/ldm/dream/args.py b/ldm/invoke/args.py similarity index 97% rename from ldm/dream/args.py rename to ldm/invoke/args.py index 2063286122..09073679c0 100644 --- a/ldm/dream/args.py +++ b/ldm/invoke/args.py @@ -1,7 +1,7 @@ """Helper class for dealing with image generation arguments. The Args class parses both the command line (shell) arguments, as well as the -command string passed at the dream> prompt. It serves as the definitive repository +command string passed at the invoke> prompt. It serves as the definitive repository of all the arguments used by Generate and their default values, and implements the preliminary metadata standards discussed here: @@ -19,7 +19,7 @@ To use: print('oops') sys.exit(-1) - # read in a command passed to the dream> prompt: + # read in a command passed to the invoke> prompt: opts = opt.parse_cmd('do androids dream of electric sheep? -H256 -W1024 -n4') # The Args object acts like a namespace object @@ -64,7 +64,7 @@ To generate a dict representing RFC266 metadata: This will generate an RFC266 dictionary that can then be turned into a JSON and written to the PNG file. The optional seeds, weights, model_hash and postprocesser arguments are not available to the opt object and so must be -provided externally. See how dream.py does it. +provided externally. See how invoke.py does it. Note that this function was originally called format_metadata() and a wrapper is provided that issues a deprecation notice. @@ -91,8 +91,8 @@ import re import copy import base64 import functools -import ldm.dream.pngwriter -from ldm.dream.conditioning import split_weighted_subprompts +import ldm.invoke.pngwriter +from ldm.invoke.conditioning import split_weighted_subprompts SAMPLER_CHOICES = [ 'ddim', @@ -151,7 +151,7 @@ class Args(object): ''' Initialize new Args class. It takes two optional arguments, an argparse parser for switches given on the shell command line, and an argparse - parser for switches given on the dream> CLI line. If one or both are + parser for switches given on the invoke> CLI line. If one or both are missing, it creates appropriate parsers internally. ''' self._arg_parser = arg_parser or self._create_arg_parser() @@ -168,7 +168,7 @@ class Args(object): return None def parse_cmd(self,cmd_string): - '''Parse a dream>-style command string ''' + '''Parse a invoke>-style command string ''' command = cmd_string.replace("'", "\\'") try: elements = shlex.split(command) @@ -269,7 +269,7 @@ class Args(object): if a['with_variations']: formatted_variations = ','.join(f'{seed}:{weight}' for seed, weight in (a["with_variations"])) switches.append(f'-V {formatted_variations}') - if 'variations' in a: + if 'variations' in a and len(a['variations'])>0: switches.append(f'-V {a["variations"]}') return ' '.join(switches) @@ -509,23 +509,23 @@ class Args(object): ) return parser - # This creates the parser that processes commands on the dream> command line + # This creates the parser that processes commands on the invoke> command line def _create_dream_cmd_parser(self): parser = PagingArgumentParser( formatter_class=ArgFormatter, description= """ *Image generation:* - dream> a fantastic alien landscape -W576 -H512 -s60 -n4 + invoke> a fantastic alien landscape -W576 -H512 -s60 -n4 *postprocessing* !fix applies upscaling/facefixing to a previously-generated image. - dream> !fix 0000045.4829112.png -G1 -U4 -ft codeformer + invoke> !fix 0000045.4829112.png -G1 -U4 -ft codeformer *History manipulation* !fetch retrieves the command used to generate an earlier image. - dream> !fetch 0000015.8929913.png - dream> a fantastic alien landscape -W 576 -H 512 -s 60 -A plms -C 7.5 + invoke> !fetch 0000015.8929913.png + invoke> a fantastic alien landscape -W 576 -H 512 -s 60 -A plms -C 7.5 !history lists all the commands issued during the current session. @@ -842,7 +842,7 @@ def metadata_from_png(png_file_path) -> Args: an Args object containing the image metadata. Note that this returns a single Args object, not multiple. ''' - meta = ldm.dream.pngwriter.retrieve_metadata(png_file_path) + meta = ldm.invoke.pngwriter.retrieve_metadata(png_file_path) if 'sd-metadata' in meta and len(meta['sd-metadata'])>0 : return metadata_loads(meta)[0] else: diff --git a/ldm/dream/conditioning.py b/ldm/invoke/conditioning.py similarity index 100% rename from ldm/dream/conditioning.py rename to ldm/invoke/conditioning.py diff --git a/ldm/dream/devices.py b/ldm/invoke/devices.py similarity index 100% rename from ldm/dream/devices.py rename to ldm/invoke/devices.py diff --git a/ldm/invoke/generator/__init__.py b/ldm/invoke/generator/__init__.py new file mode 100644 index 0000000000..2fa5573c84 --- /dev/null +++ b/ldm/invoke/generator/__init__.py @@ -0,0 +1,4 @@ +''' +Initialization file for the ldm.invoke.generator package +''' +from .base import Generator diff --git a/ldm/dream/generator/base.py b/ldm/invoke/generator/base.py similarity index 97% rename from ldm/dream/generator/base.py rename to ldm/invoke/generator/base.py index ae1e6af555..2aa0caf5f9 100644 --- a/ldm/dream/generator/base.py +++ b/ldm/invoke/generator/base.py @@ -1,5 +1,5 @@ ''' -Base class for ldm.dream.generator.* +Base class for ldm.invoke.generator.* including img2img, txt2img, and inpaint ''' import torch @@ -9,7 +9,7 @@ from tqdm import tqdm, trange from PIL import Image from einops import rearrange, repeat from pytorch_lightning import seed_everything -from ldm.dream.devices import choose_autocast +from ldm.invoke.devices import choose_autocast from ldm.util import rand_perlin_2d downsampling = 8 @@ -21,6 +21,8 @@ class Generator(): self.seed = None self.latent_channels = model.channels self.downsampling_factor = downsampling # BUG: should come from model or config + self.perlin = 0.0 + self.threshold = 0 self.variation_amount = 0 self.with_variations = [] diff --git a/ldm/dream/generator/embiggen.py b/ldm/invoke/generator/embiggen.py similarity index 98% rename from ldm/dream/generator/embiggen.py rename to ldm/invoke/generator/embiggen.py index 079b7dd9aa..53fbde68cf 100644 --- a/ldm/dream/generator/embiggen.py +++ b/ldm/invoke/generator/embiggen.py @@ -1,15 +1,15 @@ ''' -ldm.dream.generator.embiggen descends from ldm.dream.generator -and generates with ldm.dream.generator.img2img +ldm.invoke.generator.embiggen descends from ldm.invoke.generator +and generates with ldm.invoke.generator.img2img ''' import torch import numpy as np from tqdm import trange from PIL import Image -from ldm.dream.generator.base import Generator -from ldm.dream.generator.img2img import Img2Img -from ldm.dream.devices import choose_autocast +from ldm.invoke.generator.base import Generator +from ldm.invoke.generator.img2img import Img2Img +from ldm.invoke.devices import choose_autocast from ldm.models.diffusion.ddim import DDIMSampler class Embiggen(Generator): @@ -107,7 +107,7 @@ class Embiggen(Generator): initsuperwidth = round(initsuperwidth*embiggen[0]) initsuperheight = round(initsuperheight*embiggen[0]) if embiggen[1] > 0: # No point in ESRGAN upscaling if strength is set zero - from ldm.dream.restoration.realesrgan import ESRGAN + from ldm.invoke.restoration.realesrgan import ESRGAN esrgan = ESRGAN() print( f'>> ESRGAN upscaling init image prior to cutting with Embiggen with strength {embiggen[1]}') diff --git a/ldm/dream/generator/img2img.py b/ldm/invoke/generator/img2img.py similarity index 93% rename from ldm/dream/generator/img2img.py rename to ldm/invoke/generator/img2img.py index 27425a2b6b..7fde1a94cf 100644 --- a/ldm/dream/generator/img2img.py +++ b/ldm/invoke/generator/img2img.py @@ -1,11 +1,11 @@ ''' -ldm.dream.generator.img2img descends from ldm.dream.generator +ldm.invoke.generator.img2img descends from ldm.invoke.generator ''' import torch import numpy as np -from ldm.dream.devices import choose_autocast -from ldm.dream.generator.base import Generator +from ldm.invoke.devices import choose_autocast +from ldm.invoke.generator.base import Generator from ldm.models.diffusion.ddim import DDIMSampler class Img2Img(Generator): diff --git a/ldm/dream/generator/inpaint.py b/ldm/invoke/generator/inpaint.py similarity index 89% rename from ldm/dream/generator/inpaint.py rename to ldm/invoke/generator/inpaint.py index 620210b118..3ab1456564 100644 --- a/ldm/dream/generator/inpaint.py +++ b/ldm/invoke/generator/inpaint.py @@ -1,12 +1,12 @@ ''' -ldm.dream.generator.inpaint descends from ldm.dream.generator +ldm.invoke.generator.inpaint descends from ldm.invoke.generator ''' import torch import numpy as np from einops import rearrange, repeat -from ldm.dream.devices import choose_autocast -from ldm.dream.generator.img2img import Img2Img +from ldm.invoke.devices import choose_autocast +from ldm.invoke.generator.img2img import Img2Img from ldm.models.diffusion.ddim import DDIMSampler from ldm.models.diffusion.ksampler import KSampler @@ -27,7 +27,7 @@ class Inpaint(Img2Img): # klms samplers not supported yet, so ignore previous sampler if isinstance(sampler,KSampler): print( - f">> sampler '{sampler.__class__.__name__}' is not yet supported for inpainting, using DDIMSampler instead." + f">> Using recommended DDIM sampler for inpainting." ) sampler = DDIMSampler(self.model, device=self.model.device) diff --git a/ldm/dream/generator/txt2img.py b/ldm/invoke/generator/txt2img.py similarity index 96% rename from ldm/dream/generator/txt2img.py rename to ldm/invoke/generator/txt2img.py index b702edc92d..3502de9be9 100644 --- a/ldm/dream/generator/txt2img.py +++ b/ldm/invoke/generator/txt2img.py @@ -1,10 +1,10 @@ ''' -ldm.dream.generator.txt2img inherits from ldm.dream.generator +ldm.invoke.generator.txt2img inherits from ldm.invoke.generator ''' import torch import numpy as np -from ldm.dream.generator.base import Generator +from ldm.invoke.generator.base import Generator class Txt2Img(Generator): def __init__(self, model, precision): diff --git a/ldm/dream/generator/txt2img2img.py b/ldm/invoke/generator/txt2img2img.py similarity index 89% rename from ldm/dream/generator/txt2img2img.py rename to ldm/invoke/generator/txt2img2img.py index d6c0cdf168..945ebadd90 100644 --- a/ldm/dream/generator/txt2img2img.py +++ b/ldm/invoke/generator/txt2img2img.py @@ -1,11 +1,11 @@ ''' -ldm.dream.generator.txt2img inherits from ldm.dream.generator +ldm.invoke.generator.txt2img inherits from ldm.invoke.generator ''' import torch import numpy as np import math -from ldm.dream.generator.base import Generator +from ldm.invoke.generator.base import Generator from ldm.models.diffusion.ddim import DDIMSampler @@ -64,7 +64,7 @@ class Txt2Img2Img(Generator): ) print( - f"\n>> Interpolating from {init_width}x{init_height} to {width}x{height}" + f"\n>> Interpolating from {init_width}x{init_height} to {width}x{height} using DDIM sampling" ) # resizing @@ -75,17 +75,19 @@ class Txt2Img2Img(Generator): ) t_enc = int(strength * steps) + ddim_sampler = DDIMSampler(self.model, device=self.model.device) + ddim_sampler.make_schedule( + ddim_num_steps=steps, ddim_eta=ddim_eta, verbose=False + ) - x = self.get_noise(width,height,False) - - z_enc = sampler.stochastic_encode( + z_enc = ddim_sampler.stochastic_encode( samples, torch.tensor([t_enc]).to(self.model.device), - noise=x + noise=self.get_noise(width,height,False) ) # decode it - samples = sampler.decode( + samples = ddim_sampler.decode( z_enc, c, t_enc, diff --git a/ldm/dream/image_util.py b/ldm/invoke/image_util.py similarity index 100% rename from ldm/dream/image_util.py rename to ldm/invoke/image_util.py diff --git a/ldm/dream/log.py b/ldm/invoke/log.py similarity index 100% rename from ldm/dream/log.py rename to ldm/invoke/log.py diff --git a/ldm/dream/pngwriter.py b/ldm/invoke/pngwriter.py similarity index 100% rename from ldm/dream/pngwriter.py rename to ldm/invoke/pngwriter.py diff --git a/ldm/dream/readline.py b/ldm/invoke/readline.py similarity index 97% rename from ldm/dream/readline.py rename to ldm/invoke/readline.py index 037f739478..73664ef82c 100644 --- a/ldm/dream/readline.py +++ b/ldm/invoke/readline.py @@ -1,17 +1,17 @@ """ -Readline helper functions for dream.py (linux and mac only). +Readline helper functions for invoke.py. You may import the global singleton `completer` to get access to the completer object itself. This is useful when you want to autocomplete seeds: - from ldm.dream.readline import completer + from ldm.invoke.readline import completer completer.add_seed(18247566) completer.add_seed(9281839) """ import os import re import atexit -from ldm.dream.args import Args +from ldm.invoke.args import Args # ---------------readline utilities--------------------- try: @@ -20,7 +20,7 @@ try: except (ImportError,ModuleNotFoundError): readline_available = False -IMG_EXTENSIONS = ('.png','.jpg','.jpeg') +IMG_EXTENSIONS = ('.png','.jpg','.jpeg','.PNG','.JPG','.JPEG','.gif','.GIF') COMMANDS = ( '--steps','-s', '--seed','-S', @@ -74,7 +74,7 @@ class Completer(object): def complete(self, text, state): ''' - Completes dream command line. + Completes invoke command line. BUG: it doesn't correctly complete files that have spaces in the name. ''' buffer = readline.get_line_buffer() @@ -287,7 +287,7 @@ def get_completer(opt:Args)->Completer: readline.parse_and_bind('set skip-completed-text on') readline.parse_and_bind('set show-all-if-ambiguous on') - histfile = os.path.join(os.path.expanduser(opt.outdir), '.dream_history') + histfile = os.path.join(os.path.expanduser(opt.outdir), '.invoke_history') try: readline.read_history_file(histfile) readline.set_history_length(1000) diff --git a/ldm/invoke/restoration/__init__.py b/ldm/invoke/restoration/__init__.py new file mode 100644 index 0000000000..e784ea52b8 --- /dev/null +++ b/ldm/invoke/restoration/__init__.py @@ -0,0 +1,4 @@ +''' +Initialization file for the ldm.invoke.restoration package +''' +from .base import Restoration diff --git a/ldm/dream/restoration/base.py b/ldm/invoke/restoration/base.py similarity index 85% rename from ldm/dream/restoration/base.py rename to ldm/invoke/restoration/base.py index 2605c4ac4b..647b49e77e 100644 --- a/ldm/dream/restoration/base.py +++ b/ldm/invoke/restoration/base.py @@ -23,16 +23,16 @@ class Restoration(): # Face Restore Models def load_gfpgan(self, gfpgan_dir, gfpgan_model_path): - from ldm.dream.restoration.gfpgan import GFPGAN + from ldm.invoke.restoration.gfpgan import GFPGAN return GFPGAN(gfpgan_dir, gfpgan_model_path) def load_codeformer(self): - from ldm.dream.restoration.codeformer import CodeFormerRestoration + from ldm.invoke.restoration.codeformer import CodeFormerRestoration return CodeFormerRestoration() # Upscale Models def load_esrgan(self, esrgan_bg_tile=400): - from ldm.dream.restoration.realesrgan import ESRGAN + from ldm.invoke.restoration.realesrgan import ESRGAN esrgan = ESRGAN(esrgan_bg_tile) print('>> ESRGAN Initialized') return esrgan; diff --git a/ldm/dream/restoration/codeformer.py b/ldm/invoke/restoration/codeformer.py similarity index 93% rename from ldm/dream/restoration/codeformer.py rename to ldm/invoke/restoration/codeformer.py index 78648865aa..0d13ae0a36 100644 --- a/ldm/dream/restoration/codeformer.py +++ b/ldm/invoke/restoration/codeformer.py @@ -8,7 +8,7 @@ pretrained_model_url = 'https://github.com/sczhou/CodeFormer/releases/download/v class CodeFormerRestoration(): def __init__(self, - codeformer_dir='ldm/dream/restoration/codeformer', + codeformer_dir='ldm/invoke/restoration/codeformer', codeformer_model_path='weights/codeformer.pth') -> None: self.model_path = os.path.join(codeformer_dir, codeformer_model_path) self.codeformer_model_exists = os.path.isfile(self.model_path) @@ -27,7 +27,7 @@ class CodeFormerRestoration(): from basicsr.utils.download_util import load_file_from_url from basicsr.utils import img2tensor, tensor2img from facexlib.utils.face_restoration_helper import FaceRestoreHelper - from ldm.dream.restoration.codeformer_arch import CodeFormer + from ldm.invoke.restoration.codeformer_arch import CodeFormer from torchvision.transforms.functional import normalize from PIL import Image @@ -35,7 +35,7 @@ class CodeFormerRestoration(): cf = cf_class(dim_embd=512, codebook_size=1024, n_head=8, n_layers=9, connect_list=['32', '64', '128', '256']).to(device) - checkpoint_path = load_file_from_url(url=pretrained_model_url, model_dir=os.path.abspath('ldm/dream/restoration/codeformer/weights'), progress=True) + checkpoint_path = load_file_from_url(url=pretrained_model_url, model_dir=os.path.abspath('ldm/invoke/restoration/codeformer/weights'), progress=True) checkpoint = torch.load(checkpoint_path)['params_ema'] cf.load_state_dict(checkpoint) cf.eval() diff --git a/ldm/dream/restoration/codeformer/weights/README b/ldm/invoke/restoration/codeformer/weights/README similarity index 100% rename from ldm/dream/restoration/codeformer/weights/README rename to ldm/invoke/restoration/codeformer/weights/README diff --git a/ldm/dream/restoration/codeformer_arch.py b/ldm/invoke/restoration/codeformer_arch.py similarity index 99% rename from ldm/dream/restoration/codeformer_arch.py rename to ldm/invoke/restoration/codeformer_arch.py index cf6c5c91be..b23872b18f 100644 --- a/ldm/dream/restoration/codeformer_arch.py +++ b/ldm/invoke/restoration/codeformer_arch.py @@ -5,7 +5,7 @@ from torch import nn, Tensor import torch.nn.functional as F from typing import Optional, List -from ldm.dream.restoration.vqgan_arch import * +from ldm.invoke.restoration.vqgan_arch import * from basicsr.utils import get_root_logger from basicsr.utils.registry import ARCH_REGISTRY diff --git a/ldm/dream/restoration/gfpgan.py b/ldm/invoke/restoration/gfpgan.py similarity index 100% rename from ldm/dream/restoration/gfpgan.py rename to ldm/invoke/restoration/gfpgan.py diff --git a/ldm/dream/restoration/outcrop.py b/ldm/invoke/restoration/outcrop.py similarity index 100% rename from ldm/dream/restoration/outcrop.py rename to ldm/invoke/restoration/outcrop.py diff --git a/ldm/dream/restoration/outpaint.py b/ldm/invoke/restoration/outpaint.py similarity index 98% rename from ldm/dream/restoration/outpaint.py rename to ldm/invoke/restoration/outpaint.py index 525e158779..e75b48221f 100644 --- a/ldm/dream/restoration/outpaint.py +++ b/ldm/invoke/restoration/outpaint.py @@ -13,8 +13,6 @@ class Outpaint(object): seed = old_opt.seed prompt = old_opt.prompt - print(f'DEBUG: old seed={seed}, old prompt = {prompt}') - def wrapped_callback(img,seed,**kwargs): image_callback(img,seed,use_prefix=prefix,**kwargs) diff --git a/ldm/dream/restoration/realesrgan.py b/ldm/invoke/restoration/realesrgan.py similarity index 100% rename from ldm/dream/restoration/realesrgan.py rename to ldm/invoke/restoration/realesrgan.py diff --git a/ldm/dream/restoration/vqgan_arch.py b/ldm/invoke/restoration/vqgan_arch.py similarity index 100% rename from ldm/dream/restoration/vqgan_arch.py rename to ldm/invoke/restoration/vqgan_arch.py diff --git a/ldm/dream/server.py b/ldm/invoke/server.py similarity index 99% rename from ldm/dream/server.py rename to ldm/invoke/server.py index 46002a9b27..4eef1ddd56 100644 --- a/ldm/dream/server.py +++ b/ldm/invoke/server.py @@ -4,9 +4,9 @@ import copy import base64 import mimetypes import os -from ldm.dream.args import Args, metadata_dumps +from ldm.invoke.args import Args, metadata_dumps from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer -from ldm.dream.pngwriter import PngWriter +from ldm.invoke.pngwriter import PngWriter from threading import Event def build_opt(post_data, seed, gfpgan_model_exists): diff --git a/ldm/models/diffusion/ddim.py b/ldm/models/diffusion/ddim.py index 7aca381c74..f5dada8627 100644 --- a/ldm/models/diffusion/ddim.py +++ b/ldm/models/diffusion/ddim.py @@ -4,7 +4,7 @@ import torch import numpy as np from tqdm import tqdm from functools import partial -from ldm.dream.devices import choose_torch_device +from ldm.invoke.devices import choose_torch_device from ldm.models.diffusion.sampler import Sampler from ldm.modules.diffusionmodules.util import noise_like diff --git a/ldm/models/diffusion/ksampler.py b/ldm/models/diffusion/ksampler.py index 3d84ba0c9a..e763b202f9 100644 --- a/ldm/models/diffusion/ksampler.py +++ b/ldm/models/diffusion/ksampler.py @@ -2,7 +2,7 @@ import k_diffusion as K import torch import torch.nn as nn -from ldm.dream.devices import choose_torch_device +from ldm.invoke.devices import choose_torch_device from ldm.models.diffusion.sampler import Sampler from ldm.util import rand_perlin_2d from ldm.modules.diffusionmodules.util import ( @@ -57,8 +57,9 @@ class KSampler(Sampler): schedule, steps=model.num_timesteps, ) - self.ds = None - self.s_in = None + self.sigmas = None + self.ds = None + self.s_in = None def forward(self, x, sigma, uncond, cond, cond_scale): x_in = torch.cat([x] * 2) @@ -190,7 +191,7 @@ class KSampler(Sampler): 'uncond': unconditional_conditioning, 'cond_scale': unconditional_guidance_scale, } - print(f'>> Sampling with k_{self.schedule}') + print(f'>> Sampling with k_{self.schedule} starting at step {len(self.sigmas)-S-1} of {len(self.sigmas)-1} ({S} new sampling steps)') return ( K.sampling.__dict__[f'sample_{self.schedule}']( model_wrap_cfg, x, sigmas, extra_args=extra_args, @@ -199,6 +200,8 @@ class KSampler(Sampler): None, ) + # this code will support inpainting if and when ksampler API modified or + # a workaround is found. @torch.no_grad() def p_sample( self, diff --git a/ldm/models/diffusion/plms.py b/ldm/models/diffusion/plms.py index 870d8739ec..9e722eb932 100644 --- a/ldm/models/diffusion/plms.py +++ b/ldm/models/diffusion/plms.py @@ -4,7 +4,7 @@ import torch import numpy as np from tqdm import tqdm from functools import partial -from ldm.dream.devices import choose_torch_device +from ldm.invoke.devices import choose_torch_device from ldm.models.diffusion.sampler import Sampler from ldm.modules.diffusionmodules.util import noise_like diff --git a/ldm/models/diffusion/sampler.py b/ldm/models/diffusion/sampler.py index 3056cbb6b8..8b19f894e5 100644 --- a/ldm/models/diffusion/sampler.py +++ b/ldm/models/diffusion/sampler.py @@ -8,7 +8,7 @@ import torch import numpy as np from tqdm import tqdm from functools import partial -from ldm.dream.devices import choose_torch_device +from ldm.invoke.devices import choose_torch_device from ldm.modules.diffusionmodules.util import ( make_ddim_sampling_parameters, diff --git a/ldm/modules/encoders/modules.py b/ldm/modules/encoders/modules.py index 3357ee6c9e..426fccced3 100644 --- a/ldm/modules/encoders/modules.py +++ b/ldm/modules/encoders/modules.py @@ -5,7 +5,7 @@ import clip from einops import rearrange, repeat from transformers import CLIPTokenizer, CLIPTextModel import kornia -from ldm.dream.devices import choose_torch_device +from ldm.invoke.devices import choose_torch_device from ldm.modules.x_transformer import ( Encoder, diff --git a/notebooks/notebook_helpers.py b/notebooks/notebook_helpers.py index 2c4fe70d62..663b212ac5 100644 --- a/notebooks/notebook_helpers.py +++ b/notebooks/notebook_helpers.py @@ -14,7 +14,7 @@ from ldm.models.diffusion.ddim import DDIMSampler from ldm.util import ismap import time from omegaconf import OmegaConf -from ldm.dream.devices import choose_torch_device +from ldm.invoke.devices import choose_torch_device def download_models(mode): diff --git a/requirements-linux-arm64.txt b/requirements-linux-arm64.txt index 10329e47d3..56da2b94c9 100644 --- a/requirements-linux-arm64.txt +++ b/requirements-linux-arm64.txt @@ -20,6 +20,6 @@ torchmetrics==0.6.0 transformers==4.19.2 -e git+https://github.com/openai/CLIP.git@main#egg=clip -e git+https://github.com/CompVis/taming-transformers.git@master#egg=taming-transformers -git+https://github.com/lstein/k-diffusion.git@master#egg=k-diffusion --e git+https://github.com/lstein/GFPGAN@fix-dark-cast-images#egg=gfpgan --e . \ No newline at end of file +-e git+https://github.com/lstein/k-diffusion.git@master#egg=k-diffusion +-e git+https://github.com/TencentARC/GFPGAN.git#egg=gfpgan +-e . diff --git a/requirements-mac-MPS-CPU.txt b/requirements-mac-MPS-CPU.txt index a785a61372..3ea189c480 100644 --- a/requirements-mac-MPS-CPU.txt +++ b/requirements-mac-MPS-CPU.txt @@ -1,8 +1,5 @@ -r requirements.txt ---pre ---extra-index-url https://download.pytorch.org/whl/nightly/cpu --trusted-host https://download.pytorch.org - protobuf==3.19.4 torch torchvision diff --git a/requirements.txt b/requirements.txt index 0260cf32c7..7041dec3ce 100644 --- a/requirements.txt +++ b/requirements.txt @@ -31,6 +31,7 @@ flaskwebgui==0.3.7 send2trash dependency_injector==4.40.0 eventlet +realesrgan git+https://github.com/openai/CLIP.git@main#egg=clip git+https://github.com/Birch-san/k-diffusion.git@mps#egg=k-diffusion -git+https://github.com/lstein/GFPGAN@fix-dark-cast-images#egg=gfpgan +git+https://github.com/TencentARC/GFPGAN.git#egg=gfpgan diff --git a/scripts/dream.py b/scripts/dream.py index cd0d7c33b4..05cd9c9aeb 100644 --- a/scripts/dream.py +++ b/scripts/dream.py @@ -1,571 +1,12 @@ #!/usr/bin/env python3 # Copyright (c) 2022 Lincoln D. Stein (https://github.com/lstein) -import os -import re import sys -import shlex -import copy -import warnings -import time -import traceback -sys.path.append('.') # corrects a weird problem on Macs -from ldm.dream.readline import get_completer -from ldm.dream.args import Args, metadata_dumps, metadata_from_png, dream_cmd_from_png -from ldm.dream.pngwriter import PngWriter, retrieve_metadata, write_metadata -from ldm.dream.image_util import make_grid -from ldm.dream.log import write_log -from omegaconf import OmegaConf -from backend.invoke_ai_web_server import InvokeAIWebServer +import os.path +script_path = sys.argv[0] +script_args = sys.argv[1:] +script_dir,script_name = os.path.split(script_path) +script_dest = os.path.join(script_dir,'invoke.py') +os.execlp('python3','python3',script_dest,*script_args) -def main(): - """Initialize command-line parsers and the diffusion model""" - opt = Args() - args = opt.parse_args() - if not args: - sys.exit(-1) - - if args.laion400m: - print('--laion400m flag has been deprecated. Please use --model laion400m instead.') - sys.exit(-1) - if args.weights: - print('--weights argument has been deprecated. Please edit ./configs/models.yaml, and select the weights using --model instead.') - sys.exit(-1) - - print('* Initializing, be patient...\n') - from ldm.generate import Generate - - # these two lines prevent a horrible warning message from appearing - # when the frozen CLIP tokenizer is imported - import transformers - transformers.logging.set_verbosity_error() - - # Loading Face Restoration and ESRGAN Modules - try: - gfpgan, codeformer, esrgan = None, None, None - if opt.restore or opt.esrgan: - from ldm.dream.restoration import Restoration - restoration = Restoration() - if opt.restore: - gfpgan, codeformer = restoration.load_face_restore_models(opt.gfpgan_dir, opt.gfpgan_model_path) - else: - print('>> Face restoration disabled') - if opt.esrgan: - esrgan = restoration.load_esrgan(opt.esrgan_bg_tile) - else: - print('>> Upscaling disabled') - else: - print('>> Face restoration and upscaling disabled') - except (ModuleNotFoundError, ImportError): - print(traceback.format_exc(), file=sys.stderr) - print('>> You may need to install the ESRGAN and/or GFPGAN modules') - - # creating a simple text2image object with a handful of - # defaults passed on the command line. - # additional parameters will be added (or overriden) during - # the user input loop - try: - gen = Generate( - conf = opt.conf, - model = opt.model, - sampler_name = opt.sampler_name, - embedding_path = opt.embedding_path, - full_precision = opt.full_precision, - precision = opt.precision, - gfpgan=gfpgan, - codeformer=codeformer, - esrgan=esrgan - ) - except (FileNotFoundError, IOError, KeyError) as e: - print(f'{e}. Aborting.') - sys.exit(-1) - - # make sure the output directory exists - if not os.path.exists(opt.outdir): - os.makedirs(opt.outdir) - - # load the infile as a list of lines - infile = None - if opt.infile: - try: - if os.path.isfile(opt.infile): - infile = open(opt.infile, 'r', encoding='utf-8') - elif opt.infile == '-': # stdin - infile = sys.stdin - else: - raise FileNotFoundError(f'{opt.infile} not found.') - except (FileNotFoundError, IOError) as e: - print(f'{e}. Aborting.') - sys.exit(-1) - - if opt.seamless: - print(">> changed to seamless tiling mode") - - # preload the model - gen.load_model() - #set additional option - gen.free_gpu_mem = opt.free_gpu_mem - - # web server loops forever - if opt.web or opt.gui: - invoke_ai_web_server_loop(gen, gfpgan, codeformer, esrgan) - sys.exit(0) - - if not infile: - print( - "\n* Initialization done! Awaiting your command (-h for help, 'q' to quit)" - ) - - main_loop(gen, opt, infile) - -# TODO: main_loop() has gotten busy. Needs to be refactored. -def main_loop(gen, opt, infile): - """prompt/read/execute loop""" - done = False - path_filter = re.compile(r'[<>:"/\\|?*]') - last_results = list() - model_config = OmegaConf.load(opt.conf)[opt.model] - - # The readline completer reads history from the .dream_history file located in the - # output directory specified at the time of script launch. We do not currently support - # changing the history file midstream when the output directory is changed. - completer = get_completer(opt) - output_cntr = completer.get_current_history_length()+1 - - # os.pathconf is not available on Windows - if hasattr(os, 'pathconf'): - path_max = os.pathconf(opt.outdir, 'PC_PATH_MAX') - name_max = os.pathconf(opt.outdir, 'PC_NAME_MAX') - else: - path_max = 260 - name_max = 255 - - while not done: - operation = 'generate' # default operation, alternative is 'postprocess' - - if completer: - completer.set_default_dir(opt.outdir) - - try: - command = get_next_command(infile) - except EOFError: - done = True - continue - - # skip empty lines - if not command.strip(): - continue - - if command.startswith(('#', '//')): - continue - - if len(command.strip()) == 1 and command.startswith('q'): - done = True - break - - if command.startswith('!'): - subcommand = command[1:] - - if subcommand.startswith('dream'): # in case a stored prompt still contains the !dream command - command = command.replace('!dream ','',1) - - elif subcommand.startswith('fix'): - command = command.replace('!fix ','',1) - operation = 'postprocess' - - elif subcommand.startswith('fetch'): - file_path = command.replace('!fetch ','',1) - retrieve_dream_command(opt,file_path,completer) - continue - - elif subcommand.startswith('history'): - completer.show_history() - continue - - elif subcommand.startswith('search'): - search_str = command.replace('!search ','',1) - completer.show_history(search_str) - continue - - elif subcommand.startswith('clear'): - completer.clear_history() - continue - - elif re.match('^(\d+)',subcommand): - command_no = re.match('^(\d+)',subcommand).groups()[0] - command = completer.get_line(int(command_no)) - completer.set_line(command) - continue - - else: # not a recognized subcommand, so give the --help text - command = '-h' - - if opt.parse_cmd(command) is None: - continue - - if opt.init_img: - try: - if not opt.prompt: - oldargs = metadata_from_png(opt.init_img) - opt.prompt = oldargs.prompt - print(f'>> Retrieved old prompt "{opt.prompt}" from {opt.init_img}') - except (OSError, AttributeError, KeyError): - pass - - if len(opt.prompt) == 0: - print('\nTry again with a prompt!') - continue - - # width and height are set by model if not specified - if not opt.width: - opt.width = model_config.width - if not opt.height: - opt.height = model_config.height - - # retrieve previous value of init image if requested - if opt.init_img is not None and re.match('^-\\d+$', opt.init_img): - try: - opt.init_img = last_results[int(opt.init_img)][0] - print(f'>> Reusing previous image {opt.init_img}') - except IndexError: - print( - f'>> No previous initial image at position {opt.init_img} found') - opt.init_img = None - continue - - # try to relativize pathnames - for attr in ('init_img','init_mask','init_color','embedding_path'): - if getattr(opt,attr) and not os.path.exists(getattr(opt,attr)): - basename = getattr(opt,attr) - path = os.path.join(opt.outdir,basename) - setattr(opt,attr,path) - - # retrieve previous value of seed if requested - if opt.seed is not None and opt.seed < 0: - try: - opt.seed = last_results[opt.seed][1] - print(f'>> Reusing previous seed {opt.seed}') - except IndexError: - print(f'>> No previous seed at position {opt.seed} found') - opt.seed = None - continue - - if opt.strength is None: - opt.strength = 0.75 if opt.out_direction is None else 0.83 - - if opt.with_variations is not None: - opt.with_variations = split_variations(opt.with_variations) - - if opt.prompt_as_dir: - # sanitize the prompt to a valid folder name - subdir = path_filter.sub('_', opt.prompt)[:name_max].rstrip(' .') - - # truncate path to maximum allowed length - # 39 is the length of '######.##########.##########-##.png', plus two separators and a NUL - subdir = subdir[:(path_max - 39 - len(os.path.abspath(opt.outdir)))] - current_outdir = os.path.join(opt.outdir, subdir) - - print('Writing files to directory: "' + current_outdir + '"') - - # make sure the output directory exists - if not os.path.exists(current_outdir): - os.makedirs(current_outdir) - else: - if not os.path.exists(opt.outdir): - os.makedirs(opt.outdir) - current_outdir = opt.outdir - - # Here is where the images are actually generated! - last_results = [] - try: - file_writer = PngWriter(current_outdir) - results = [] # list of filename, prompt pairs - grid_images = dict() # seed -> Image, only used if `opt.grid` - prior_variations = opt.with_variations or [] - prefix = file_writer.unique_prefix() - - def image_writer(image, seed, upscaled=False, first_seed=None, use_prefix=None): - # note the seed is the seed of the current image - # the first_seed is the original seed that noise is added to - # when the -v switch is used to generate variations - nonlocal prior_variations - nonlocal prefix - if use_prefix is not None: - prefix = use_prefix - - path = None - if opt.grid: - grid_images[seed] = image - else: - postprocessed = upscaled if upscaled else operation=='postprocess' - filename, formatted_dream_prompt = prepare_image_metadata( - opt, - prefix, - seed, - operation, - prior_variations, - postprocessed, - first_seed - ) - path = file_writer.save_image_and_prompt_to_png( - image = image, - dream_prompt = formatted_dream_prompt, - metadata = metadata_dumps( - opt, - seeds = [seed if opt.variation_amount==0 and len(prior_variations)==0 else first_seed], - model_hash = gen.model_hash, - ), - name = filename, - ) - - # update rfc metadata - if operation == 'postprocess': - tool = re.match('postprocess:(\w+)',opt.last_operation).groups()[0] - add_postprocessing_to_metadata( - opt, - opt.prompt, - filename, - tool, - formatted_dream_prompt, - ) - - if (not postprocessed) or opt.save_original: - # only append to results if we didn't overwrite an earlier output - results.append([path, formatted_dream_prompt]) - - # so that the seed autocompletes (on linux|mac when -S or --seed specified - if completer: - completer.add_seed(seed) - completer.add_seed(first_seed) - last_results.append([path, seed]) - - if operation == 'generate': - catch_ctrl_c = infile is None # if running interactively, we catch keyboard interrupts - opt.last_operation='generate' - gen.prompt2image( - image_callback=image_writer, - catch_interrupts=catch_ctrl_c, - **vars(opt) - ) - elif operation == 'postprocess': - print(f'>> fixing {opt.prompt}') - opt.last_operation = do_postprocess(gen,opt,image_writer) - - if opt.grid and len(grid_images) > 0: - grid_img = make_grid(list(grid_images.values())) - grid_seeds = list(grid_images.keys()) - first_seed = last_results[0][1] - filename = f'{prefix}.{first_seed}.png' - formatted_dream_prompt = opt.dream_prompt_str(seed=first_seed,grid=True,iterations=len(grid_images)) - formatted_dream_prompt += f' # {grid_seeds}' - metadata = metadata_dumps( - opt, - seeds = grid_seeds, - model_hash = gen.model_hash - ) - path = file_writer.save_image_and_prompt_to_png( - image = grid_img, - dream_prompt = formatted_dream_prompt, - metadata = metadata, - name = filename - ) - results = [[path, formatted_dream_prompt]] - - except AssertionError as e: - print(e) - continue - - except OSError as e: - print(e) - continue - - print('Outputs:') - log_path = os.path.join(current_outdir, 'dream_log') - output_cntr = write_log(results, log_path ,('txt', 'md'), output_cntr) - print() - if operation == 'postprocess': - completer.add_history(f'!fix {command}') - else: - completer.add_history(command) - - print('goodbye!') - -def do_postprocess (gen, opt, callback): - file_path = opt.prompt # treat the prompt as the file pathname - if os.path.dirname(file_path) == '': #basename given - file_path = os.path.join(opt.outdir,file_path) - - tool=None - if opt.gfpgan_strength > 0: - tool = opt.facetool - elif opt.embiggen: - tool = 'embiggen' - elif opt.upscale: - tool = 'upscale' - elif opt.out_direction: - tool = 'outpaint' - elif opt.outcrop: - tool = 'outcrop' - opt.save_original = True # do not overwrite old image! - opt.last_operation = f'postprocess:{tool}' - try: - gen.apply_postprocessor( - image_path = file_path, - tool = tool, - gfpgan_strength = opt.gfpgan_strength, - codeformer_fidelity = opt.codeformer_fidelity, - save_original = opt.save_original, - upscale = opt.upscale, - out_direction = opt.out_direction, - outcrop = opt.outcrop, - callback = callback, - opt = opt, - ) - except OSError: - print(f'** {file_path}: file could not be read') - return - except (KeyError, AttributeError): - print(traceback.format_exc(), file=sys.stderr) - return - return opt.last_operation - -def add_postprocessing_to_metadata(opt,original_file,new_file,tool,command): - original_file = original_file if os.path.exists(original_file) else os.path.join(opt.outdir,original_file) - new_file = new_file if os.path.exists(new_file) else os.path.join(opt.outdir,new_file) - meta = retrieve_metadata(original_file)['sd-metadata'] - img_data = meta['image'] - pp = img_data.get('postprocessing',[]) or [] - pp.append( - { - 'tool':tool, - 'dream_command':command, - } - ) - meta['image']['postprocessing'] = pp - write_metadata(new_file,meta) - -def prepare_image_metadata( - opt, - prefix, - seed, - operation='generate', - prior_variations=[], - postprocessed=False, - first_seed=None -): - - if postprocessed and opt.save_original: - filename = choose_postprocess_name(opt,prefix,seed) - else: - filename = f'{prefix}.{seed}.png' - - if opt.variation_amount > 0: - first_seed = first_seed or seed - this_variation = [[seed, opt.variation_amount]] - opt.with_variations = prior_variations + this_variation - formatted_dream_prompt = opt.dream_prompt_str(seed=first_seed) - elif len(prior_variations) > 0: - formatted_dream_prompt = opt.dream_prompt_str(seed=first_seed) - elif operation == 'postprocess': - formatted_dream_prompt = '!fix '+opt.dream_prompt_str(seed=seed) - else: - formatted_dream_prompt = opt.dream_prompt_str(seed=seed) - return filename,formatted_dream_prompt - -def choose_postprocess_name(opt,prefix,seed) -> str: - match = re.search('postprocess:(\w+)',opt.last_operation) - if match: - modifier = match.group(1) # will look like "gfpgan", "upscale", "outpaint" or "embiggen" - else: - modifier = 'postprocessed' - - counter = 0 - filename = None - available = False - while not available: - if counter == 0: - filename = f'{prefix}.{seed}.{modifier}.png' - else: - filename = f'{prefix}.{seed}.{modifier}-{counter:02d}.png' - available = not os.path.exists(os.path.join(opt.outdir,filename)) - counter += 1 - return filename - -def get_next_command(infile=None) -> str: # command string - if infile is None: - command = input('dream> ') - else: - command = infile.readline() - if not command: - raise EOFError - else: - command = command.strip() - if len(command)>0: - print(f'#{command}') - return command - -def invoke_ai_web_server_loop(gen, gfpgan, codeformer, esrgan): - print('\n* --web was specified, starting web server...') - # Change working directory to the stable-diffusion directory - os.chdir( - os.path.abspath(os.path.join(os.path.dirname(__file__), '..')) - ) - - invoke_ai_web_server = InvokeAIWebServer(generate=gen, gfpgan=gfpgan, codeformer=codeformer, esrgan=esrgan) - - try: - invoke_ai_web_server.run() - except KeyboardInterrupt: - pass - - -def split_variations(variations_string) -> list: - # shotgun parsing, woo - parts = [] - broken = False # python doesn't have labeled loops... - for part in variations_string.split(','): - seed_and_weight = part.split(':') - if len(seed_and_weight) != 2: - print(f'** Could not parse with_variation part "{part}"') - broken = True - break - try: - seed = int(seed_and_weight[0]) - weight = float(seed_and_weight[1]) - except ValueError: - print(f'** Could not parse with_variation part "{part}"') - broken = True - break - parts.append([seed, weight]) - if broken: - return None - elif len(parts) == 0: - return None - else: - return parts - -def retrieve_dream_command(opt,file_path,completer): - ''' - Given a full or partial path to a previously-generated image file, - will retrieve and format the dream command used to generate the image, - and pop it into the readline buffer (linux, Mac), or print out a comment - for cut-and-paste (windows) - ''' - dir,basename = os.path.split(file_path) - if len(dir) == 0: - path = os.path.join(opt.outdir,basename) - else: - path = file_path - try: - cmd = dream_cmd_from_png(path) - except OSError: - print(f'** {path}: file could not be read') - return - except (KeyError, AttributeError): - print(f'** {path}: file has no metadata') - return - completer.set_line(cmd) - -if __name__ == '__main__': - main() diff --git a/scripts/images2prompt.py b/scripts/images2prompt.py index c23eee0f75..70312b1c90 100755 --- a/scripts/images2prompt.py +++ b/scripts/images2prompt.py @@ -1,12 +1,12 @@ #!/usr/bin/env python3 -'''This script reads the "Dream" Stable Diffusion prompt embedded in files generated by dream.py''' +'''This script reads the "Invoke" Stable Diffusion prompt embedded in files generated by invoke.py''' import sys from PIL import Image,PngImagePlugin if len(sys.argv) < 2: print("Usage: file2prompt.py ...") - print("This script opens up the indicated dream.py-generated PNG file(s) and prints out the prompt used to generate them.") + print("This script opens up the indicated invoke.py-generated PNG file(s) and prints out the prompt used to generate them.") exit(-1) filenames = sys.argv[1:] diff --git a/scripts/invoke.py b/scripts/invoke.py new file mode 100644 index 0000000000..100ab2413b --- /dev/null +++ b/scripts/invoke.py @@ -0,0 +1,573 @@ +#!/usr/bin/env python3 +# Copyright (c) 2022 Lincoln D. Stein (https://github.com/lstein) + +import os +import re +import sys +import shlex +import copy +import warnings +import time +import traceback +sys.path.append('.') # corrects a weird problem on Macs +from ldm.invoke.readline import get_completer +from ldm.invoke.args import Args, metadata_dumps, metadata_from_png, dream_cmd_from_png +from ldm.invoke.pngwriter import PngWriter, retrieve_metadata, write_metadata +from ldm.invoke.image_util import make_grid +from ldm.invoke.log import write_log +from omegaconf import OmegaConf +from backend.invoke_ai_web_server import InvokeAIWebServer + + +def main(): + """Initialize command-line parsers and the diffusion model""" + opt = Args() + args = opt.parse_args() + if not args: + sys.exit(-1) + + if args.laion400m: + print('--laion400m flag has been deprecated. Please use --model laion400m instead.') + sys.exit(-1) + if args.weights: + print('--weights argument has been deprecated. Please edit ./configs/models.yaml, and select the weights using --model instead.') + sys.exit(-1) + + print('* Initializing, be patient...\n') + from ldm.generate import Generate + + # these two lines prevent a horrible warning message from appearing + # when the frozen CLIP tokenizer is imported + import transformers + transformers.logging.set_verbosity_error() + + # Loading Face Restoration and ESRGAN Modules + try: + gfpgan, codeformer, esrgan = None, None, None + if opt.restore or opt.esrgan: + from ldm.invoke.restoration import Restoration + restoration = Restoration() + if opt.restore: + gfpgan, codeformer = restoration.load_face_restore_models(opt.gfpgan_dir, opt.gfpgan_model_path) + else: + print('>> Face restoration disabled') + if opt.esrgan: + esrgan = restoration.load_esrgan(opt.esrgan_bg_tile) + else: + print('>> Upscaling disabled') + else: + print('>> Face restoration and upscaling disabled') + except (ModuleNotFoundError, ImportError): + print(traceback.format_exc(), file=sys.stderr) + print('>> You may need to install the ESRGAN and/or GFPGAN modules') + + # creating a simple text2image object with a handful of + # defaults passed on the command line. + # additional parameters will be added (or overriden) during + # the user input loop + try: + gen = Generate( + conf = opt.conf, + model = opt.model, + sampler_name = opt.sampler_name, + embedding_path = opt.embedding_path, + full_precision = opt.full_precision, + precision = opt.precision, + gfpgan=gfpgan, + codeformer=codeformer, + esrgan=esrgan, + free_gpu_mem=opt.free_gpu_mem, + ) + except (FileNotFoundError, IOError, KeyError) as e: + print(f'{e}. Aborting.') + sys.exit(-1) + + # make sure the output directory exists + if not os.path.exists(opt.outdir): + os.makedirs(opt.outdir) + + # load the infile as a list of lines + infile = None + if opt.infile: + try: + if os.path.isfile(opt.infile): + infile = open(opt.infile, 'r', encoding='utf-8') + elif opt.infile == '-': # stdin + infile = sys.stdin + else: + raise FileNotFoundError(f'{opt.infile} not found.') + except (FileNotFoundError, IOError) as e: + print(f'{e}. Aborting.') + sys.exit(-1) + + if opt.seamless: + print(">> changed to seamless tiling mode") + + # preload the model + gen.load_model() + + # web server loops forever + if opt.web or opt.gui: + invoke_ai_web_server_loop(gen, gfpgan, codeformer, esrgan) + sys.exit(0) + + if not infile: + print( + "\n* Initialization done! Awaiting your command (-h for help, 'q' to quit)" + ) + + main_loop(gen, opt, infile) + +# TODO: main_loop() has gotten busy. Needs to be refactored. +def main_loop(gen, opt, infile): + """prompt/read/execute loop""" + done = False + path_filter = re.compile(r'[<>:"/\\|?*]') + last_results = list() + model_config = OmegaConf.load(opt.conf)[opt.model] + + # The readline completer reads history from the .dream_history file located in the + # output directory specified at the time of script launch. We do not currently support + # changing the history file midstream when the output directory is changed. + completer = get_completer(opt) + output_cntr = completer.get_current_history_length()+1 + + # os.pathconf is not available on Windows + if hasattr(os, 'pathconf'): + path_max = os.pathconf(opt.outdir, 'PC_PATH_MAX') + name_max = os.pathconf(opt.outdir, 'PC_NAME_MAX') + else: + path_max = 260 + name_max = 255 + + while not done: + operation = 'generate' # default operation, alternative is 'postprocess' + + if completer: + completer.set_default_dir(opt.outdir) + + try: + command = get_next_command(infile) + except EOFError: + done = True + continue + + # skip empty lines + if not command.strip(): + continue + + if command.startswith(('#', '//')): + continue + + if len(command.strip()) == 1 and command.startswith('q'): + done = True + break + + if command.startswith('!'): + subcommand = command[1:] + + if subcommand.startswith('dream'): # in case a stored prompt still contains the !dream command + command = command.replace('!dream ','',1) + + elif subcommand.startswith('fix'): + command = command.replace('!fix ','',1) + operation = 'postprocess' + + elif subcommand.startswith('fetch'): + file_path = command.replace('!fetch ','',1) + retrieve_dream_command(opt,file_path,completer) + continue + + elif subcommand.startswith('history'): + completer.show_history() + continue + + elif subcommand.startswith('search'): + search_str = command.replace('!search ','',1) + completer.show_history(search_str) + continue + + elif subcommand.startswith('clear'): + completer.clear_history() + continue + + elif re.match('^(\d+)',subcommand): + command_no = re.match('^(\d+)',subcommand).groups()[0] + command = completer.get_line(int(command_no)) + completer.set_line(command) + continue + + else: # not a recognized subcommand, so give the --help text + command = '-h' + + if opt.parse_cmd(command) is None: + continue + + if opt.init_img: + try: + if not opt.prompt: + oldargs = metadata_from_png(opt.init_img) + opt.prompt = oldargs.prompt + print(f'>> Retrieved old prompt "{opt.prompt}" from {opt.init_img}') + except (OSError, AttributeError, KeyError): + pass + + if len(opt.prompt) == 0: + print('\nTry again with a prompt!') + continue + + # width and height are set by model if not specified + if not opt.width: + opt.width = model_config.width + if not opt.height: + opt.height = model_config.height + + # retrieve previous value of init image if requested + if opt.init_img is not None and re.match('^-\\d+$', opt.init_img): + try: + opt.init_img = last_results[int(opt.init_img)][0] + print(f'>> Reusing previous image {opt.init_img}') + except IndexError: + print( + f'>> No previous initial image at position {opt.init_img} found') + opt.init_img = None + continue + + # try to relativize pathnames + for attr in ('init_img','init_mask','init_color','embedding_path'): + if getattr(opt,attr) and not os.path.exists(getattr(opt,attr)): + basename = getattr(opt,attr) + path = os.path.join(opt.outdir,basename) + setattr(opt,attr,path) + + # retrieve previous value of seed if requested + if opt.seed is not None and opt.seed < 0: + try: + opt.seed = last_results[opt.seed][1] + print(f'>> Reusing previous seed {opt.seed}') + except IndexError: + print(f'>> No previous seed at position {opt.seed} found') + opt.seed = None + continue + + if opt.strength is None: + opt.strength = 0.75 if opt.out_direction is None else 0.83 + + if opt.with_variations is not None: + opt.with_variations = split_variations(opt.with_variations) + + if opt.prompt_as_dir and operation == 'generate': + # sanitize the prompt to a valid folder name + subdir = path_filter.sub('_', opt.prompt)[:name_max].rstrip(' .') + + # truncate path to maximum allowed length + # 39 is the length of '######.##########.##########-##.png', plus two separators and a NUL + subdir = subdir[:(path_max - 39 - len(os.path.abspath(opt.outdir)))] + current_outdir = os.path.join(opt.outdir, subdir) + + print('Writing files to directory: "' + current_outdir + '"') + + # make sure the output directory exists + if not os.path.exists(current_outdir): + os.makedirs(current_outdir) + else: + if not os.path.exists(opt.outdir): + os.makedirs(opt.outdir) + current_outdir = opt.outdir + + # write out the history at this point + if operation == 'postprocess': + completer.add_history(f'!fix {command}') + else: + completer.add_history(command) + + # Here is where the images are actually generated! + last_results = [] + try: + file_writer = PngWriter(current_outdir) + results = [] # list of filename, prompt pairs + grid_images = dict() # seed -> Image, only used if `opt.grid` + prior_variations = opt.with_variations or [] + prefix = file_writer.unique_prefix() + + def image_writer(image, seed, upscaled=False, first_seed=None, use_prefix=None): + # note the seed is the seed of the current image + # the first_seed is the original seed that noise is added to + # when the -v switch is used to generate variations + nonlocal prior_variations + nonlocal prefix + if use_prefix is not None: + prefix = use_prefix + + path = None + if opt.grid: + grid_images[seed] = image + else: + postprocessed = upscaled if upscaled else operation=='postprocess' + filename, formatted_dream_prompt = prepare_image_metadata( + opt, + prefix, + seed, + operation, + prior_variations, + postprocessed, + first_seed + ) + path = file_writer.save_image_and_prompt_to_png( + image = image, + dream_prompt = formatted_dream_prompt, + metadata = metadata_dumps( + opt, + seeds = [seed if opt.variation_amount==0 and len(prior_variations)==0 else first_seed], + model_hash = gen.model_hash, + ), + name = filename, + ) + + # update rfc metadata + if operation == 'postprocess': + tool = re.match('postprocess:(\w+)',opt.last_operation).groups()[0] + add_postprocessing_to_metadata( + opt, + opt.prompt, + filename, + tool, + formatted_dream_prompt, + ) + + if (not postprocessed) or opt.save_original: + # only append to results if we didn't overwrite an earlier output + results.append([path, formatted_dream_prompt]) + + # so that the seed autocompletes (on linux|mac when -S or --seed specified + if completer: + completer.add_seed(seed) + completer.add_seed(first_seed) + last_results.append([path, seed]) + + if operation == 'generate': + catch_ctrl_c = infile is None # if running interactively, we catch keyboard interrupts + opt.last_operation='generate' + gen.prompt2image( + image_callback=image_writer, + catch_interrupts=catch_ctrl_c, + **vars(opt) + ) + elif operation == 'postprocess': + print(f'>> fixing {opt.prompt}') + opt.last_operation = do_postprocess(gen,opt,image_writer) + + if opt.grid and len(grid_images) > 0: + grid_img = make_grid(list(grid_images.values())) + grid_seeds = list(grid_images.keys()) + first_seed = last_results[0][1] + filename = f'{prefix}.{first_seed}.png' + formatted_dream_prompt = opt.dream_prompt_str(seed=first_seed,grid=True,iterations=len(grid_images)) + formatted_dream_prompt += f' # {grid_seeds}' + metadata = metadata_dumps( + opt, + seeds = grid_seeds, + model_hash = gen.model_hash + ) + path = file_writer.save_image_and_prompt_to_png( + image = grid_img, + dream_prompt = formatted_dream_prompt, + metadata = metadata, + name = filename + ) + results = [[path, formatted_dream_prompt]] + + except AssertionError as e: + print(e) + continue + + except OSError as e: + print(e) + continue + + print('Outputs:') + log_path = os.path.join(current_outdir, 'invoke_log') + output_cntr = write_log(results, log_path ,('txt', 'md'), output_cntr) + print() + + print('goodbye!') + +def do_postprocess (gen, opt, callback): + file_path = opt.prompt # treat the prompt as the file pathname + if os.path.dirname(file_path) == '': #basename given + file_path = os.path.join(opt.outdir,file_path) + + tool=None + if opt.gfpgan_strength > 0: + tool = opt.facetool + elif opt.embiggen: + tool = 'embiggen' + elif opt.upscale: + tool = 'upscale' + elif opt.out_direction: + tool = 'outpaint' + elif opt.outcrop: + tool = 'outcrop' + opt.save_original = True # do not overwrite old image! + opt.last_operation = f'postprocess:{tool}' + try: + gen.apply_postprocessor( + image_path = file_path, + tool = tool, + gfpgan_strength = opt.gfpgan_strength, + codeformer_fidelity = opt.codeformer_fidelity, + save_original = opt.save_original, + upscale = opt.upscale, + out_direction = opt.out_direction, + outcrop = opt.outcrop, + callback = callback, + opt = opt, + ) + except OSError: + print(traceback.format_exc(), file=sys.stderr) + print(f'** {file_path}: file could not be read') + return + except (KeyError, AttributeError): + print(traceback.format_exc(), file=sys.stderr) + return + return opt.last_operation + +def add_postprocessing_to_metadata(opt,original_file,new_file,tool,command): + original_file = original_file if os.path.exists(original_file) else os.path.join(opt.outdir,original_file) + new_file = new_file if os.path.exists(new_file) else os.path.join(opt.outdir,new_file) + meta = retrieve_metadata(original_file)['sd-metadata'] + img_data = meta['image'] + pp = img_data.get('postprocessing',[]) or [] + pp.append( + { + 'tool':tool, + 'dream_command':command, + } + ) + meta['image']['postprocessing'] = pp + write_metadata(new_file,meta) + +def prepare_image_metadata( + opt, + prefix, + seed, + operation='generate', + prior_variations=[], + postprocessed=False, + first_seed=None +): + + if postprocessed and opt.save_original: + filename = choose_postprocess_name(opt,prefix,seed) + else: + filename = f'{prefix}.{seed}.png' + + if opt.variation_amount > 0: + first_seed = first_seed or seed + this_variation = [[seed, opt.variation_amount]] + opt.with_variations = prior_variations + this_variation + formatted_dream_prompt = opt.dream_prompt_str(seed=first_seed) + elif len(prior_variations) > 0: + formatted_dream_prompt = opt.dream_prompt_str(seed=first_seed) + elif operation == 'postprocess': + formatted_dream_prompt = '!fix '+opt.dream_prompt_str(seed=seed) + else: + formatted_dream_prompt = opt.dream_prompt_str(seed=seed) + return filename,formatted_dream_prompt + +def choose_postprocess_name(opt,prefix,seed) -> str: + match = re.search('postprocess:(\w+)',opt.last_operation) + if match: + modifier = match.group(1) # will look like "gfpgan", "upscale", "outpaint" or "embiggen" + else: + modifier = 'postprocessed' + + counter = 0 + filename = None + available = False + while not available: + if counter == 0: + filename = f'{prefix}.{seed}.{modifier}.png' + else: + filename = f'{prefix}.{seed}.{modifier}-{counter:02d}.png' + available = not os.path.exists(os.path.join(opt.outdir,filename)) + counter += 1 + return filename + +def get_next_command(infile=None) -> str: # command string + if infile is None: + command = input('invoke> ') + else: + command = infile.readline() + if not command: + raise EOFError + else: + command = command.strip() + if len(command)>0: + print(f'#{command}') + return command + +def invoke_ai_web_server_loop(gen, gfpgan, codeformer, esrgan): + print('\n* --web was specified, starting web server...') + # Change working directory to the stable-diffusion directory + os.chdir( + os.path.abspath(os.path.join(os.path.dirname(__file__), '..')) + ) + + invoke_ai_web_server = InvokeAIWebServer(generate=gen, gfpgan=gfpgan, codeformer=codeformer, esrgan=esrgan) + + try: + invoke_ai_web_server.run() + except KeyboardInterrupt: + pass + + +def split_variations(variations_string) -> list: + # shotgun parsing, woo + parts = [] + broken = False # python doesn't have labeled loops... + for part in variations_string.split(','): + seed_and_weight = part.split(':') + if len(seed_and_weight) != 2: + print(f'** Could not parse with_variation part "{part}"') + broken = True + break + try: + seed = int(seed_and_weight[0]) + weight = float(seed_and_weight[1]) + except ValueError: + print(f'** Could not parse with_variation part "{part}"') + broken = True + break + parts.append([seed, weight]) + if broken: + return None + elif len(parts) == 0: + return None + else: + return parts + +def retrieve_dream_command(opt,file_path,completer): + ''' + Given a full or partial path to a previously-generated image file, + will retrieve and format the dream command used to generate the image, + and pop it into the readline buffer (linux, Mac), or print out a comment + for cut-and-paste (windows) + ''' + dir,basename = os.path.split(file_path) + if len(dir) == 0: + path = os.path.join(opt.outdir,basename) + else: + path = file_path + try: + cmd = dream_cmd_from_png(path) + except OSError: + print(f'** {path}: file could not be read') + return + except (KeyError, AttributeError): + print(f'** {path}: file has no metadata') + return + completer.set_line(cmd) + +if __name__ == '__main__': + main() diff --git a/scripts/orig_scripts/img2img.py b/scripts/orig_scripts/img2img.py index fcd0b8cdfa..9f74f25bf2 100644 --- a/scripts/orig_scripts/img2img.py +++ b/scripts/orig_scripts/img2img.py @@ -18,7 +18,7 @@ from pytorch_lightning import seed_everything from ldm.util import instantiate_from_config from ldm.models.diffusion.ddim import DDIMSampler from ldm.models.diffusion.plms import PLMSSampler -from ldm.dream.devices import choose_torch_device +from ldm.invoke.devices import choose_torch_device def chunk(it, size): diff --git a/scripts/orig_scripts/inpaint.py b/scripts/orig_scripts/inpaint.py index 87b0e98d96..b8245db322 100644 --- a/scripts/orig_scripts/inpaint.py +++ b/scripts/orig_scripts/inpaint.py @@ -6,7 +6,7 @@ import numpy as np import torch from main import instantiate_from_config from ldm.models.diffusion.ddim import DDIMSampler -from ldm.dream.devices import choose_torch_device +from ldm.invoke.devices import choose_torch_device def make_batch(image, mask, device): image = np.array(Image.open(image).convert("RGB")) diff --git a/scripts/orig_scripts/txt2img.py b/scripts/orig_scripts/txt2img.py index 6c43e73b93..0d350d2c73 100644 --- a/scripts/orig_scripts/txt2img.py +++ b/scripts/orig_scripts/txt2img.py @@ -18,7 +18,7 @@ import torch.nn as nn from ldm.util import instantiate_from_config from ldm.models.diffusion.ddim import DDIMSampler from ldm.models.diffusion.plms import PLMSSampler -from ldm.dream.devices import choose_torch_device +from ldm.invoke.devices import choose_torch_device def chunk(it, size): it = iter(it) diff --git a/scripts/preload_models.py b/scripts/preload_models.py index f1475d38ec..db484517db 100644 --- a/scripts/preload_models.py +++ b/scripts/preload_models.py @@ -15,13 +15,13 @@ import urllib.request transformers.logging.set_verbosity_error() # this will preload the Bert tokenizer fles -print('preloading bert tokenizer...') +print('preloading bert tokenizer...', end='') tokenizer = BertTokenizerFast.from_pretrained('bert-base-uncased') print('...success') # this will download requirements for Kornia -print('preloading Kornia requirements (ignore the deprecation warnings)...') +print('preloading Kornia requirements...', end='') with warnings.catch_warnings(): warnings.filterwarnings('ignore', category=DeprecationWarning) import kornia @@ -29,12 +29,12 @@ print('...success') version = 'openai/clip-vit-large-patch14' -print('preloading CLIP model (Ignore the deprecation warnings)...') +print('preloading CLIP model...',end='') sys.stdout.flush() tokenizer = CLIPTokenizer.from_pretrained(version) transformer = CLIPTextModel.from_pretrained(version) -print('\n\n...success') +print('...success') # In the event that the user has installed GFPGAN and also elected to use # RealESRGAN, this will attempt to download the model needed by RealESRGANer @@ -47,7 +47,7 @@ except ModuleNotFoundError: pass if gfpgan: - print('Loading models from RealESRGAN and facexlib') + print('Loading models from RealESRGAN and facexlib...',end='') try: from realesrgan.archs.srvgg_arch import SRVGGNetCompact from facexlib.utils.face_restoration_helper import FaceRestoreHelper @@ -65,27 +65,41 @@ if gfpgan: print('Error loading ESRGAN:') print(traceback.format_exc()) - try: - import urllib.request - model_url = 'https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.4.pth' - model_dest = 'src/gfpgan/experiments/pretrained_models/GFPGANv1.4.pth' + print('Loading models from GFPGAN') + import urllib.request + for model in ( + [ + 'https://github.com/TencentARC/GFPGAN/releases/download/v1.3.0/GFPGANv1.4.pth', + 'src/gfpgan/experiments/pretrained_models/GFPGANv1.4.pth' + ], + [ + 'https://github.com/xinntao/facexlib/releases/download/v0.1.0/detection_Resnet50_Final.pth', + './gfpgan/weights/detection_Resnet50_Final.pth' + ], + [ + 'https://github.com/xinntao/facexlib/releases/download/v0.2.2/parsing_parsenet.pth', + './gfpgan/weights/parsing_parsenet.pth' + ], + ): + model_url,model_dest = model + try: + if not os.path.exists(model_dest): + print(f'Downloading gfpgan model file {model_url}...',end='') + os.makedirs(os.path.dirname(model_dest), exist_ok=True) + urllib.request.urlretrieve(model_url,model_dest) + print('...success') + except Exception: + import traceback + print('Error loading GFPGAN:') + print(traceback.format_exc()) - if not os.path.exists(model_dest): - print('downloading gfpgan model file...') - urllib.request.urlretrieve(model_url,model_dest) - except Exception: - import traceback - print('Error loading GFPGAN:') - print(traceback.format_exc()) -print('...success') - -print('preloading CodeFormer model file...') +print('preloading CodeFormer model file...',end='') try: import urllib.request model_url = 'https://github.com/sczhou/CodeFormer/releases/download/v0.1.0/codeformer.pth' - model_dest = 'ldm/dream/restoration/codeformer/weights/codeformer.pth' + model_dest = 'ldm/invoke/restoration/codeformer/weights/codeformer.pth' if not os.path.exists(model_dest): - print('downloading codeformer model file...') + print('Downloading codeformer model file...') os.makedirs(os.path.dirname(model_dest), exist_ok=True) urllib.request.urlretrieve(model_url,model_dest) except Exception: diff --git a/scripts/sd-metadata.py b/scripts/sd-metadata.py index 02d5002d60..6a94fd6115 100755 --- a/scripts/sd-metadata.py +++ b/scripts/sd-metadata.py @@ -2,11 +2,11 @@ import sys import json -from ldm.dream.pngwriter import retrieve_metadata +from ldm.invoke.pngwriter import retrieve_metadata if len(sys.argv) < 2: print("Usage: file2prompt.py ...") - print("This script opens up the indicated dream.py-generated PNG file(s) and prints out their metadata.") + print("This script opens up the indicated invoke.py-generated PNG file(s) and prints out their metadata.") exit(-1) filenames = sys.argv[1:] diff --git a/server/application.py b/server/application.py index 58725637a7..a48ee5488d 100644 --- a/server/application.py +++ b/server/application.py @@ -10,7 +10,7 @@ from flask_cors import CORS from flask_socketio import SocketIO from omegaconf import OmegaConf from dependency_injector.wiring import inject, Provide -from ldm.dream.args import Args +from ldm.invoke.args import Args from server import views from server.containers import Container from server.services import GeneratorService, SignalService diff --git a/server/services.py b/server/services.py index 93bbe1d240..19b2360a37 100644 --- a/server/services.py +++ b/server/services.py @@ -12,12 +12,12 @@ import shlex from threading import Thread import time from flask_socketio import SocketIO, join_room, leave_room -from ldm.dream.args import Args -from ldm.dream.generator import embiggen +from ldm.invoke.args import Args +from ldm.invoke.generator import embiggen from PIL import Image -from ldm.dream.pngwriter import PngWriter -from ldm.dream.server import CanceledException +from ldm.invoke.pngwriter import PngWriter +from ldm.invoke.server import CanceledException from ldm.generate import Generate from server.models import DreamResult, JobRequest, PaginatedItems, ProgressType, Signal diff --git a/setup.py b/setup.py index 3baab3abc4..cc4a1f7237 100644 --- a/setup.py +++ b/setup.py @@ -1,8 +1,8 @@ from setuptools import setup, find_packages setup( - name='stable-diffusion', - version='1.15.0-dev', + name='invoke-ai', + version='2.0.0', description='', packages=find_packages(), install_requires=[ @@ -10,4 +10,4 @@ setup( 'numpy', 'tqdm', ], -) \ No newline at end of file +)