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https://github.com/invoke-ai/InvokeAI
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193 lines
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Markdown
193 lines
8.3 KiB
Markdown
---
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title: Changelog
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---
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# :octicons-log-16: **Changelog**
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## v2.0.1 (13 October 2022)
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- fix noisy images at high step count when using k* samplers
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- dream.py script now calls invoke.py module directly rather than
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via a new python process (which could break the environment)
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## v2.0.0 <small>(9 October 2022)</small>
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- `dream.py` script renamed `invoke.py`. A `dream.py` script wrapper remains
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for backward compatibility.
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- Completely new WebGUI - launch with `python3 scripts/invoke.py --web`
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- Support for [inpainting](features/INPAINTING.md) and [outpainting](features/OUTPAINTING.md)
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- img2img runs on all k* samplers
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- Support for [negative prompts](features/PROMPTS.md#negative-and-unconditioned-prompts)
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- Support for CodeFormer face reconstruction
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- Support for Textual Inversion on Macintoshes
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- Support in both WebGUI and CLI for [post-processing of previously-generated images](features/POSTPROCESS.md)
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using facial reconstruction, ESRGAN upscaling, outcropping (similar to DALL-E infinite canvas),
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and "embiggen" upscaling. See the `!fix` command.
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- New `--hires` option on `invoke>` line allows [larger images to be created without duplicating elements](features/CLI.md#this-is-an-example-of-txt2img), at the cost of some performance.
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- New `--perlin` and `--threshold` options allow you to add and control variation
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during image generation (see [Thresholding and Perlin Noise Initialization](features/OTHER.md#thresholding-and-perlin-noise-initialization-options))
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- Extensive metadata now written into PNG files, allowing reliable regeneration of images
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and tweaking of previous settings.
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- Command-line completion in `invoke.py` now works on Windows, Linux and Mac platforms.
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- Improved [command-line completion behavior](features/CLI.md)
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New commands added:
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- List command-line history with `!history`
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- Search command-line history with `!search`
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- Clear history with `!clear`
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- Deprecated `--full_precision` / `-F`. Simply omit it and `invoke.py` will auto
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configure. To switch away from auto use the new flag like `--precision=float32`.
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## v1.14 <small>(11 September 2022)</small>
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- Memory optimizations for small-RAM cards. 512x512 now possible on 4 GB GPUs.
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- Full support for Apple hardware with M1 or M2 chips.
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- Add "seamless mode" for circular tiling of image. Generates beautiful effects.
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([prixt](https://github.com/prixt)).
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- Inpainting support.
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- Improved web server GUI.
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- Lots of code and documentation cleanups.
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## v1.13 <small>(3 September 2022)</small>
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- Support image variations (see [VARIATIONS](features/VARIATIONS.md)
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([Kevin Gibbons](https://github.com/bakkot) and many contributors and reviewers)
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- Supports a Google Colab notebook for a standalone server running on Google hardware
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[Arturo Mendivil](https://github.com/artmen1516)
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- WebUI supports GFPGAN/ESRGAN facial reconstruction and upscaling
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[Kevin Gibbons](https://github.com/bakkot)
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- WebUI supports incremental display of in-progress images during generation
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[Kevin Gibbons](https://github.com/bakkot)
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- A new configuration file scheme that allows new models (including upcoming
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stable-diffusion-v1.5) to be added without altering the code.
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([David Wager](https://github.com/maddavid12))
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- Can specify --grid on invoke.py command line as the default.
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- Miscellaneous internal bug and stability fixes.
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- Works on M1 Apple hardware.
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- Multiple bug fixes.
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---
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## v1.12 <small>(28 August 2022)</small>
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- Improved file handling, including ability to read prompts from standard input.
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(kudos to [Yunsaki](https://github.com/yunsaki)
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- The web server is now integrated with the invoke.py script. Invoke by adding --web to
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the invoke.py command arguments.
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- Face restoration and upscaling via GFPGAN and Real-ESGAN are now automatically
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enabled if the GFPGAN directory is located as a sibling to Stable Diffusion.
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VRAM requirements are modestly reduced. Thanks to both [Blessedcoolant](https://github.com/blessedcoolant) and
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[Oceanswave](https://github.com/oceanswave) for their work on this.
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- You can now swap samplers on the invoke> command line. [Blessedcoolant](https://github.com/blessedcoolant)
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---
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## v1.11 <small>(26 August 2022)</small>
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- NEW FEATURE: Support upscaling and face enhancement using the GFPGAN module. (kudos to [Oceanswave](https://github.com/Oceanswave)
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- 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.
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Seed memory only extends back to the previous command, but will work on all images generated with the -n# switch.
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- Variant generation support temporarily disabled pending more general solution.
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- Created a feature branch named **yunsaki-morphing-invoke** which adds experimental support for
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iteratively modifying the prompt and its parameters. Please see[Pull Request #86](https://github.com/lstein/stable-diffusion/pull/86)
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for a synopsis of how this works. Note that when this feature is eventually added to the main branch, it will may be modified
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significantly.
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---
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## v1.10 <small>(25 August 2022)</small>
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- A barebones but fully functional interactive web server for online generation of txt2img and img2img.
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---
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## v1.09 <small>(24 August 2022)</small>
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- A new -v option allows you to generate multiple variants of an initial image
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in img2img mode. (kudos to [Oceanswave](https://github.com/Oceanswave). [
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See this discussion in the PR for examples and details on use](https://github.com/lstein/stable-diffusion/pull/71#issuecomment-1226700810))
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- Added ability to personalize text to image generation (kudos to [Oceanswave](https://github.com/Oceanswave) and [nicolai256](https://github.com/nicolai256))
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- Enabled all of the samplers from k_diffusion
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---
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## v1.08 <small>(24 August 2022)</small>
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- Escape single quotes on the invoke> command before trying to parse. This avoids
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parse errors.
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- Removed instruction to get Python3.8 as first step in Windows install.
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Anaconda3 does it for you.
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- Added bounds checks for numeric arguments that could cause crashes.
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- Cleaned up the copyright and license agreement files.
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---
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## v1.07 <small>(23 August 2022)</small>
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- Image filenames will now never fill gaps in the sequence, but will be assigned the
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next higher name in the chosen directory. This ensures that the alphabetic and chronological
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sort orders are the same.
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---
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## v1.06 <small>(23 August 2022)</small>
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- Added weighted prompt support contributed by [xraxra](https://github.com/xraxra)
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- Example of using weighted prompts to tweak a demonic figure contributed by [bmaltais](https://github.com/bmaltais)
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---
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## v1.05 <small>(22 August 2022 - after the drop)</small>
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- Filenames now use the following formats:
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000010.95183149.png -- Two files produced by the same command (e.g. -n2),
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000010.26742632.png -- distinguished by a different seed.
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000011.455191342.01.png -- Two files produced by the same command using
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000011.455191342.02.png -- a batch size>1 (e.g. -b2). They have the same seed.
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000011.4160627868.grid#1-4.png -- a grid of four images (-g); the whole grid can
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be regenerated with the indicated key
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- It should no longer be possible for one image to overwrite another
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- You can use the "cd" and "pwd" commands at the invoke> prompt to set and retrieve
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the path of the output directory.
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---
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## v1.04 <small>(22 August 2022 - after the drop)</small>
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- Updated README to reflect installation of the released weights.
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- Suppressed very noisy and inconsequential warning when loading the frozen CLIP
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tokenizer.
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---
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## v1.03 <small>(22 August 2022)</small>
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- The original txt2img and img2img scripts from the CompViz repository have been moved into
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a subfolder named "orig_scripts", to reduce confusion.
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---
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## v1.02 <small>(21 August 2022)</small>
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- A copy of the prompt and all of its switches and options is now stored in the corresponding
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image in a tEXt metadata field named "Dream". You can read the prompt using scripts/images2prompt.py,
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or an image editor that allows you to explore the full metadata.
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**Please run "conda env update" to load the k_lms dependencies!!**
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---
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## v1.01 <small>(21 August 2022)</small>
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- added k_lms sampling.
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**Please run "conda env update" to load the k_lms dependencies!!**
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- use half precision arithmetic by default, resulting in faster execution and lower memory requirements
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Pass argument --full_precision to invoke.py to get slower but more accurate image generation
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---
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## Links
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- **[Read Me](index.md)**
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