InvokeAI/pyproject.toml
Gregg Helt c647056287
Feat/easy param (#3504)
* Testing change to LatentsToText to allow setting different cfg_scale values per diffusion step.

* Adding first attempt at float param easing node, using Penner easing functions.

* Core implementation of ControlNet and MultiControlNet.

* Added support for ControlNet and MultiControlNet to legacy non-nodal Txt2Img in backend/generator. Although backend/generator will likely disappear by v3.x, right now they are very useful for testing core ControlNet and MultiControlNet functionality while node codebase is rapidly evolving.

* Added example of using ControlNet with legacy Txt2Img generator

* Resolving rebase conflict

* Added first controlnet preprocessor node for canny edge detection.

* Initial port of controlnet node support from generator-based TextToImageInvocation node to latent-based TextToLatentsInvocation node

* Switching to ControlField for output from controlnet nodes.

* Resolving conflicts in rebase to origin/main

* Refactored ControlNet nodes so they subclass from PreprocessedControlInvocation, and only need to override run_processor(image) (instead of reimplementing invoke())

* changes to base class for controlnet nodes

* Added HED, LineArt, and OpenPose ControlNet nodes

* Added an additional "raw_processed_image" output port to controlnets, mainly so could route ImageField to a ShowImage node

* Added more preprocessor nodes for:
      MidasDepth
      ZoeDepth
      MLSD
      NormalBae
      Pidi
      LineartAnime
      ContentShuffle
Removed pil_output options, ControlNet preprocessors should always output as PIL. Removed diagnostics and other general cleanup.

* Prep for splitting pre-processor and controlnet nodes

* Refactored controlnet nodes: split out controlnet stuff into separate node, stripped controlnet stuff form image processing/analysis nodes.

* Added resizing of controlnet image based on noise latent. Fixes a tensor mismatch issue.

* More rebase repair.

* Added support for using multiple control nets. Unfortunately this breaks direct usage of Control node output port  ==> TextToLatent control input port -- passing through a Collect node is now required. Working on fixing this...

* Fixed use of ControlNet control_weight parameter

* Fixed lint-ish formatting error

* Core implementation of ControlNet and MultiControlNet.

* Added first controlnet preprocessor node for canny edge detection.

* Initial port of controlnet node support from generator-based TextToImageInvocation node to latent-based TextToLatentsInvocation node

* Switching to ControlField for output from controlnet nodes.

* Refactored controlnet node to output ControlField that bundles control info.

* changes to base class for controlnet nodes

* Added more preprocessor nodes for:
      MidasDepth
      ZoeDepth
      MLSD
      NormalBae
      Pidi
      LineartAnime
      ContentShuffle
Removed pil_output options, ControlNet preprocessors should always output as PIL. Removed diagnostics and other general cleanup.

* Prep for splitting pre-processor and controlnet nodes

* Refactored controlnet nodes: split out controlnet stuff into separate node, stripped controlnet stuff form image processing/analysis nodes.

* Added resizing of controlnet image based on noise latent. Fixes a tensor mismatch issue.

* Cleaning up TextToLatent arg testing

* Cleaning up mistakes after rebase.

* Removed last bits of dtype and and device hardwiring from controlnet section

* Refactored ControNet support to consolidate multiple parameters into data struct. Also redid how multiple controlnets are handled.

* Added support for specifying which step iteration to start using
each ControlNet, and which step to end using each controlnet (specified as fraction of total steps)

* Cleaning up prior to submitting ControlNet PR. Mostly turning off diagnostic printing. Also fixed error when there is no controlnet input.

* Added dependency on controlnet-aux v0.0.3

* Commented out ZoeDetector. Will re-instate once there's a controlnet-aux release that supports it.

* Switched CotrolNet node modelname input from free text to default list of popular ControlNet model names.

* Fix to work with current stable release of controlnet_aux (v0.0.3). Turned of pre-processor params that were added post v0.0.3. Also change defaults for shuffle.

* Refactored most of controlnet code into its own method to declutter TextToLatents.invoke(), and make upcoming integration with LatentsToLatents easier.

* Cleaning up after ControlNet refactor in TextToLatentsInvocation

* Extended node-based ControlNet support to LatentsToLatentsInvocation.

* chore(ui): regen api client

* fix(ui): add value to conditioning field

* fix(ui): add control field type

* fix(ui): fix node ui type hints

* fix(nodes): controlnet input accepts list or single controlnet

* Moved to controlnet_aux v0.0.4, reinstated Zoe controlnet preprocessor. Also in pyproject.toml  had to specify downgrade of timm to 0.6.13 _after_ controlnet-aux installs timm >= 0.9.2, because timm >0.6.13 breaks Zoe preprocessor.

* Core implementation of ControlNet and MultiControlNet.

* Added first controlnet preprocessor node for canny edge detection.

* Switching to ControlField for output from controlnet nodes.

* Resolving conflicts in rebase to origin/main

* Refactored ControlNet nodes so they subclass from PreprocessedControlInvocation, and only need to override run_processor(image) (instead of reimplementing invoke())

* changes to base class for controlnet nodes

* Added HED, LineArt, and OpenPose ControlNet nodes

* Added more preprocessor nodes for:
      MidasDepth
      ZoeDepth
      MLSD
      NormalBae
      Pidi
      LineartAnime
      ContentShuffle
Removed pil_output options, ControlNet preprocessors should always output as PIL. Removed diagnostics and other general cleanup.

* Prep for splitting pre-processor and controlnet nodes

* Refactored controlnet nodes: split out controlnet stuff into separate node, stripped controlnet stuff form image processing/analysis nodes.

* Added resizing of controlnet image based on noise latent. Fixes a tensor mismatch issue.

* Added support for using multiple control nets. Unfortunately this breaks direct usage of Control node output port  ==> TextToLatent control input port -- passing through a Collect node is now required. Working on fixing this...

* Fixed use of ControlNet control_weight parameter

* Core implementation of ControlNet and MultiControlNet.

* Added first controlnet preprocessor node for canny edge detection.

* Initial port of controlnet node support from generator-based TextToImageInvocation node to latent-based TextToLatentsInvocation node

* Switching to ControlField for output from controlnet nodes.

* Refactored controlnet node to output ControlField that bundles control info.

* changes to base class for controlnet nodes

* Added more preprocessor nodes for:
      MidasDepth
      ZoeDepth
      MLSD
      NormalBae
      Pidi
      LineartAnime
      ContentShuffle
Removed pil_output options, ControlNet preprocessors should always output as PIL. Removed diagnostics and other general cleanup.

* Prep for splitting pre-processor and controlnet nodes

* Refactored controlnet nodes: split out controlnet stuff into separate node, stripped controlnet stuff form image processing/analysis nodes.

* Added resizing of controlnet image based on noise latent. Fixes a tensor mismatch issue.

* Cleaning up TextToLatent arg testing

* Cleaning up mistakes after rebase.

* Removed last bits of dtype and and device hardwiring from controlnet section

* Refactored ControNet support to consolidate multiple parameters into data struct. Also redid how multiple controlnets are handled.

* Added support for specifying which step iteration to start using
each ControlNet, and which step to end using each controlnet (specified as fraction of total steps)

* Cleaning up prior to submitting ControlNet PR. Mostly turning off diagnostic printing. Also fixed error when there is no controlnet input.

* Commented out ZoeDetector. Will re-instate once there's a controlnet-aux release that supports it.

* Switched CotrolNet node modelname input from free text to default list of popular ControlNet model names.

* Fix to work with current stable release of controlnet_aux (v0.0.3). Turned of pre-processor params that were added post v0.0.3. Also change defaults for shuffle.

* Refactored most of controlnet code into its own method to declutter TextToLatents.invoke(), and make upcoming integration with LatentsToLatents easier.

* Cleaning up after ControlNet refactor in TextToLatentsInvocation

* Extended node-based ControlNet support to LatentsToLatentsInvocation.

* chore(ui): regen api client

* fix(ui): fix node ui type hints

* fix(nodes): controlnet input accepts list or single controlnet

* Added Mediapipe image processor for use as ControlNet preprocessor.
Also hacked in ability to specify HF subfolder when loading ControlNet models from string.

* Fixed bug where MediapipFaceProcessorInvocation was ignoring max_faces and min_confidence params.

* Added nodes for float params: ParamFloatInvocation and FloatCollectionOutput. Also added FloatOutput.

* Added mediapipe install requirement. Should be able to remove once controlnet_aux package adds mediapipe to its requirements.

* Added float to FIELD_TYPE_MAP ins constants.ts

* Progress toward improvement in fieldTemplateBuilder.ts  getFieldType()

* Fixed controlnet preprocessors and controlnet handling in TextToLatents to work with revised Image services.

* Cleaning up from merge, re-adding cfg_scale to FIELD_TYPE_MAP

* Making sure cfg_scale of type list[float] can be used in image metadata, to support param easing for cfg_scale

* Fixed math for per-step param easing.

* Added option to show plot of param value at each step

* Just cleaning up after adding param easing plot option, removing vestigial code.

* Modified control_weight ControlNet param to be polistmorphic --
can now be either a single float weight applied for all steps, or a list of floats of size total_steps, that specifies weight for each step.

* Added more informative error message when _validat_edge() throws an error.

* Just improving parm easing bar chart title to include easing type.

* Added requirement for easing-functions package

* Taking out some diagnostic prints.

* Added option to use both easing function and mirror of easing function together.

* Fixed recently introduced problem (when pulled in main), triggered by num_steps in StepParamEasingInvocation not having a default value -- just added default.

---------

Co-authored-by: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
2023-06-11 16:27:44 +10:00

174 lines
5.4 KiB
TOML

[build-system]
requires = ["setuptools~=65.5", "pip~=22.3", "wheel"]
build-backend = "setuptools.build_meta"
[project]
name = "InvokeAI"
description = "An implementation of Stable Diffusion which provides various new features and options to aid the image generation process"
requires-python = ">=3.9, <3.11"
readme = { content-type = "text/markdown", file = "README.md" }
keywords = ["stable-diffusion", "AI"]
dynamic = ["version"]
license = { file = "LICENSE" }
authors = [{ name = "The InvokeAI Project", email = "lincoln.stein@gmail.com" }]
classifiers = [
'Development Status :: 4 - Beta',
'Environment :: GPU',
'Environment :: GPU :: NVIDIA CUDA',
'Environment :: MacOS X',
'Intended Audience :: End Users/Desktop',
'Intended Audience :: Developers',
'License :: OSI Approved :: MIT License',
'Operating System :: POSIX :: Linux',
'Operating System :: MacOS',
'Operating System :: Microsoft :: Windows',
'Programming Language :: Python :: 3 :: Only',
'Programming Language :: Python :: 3.8',
'Programming Language :: Python :: 3.9',
'Programming Language :: Python :: 3.10',
'Topic :: Artistic Software',
'Topic :: Internet :: WWW/HTTP :: WSGI :: Application',
'Topic :: Internet :: WWW/HTTP :: WSGI :: Server',
'Topic :: Multimedia :: Graphics',
'Topic :: Scientific/Engineering :: Artificial Intelligence',
'Topic :: Scientific/Engineering :: Image Processing',
]
dependencies = [
"accelerate~=0.16",
"albumentations",
"click",
"clip_anytorch", # replacing "clip @ https://github.com/openai/CLIP/archive/eaa22acb90a5876642d0507623e859909230a52d.zip",
"compel>=1.2.1",
"controlnet-aux>=0.0.4",
"timm==0.6.13", # needed to override timm latest in controlnet_aux, see https://github.com/isl-org/ZoeDepth/issues/26
"datasets",
"diffusers[torch]~=0.16.1",
"dnspython==2.2.1",
"easing-functions",
"einops",
"eventlet",
"facexlib",
"fastapi==0.88.0",
"fastapi-events==0.8.0",
"fastapi-socketio==0.0.10",
"flask==2.1.3",
"flask_cors==3.0.10",
"flask_socketio==5.3.0",
"flaskwebgui==1.0.3",
"gfpgan==1.3.8",
"huggingface-hub>=0.11.1",
"matplotlib", # needed for plotting of Penner easing functions
"mediapipe", # needed for "mediapipeface" controlnet model
"npyscreen",
"numpy<1.24",
"omegaconf",
"opencv-python",
"picklescan",
"pillow",
"prompt-toolkit",
"pypatchmatch",
'pyperclip',
"pyreadline3",
"python-multipart==0.0.6",
"pytorch-lightning==1.7.7",
"realesrgan",
"requests==2.28.2",
"rich~=13.3",
"safetensors~=0.3.0",
"scikit-image>=0.19",
"send2trash",
"test-tube>=0.7.5",
"torch~=2.0.0",
"torchvision>=0.14.1",
"torchmetrics",
"transformers~=4.26",
"uvicorn[standard]==0.21.1",
"windows-curses; sys_platform=='win32'",
]
[project.optional-dependencies]
"dist" = ["pip-tools", "pipdeptree", "twine"]
"docs" = [
"mkdocs-material<9.0",
"mkdocs-git-revision-date-localized-plugin",
"mkdocs-redirects==1.2.0",
]
"dev" = [
"pudb",
]
"test" = ["pytest>6.0.0", "pytest-cov"]
"xformers" = [
"xformers~=0.0.19; sys_platform!='darwin'",
"triton; sys_platform=='linux'",
]
[project.scripts]
# legacy entrypoints; provided for backwards compatibility
"configure_invokeai.py" = "invokeai.frontend.install:invokeai_configure"
"textual_inversion.py" = "invokeai.frontend.training:invokeai_textual_inversion"
# shortcut commands to start cli and web
"invokeai" = "invokeai.app.cli_app:invoke_cli"
"invokeai-web" = "invokeai.app.api_app:invoke_api"
# full commands
"invokeai-configure" = "invokeai.frontend.install:invokeai_configure"
"invokeai-merge" = "invokeai.frontend.merge:invokeai_merge_diffusers"
"invokeai-ti" = "invokeai.frontend.training:invokeai_textual_inversion"
"invokeai-model-install" = "invokeai.frontend.install:invokeai_model_install"
"invokeai-update" = "invokeai.frontend.install:invokeai_update"
"invokeai-metadata" = "invokeai.frontend.CLI.sd_metadata:print_metadata"
"invokeai-node-cli" = "invokeai.app.cli_app:invoke_cli"
"invokeai-node-web" = "invokeai.app.api_app:invoke_api"
[project.urls]
"Homepage" = "https://invoke-ai.github.io/InvokeAI/"
"Documentation" = "https://invoke-ai.github.io/InvokeAI/"
"Source" = "https://github.com/invoke-ai/InvokeAI/"
"Bug Reports" = "https://github.com/invoke-ai/InvokeAI/issues"
"Discord" = "https://discord.gg/ZmtBAhwWhy"
[tool.setuptools.dynamic]
version = { attr = "invokeai.version.__version__" }
[tool.setuptools.packages.find]
"where" = ["."]
"include" = [
"invokeai.assets.web*","invokeai.version*",
"invokeai.generator*","invokeai.backend*",
"invokeai.frontend*", "invokeai.frontend.web.dist*",
"invokeai.frontend.web.static*",
"invokeai.configs*",
"invokeai.app*","ldm*",
]
[tool.setuptools.package-data]
"invokeai.assets.web" = ["**.png"]
"invokeai.backend" = ["**.png"]
"invokeai.configs" = ["*.example", "**/*.yaml", "*.txt"]
"invokeai.frontend.web.dist" = ["**"]
"invokeai.frontend.web.static" = ["**"]
#=== Begin: PyTest and Coverage
[tool.pytest.ini_options]
addopts = "--cov-report term --cov-report html --cov-report xml"
[tool.coverage.run]
branch = true
source = ["invokeai"]
omit = ["*tests*", "*migrations*", ".venv/*", "*.env"]
[tool.coverage.report]
show_missing = true
fail_under = 85 # let's set something sensible on Day 1 ...
[tool.coverage.json]
output = "coverage/coverage.json"
pretty_print = true
[tool.coverage.html]
directory = "coverage/html"
[tool.coverage.xml]
output = "coverage/index.xml"
#=== End: PyTest and Coverage
[flake8]
max-line-length = 120