GitLab

* minor documentation fixes of the depth and normals pipelines

* update license headers

* update model checkpoints in examples
fix missing prediction_type in register_to_config in the normals pipeline

* add initial marigold intrinsics pipeline
update comments about num_inference_steps and ensemble_size
minor fixes in comments of marigold normals and depth pipelines

* update uncertainty visualization to work with intrinsics

* integrate iid


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Co-authored-by: YiYi Xu <yixu310@gmail.com>
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* implement marigold depth and normals pipelines in diffusers core

* remove bibtex

* remove deprecations

* remove save_memory argument

* remove validate_vae

* remove config output

* remove batch_size autodetection

* remove presets logic
move default denoising_steps and processing_resolution into the model config
make default ensemble_size 1

* remove no_grad

* add fp16 to the example usage

* implement is_matplotlib_available
use is_matplotlib_available, is_scipy_available for conditional imports in the marigold depth pipeline

* move colormap, visualize_depth, and visualize_normals into export_utils.py

* make the denoising loop more lucid
fix the outputs to always be 4d tensors or lists of pil images
support a 4d input_image case
attempt to support model_cpu_offload_seq
move check_inputs into a separate function
change default batch_size to 1, remove any logic to make it bigger implicitly

* style

* rename denoising_steps into num_inference_steps

* rename input_image into image

* rename input_latent into latents

* remove decode_image
change decode_prediction to use the AutoencoderKL.decode method

* move clean_latent outside of progress_bar

* refactor marigold-reusable image processing bits into MarigoldImageProcessor class

* clean up the usage example docstring

* make ensemble functions members of the pipelines

* add early checks in check_inputs
rename E into ensemble_size in depth ensembling

* fix vae_scale_factor computation

* better compatibility with torch.compile
better variable naming

* move export_depth_to_png to export_utils

* remove encode_prediction

* improve visualize_depth and visualize_normals to accept multi-dimensional data and lists
remove visualization functions from the pipelines
move exporting depth as 16-bit PNGs functionality from the depth pipeline
update example docstrings

* do not shortcut vae.config variables

* change all asserts to raise ValueError

* rename output_prediction_type to output_type

* better variable names
clean up variable deletion code

* better variable names

* pass desc and leave kwargs into the diffusers progress_bar
implement nested progress bar for images and steps loops

* implement scale_invariant and shift_invariant flags in the ensemble_depth function
add scale_invariant and shift_invariant flags readout from the model config
further refactor ensemble_depth
support ensembling without alignment
add ensemble_depth docstring

* fix generator device placement checks

* move encode_empty_text body into the pipeline call

* minor empty text encoding simplifications

* adjust pipelines' class docstrings to explain the added construction arguments

* improve the scipy failure condition
add comments
improve docstrings
change the default use_full_z_range to True

* make input image values range check configurable in the preprocessor
refactor load_image_canonical in preprocessor to reject unknown types and return the image in the expected 4D format of tensor and on right device
support a list of everything as inputs to the pipeline, change type to PipelineImageInput
implement a check that all input list elements have the same dimensions
improve docstrings of pipeline outputs
remove check_input pipeline argument

* remove forgotten print

* add prediction_type model config

* add uncertainty visualization into export utils
fix NaN values in normals uncertainties

* change default of output_uncertainty to False
better handle the case of an attempt to export or visualize none

* fix `output_uncertainty=False`

* remove kwargs
fix check_inputs according to the new inputs of the pipeline

* rename prepare_latent into prepare_latents as in other pipelines
annotate prepare_latents in normals pipeline with "Copied from"
annotate encode_image in normals pipeline with "Copied from"

* move nested-capable `progress_bar` method into the pipelines
revert the original `progress_bar` method in pipeline_utils

* minor message improvement

* fix cpu offloading

* move colormap, visualize_depth, export_depth_to_16bit_png, visualize_normals, visualize_uncertainty to marigold_image_processing.py
update example docstrings

* fix missing comma

* change torch.FloatTensor to torch.Tensor

* fix importing of MarigoldImageProcessor

* fix vae offloading
fix batched image encoding
remove separate encode_image function and use vae.encode instead

* implement marigold's intial tests
relax generator checks in line with other pipelines
implement return_dict __call__ argument in line with other pipelines

* fix num_images computation

* remove MarigoldImageProcessor and outputs from import structure
update tests

* update docstrings

* update init

* update

* style

* fix

* fix

* up

* up

* up

* add simple test

* up

* update expected np input/output to be channel last

* move expand_tensor_or_array into the MarigoldImageProcessor

* rewrite tests to follow conventions - hardcoded slices instead of image artifacts
write more smoke tests

* add basic docs.

* add anton's contribution statement

* remove todos.

* fix assertion values for marigold depth slow tests

* fix assertion values for depth normals.

* remove print

* support AutoencoderTiny in the pipelines

* update documentation page
add Available Pipelines section
add Available Checkpoints section
add warning about num_inference_steps

* fix missing import in docstring
fix wrong value in visualize_depth docstring

* [doc] add marigold to pipelines overview

* [doc] add section "usage examples"

* fix an issue with latents check in the pipelines

* add "Frame-by-frame Video Processing with Consistency" section

* grammarly

* replace tables with images with css-styled images (blindly)

* style

* print

* fix the assertions.

* take from the github runner.

* take the slices from action artifacts

* style.

* update with the slices from the runner.

* remove unnecessary code blocks.

* Revert "[doc] add marigold to pipelines overview"

This reverts commit a505165150afd8dab23c474d1a054ea505a56a5f.

* remove invitation for new modalities

* split out marigold usage examples

* doc cleanup

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Co-authored-by: yiyixuxu <yixu310@gmail.com>
Co-authored-by: yiyixuxu <yixu310@gmail,com>
Co-authored-by: sayakpaul <spsayakpaul@gmail.com>

clean-up kendinsky 3.0

* finalize

* finalize

* finalize

* add slow test

* add slow test

* add slow test

* Fix more

* add slow test

* fix more

* fix more

* fix more

* fix more

* fix more

* fix more

* fix more

* fix more

* fix more

* Better

* Fix more

* Fix more

* add slow test

* Add auto pipelines

* add slow test

* Add all

* add slow test

* add slow test

* add slow test

* add slow test

* add slow test

* Apply suggestions from code review

* add slow test

* add slow test

* [Doc builder] Ensure slow import for doc builder

* Apply suggestions from code review

* env for doc builder

* fix more

* [Diffusers] Set import to slow as env variable

* fix docs

* fix docs

* Apply suggestions from code review

* Apply suggestions from code review

* fix docs

* fix docs

* [Utils] Correct custom init sort

* [Utils] Correct custom init sort

* [Utils] Correct custom init sort

* add type checking

* fix custom init sort

* fix test

* fix tests

---------
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>

* initial commit

* move modules to import struct

* add dummy objects and _LazyModule

* add lazy import to schedulers

* clean up unused imports

* lazy import on models module

* lazy import for schedulers module

* add lazy import to pipelines module

* lazy import altdiffusion

* lazy import audio diffusion

* lazy import audioldm

* lazy import consistency model

* lazy import controlnet

* lazy import dance diffusion ddim ddpm

* lazy import deepfloyd

* lazy import kandinksy

* lazy imports

* lazy import semantic diffusion

* lazy imports

* lazy import stable diffusion

* move sd output to its own module

* clean up

* lazy import t2iadapter

* lazy import unclip

* lazy import versatile and vq diffsuion

* lazy import vq diffusion

* helper to fetch objects from modules

* lazy import sdxl

* lazy import txt2vid

* lazy import stochastic karras

* fix model imports

* fix bug

* lazy import

* clean up

* clean up

* fixes for tests

* fixes for tests

* clean up

* remove import of torch_utils from utils module

* clean up

* clean up

* fix mistake import statement

* dedicated modules for exporting and loading

* remove testing utils from utils module

* fixes from  merge conflicts

* Update src/diffusers/pipelines/kandinsky2_2/__init__.py

* fix docs

* fix alt diffusion copied from

* fix check dummies

* fix more docs

* remove accelerate import from utils module

* add type checking

* make style

* fix check dummies

* remove torch import from xformers check

* clean up error message

* fixes after upstream merges

* dummy objects fix

* fix tests

* remove unused module import

---------
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* fix circular import

* fix imports when watermark not specified

* fix all pipelines

* start with stable diffusion

* fix

* finish stable diffusion pipelines

* fix path to pipeline output

* fix flax paths

* fix copies

* add up to score sde ve

* finish first pass of pipelines

* fix copies

* second review

* align doc titles

* more review fixes

* final review

* Add semantic guidance pipeline

* Fix style

* Refactor Pipeline

* Pipeline documentation

* Add documentation

* Fix style and quality

* Fix doctree

* Add tests for SEGA

* Update src/diffusers/pipelines/semantic_stable_diffusion/pipeline_semantic_stable_diffusion.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/diffusers/pipelines/semantic_stable_diffusion/pipeline_semantic_stable_diffusion.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/diffusers/pipelines/semantic_stable_diffusion/pipeline_semantic_stable_diffusion.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Make compatible with half precision

* Change deprecation warning to throw an exception

* update

---------
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* before running make style

* remove left overs from flake8

* finish

* make fix-copies

* final fix

* more fixes

* add conversion script for vae

* up

* up

* some fixes

* add text model

* use the correct config

* add docs

* move model in it's own file

* move model in its own file

* pass attenion mask to text encoder

* pass attn mask to uncond inputs

* quality

* fix image2image

* add imag2image in init

* fix import

* fix one more import

* fix import, dummy objetcs

* fix copied from

* up

* finish
Co-authored-by: patil-suraj <surajp815@gmail.com>