GitLab

* BLIP preprocess

* BIT preprocess

* BRIDGETOWER preprocess

* CHAMELEON preprocess

* CHINESE_CLIP preprocess

* CONVNEXT preprocess

* DEIT preprocess

* DONUT preprocess

* DPT preprocess

* FLAVA preprocess

* EFFICIENTNET preprocess

* FUYU preprocess

* GLPN preprocess

* IMAGEGPT preprocess

* INTRUCTBLIPVIDEO preprocess

* VIVIT preprocess

* ZOEDEPTH preprocess

* VITMATTE preprocess

* VIT preprocess

* VILT preprocess

* VIDEOMAE preprocess

* VIDEOLLAVA

* TVP processing

* TVP fixup

* SWIN2SR preprocess

* SIGLIP preprocess

* SAM preprocess

* RT-DETR preprocess

* PVT preprocess

* POOLFORMER preprocess

* PERCEIVER preprocess

* OWLVIT preprocess

* OWLV2 preprocess

* NOUGAT preprocess

* MOBILEVIT preprocess

* MOBILENETV2 preprocess

* MOBILENETV1 preprocess

* LEVIT preprocess

* LAYOUTLMV2 preprocess

* LAYOUTLMV3 preprocess

* Add test

* Update tests

* Draft fast image processors

* Draft working fast version

* py3.8 compatible cache

* Enable loading fast image processors through auto

* Tidy up; rescale behaviour based on input type

* Enable tests for fast image processors

* Smarter rescaling

* Don't default to Fast

* Safer imports

* Add necessary Pillow requirement

* Woops

* Add AutoImageProcessor test

* Fix up

* Fix test for imagegpt

* Fix test

* Review comments

* Add warning for TF and JAX input types

* Rearrange

* Return transforms

* NumpyToTensor transformation

* Rebase - include changes from upstream in ImageProcessingMixin

* Safe typing

* Fix up

* convert mean/std to tesnor to rescale

* Don't store transforms in state

* Fix up

* Update src/transformers/image_processing_utils_fast.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Update src/transformers/models/auto/image_processing_auto.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Update src/transformers/models/auto/image_processing_auto.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Update src/transformers/models/auto/image_processing_auto.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Warn if fast image processor available

* Update src/transformers/models/vit/image_processing_vit_fast.py

* Transpose incoming numpy images to be in CHW format

* Update mapping names based on packages, auto set fast to None

* Fix up

* Fix

* Add AutoImageProcessor.from_pretrained(checkpoint, use_fast=True) test

* Update src/transformers/models/vit/image_processing_vit_fast.py
Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com>

* Add equivalence and speed tests

* Fix up

---------
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com>

* Add conversion script

* Add NougatImageProcessor

* Add crop margin

* More improvements

* Add docs, READMEs

* Remove print statements

* Include model_max_length

* Add NougatTokenizerFast

* Fix imports

* Improve postprocessing

* Improve image processor

* Fix image processor

* Improve normalize method

* More improvements

* More improvements

* Add processor, improve docs

* Simplify fast tokenizer

* Remove test file

* Fix docstrings

* Use NougatProcessor in conversion script

* Add is_levensthein_available

* Add tokenizer tests

* More improvements

* Use numpy instead of opencv

* Add is_cv2_available

* Fix cv2_available

* Add is_nltk_available

* Add image processor tests, improve crop_margin

* Add integration tests

* Improve integration test

* Use do_rescale instead of hacks, thanks Amy

* Remove random_padding

* Address comments

* Address more comments

* Add import

* Address more comments

* Address more comments

* Address comment

* Address comment

* Set max_model_input_sizes

* Add tests

* Add requires_backends

* Add Nougat to exotic tests

* Use to_pil_image

* Address comment regarding nltk

* Add NLTK

* Improve variable names, integration test

* Add test

* refactor, document, and test regexes

* remove named capture groups, add comments

* format

* add non-markdown fixed tokenization

* format

* correct flakyness of args parse

* add regex comments

* test functionalities for crop_image, align long axis and expected output

* add regex tests

* remove cv2 dependency

* test crop_margin equality between cv2 and python

* refactor table regexes to markdown

add newline

* change print to log, improve doc

* fix high count tables correction

* address PR comments: naming, linting, asserts

* Address comments

* Add copied from

* Update conversion script

* Update conversion script to convert both small and base versions

* Add inference example

* Add more info

* Fix style

* Add require annotators to test

* Define all keyword arguments explicitly

* Move cv2 annotator

* Add tokenizer init method

* Transfer checkpoints

* Add reference to Donut

* Address comments

* Skip test

* Remove cv2 method

* Add copied from statements

* Use cached_property

* Fix docstring

* Add file to not doctested

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Co-authored-by: Pablo Montalvo <pablo.montalvo.leroux@gmail.com>