Add Image Processors (#19796)
* Add CLIP image processor * Crop size as dict too * Update warning * Actually use logger this time * Normalize doesn't change dtype of input * Add perceiver image processor * Tidy up * Add DPT image processor * Add Vilt image processor * Tidy up * Add poolformer image processor * Tidy up * Add LayoutLM v2 and v3 imsge processors * Tidy up * Add Flava image processor * Tidy up * Add deit image processor * Tidy up * Add ConvNext image processor * Tidy up * Add levit image processor * Add segformer image processor * Add in post processing * Fix up * Add ImageGPT image processor * Fixup * Add mobilevit image processor * Tidy up * Add postprocessing * Fixup * Add VideoMAE image processor * Tidy up * Add ImageGPT image processor * Fixup * Add ViT image processor * Tidy up * Add beit image processor * Add mobilevit image processor * Tidy up * Add postprocessing * Fixup * Fix up * Fix flava and remove tree module * Fix image classification pipeline failing tests * Update feature extractor in trainer scripts * Update pad_if_smaller to accept tuple and int size * Update for image segmentation pipeline * Update src/transformers/models/perceiver/image_processing_perceiver.py Co-authored-by: Alara Dirik <8944735+alaradirik@users.noreply.github.com> * Update src/transformers/image_processing_utils.py Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * Update src/transformers/models/beit/image_processing_beit.py Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * PR comments - docstrings; remove accidentally added resize; var names * Update docstrings * Add exception if size is not in the right format * Fix exception check * Fix up * Use shortest_edge in tuple in script Co-authored-by: Alara Dirik <8944735+alaradirik@users.noreply.github.com> Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
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@@ -32,7 +32,7 @@ if is_vision_available():
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from PIL import Image
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from transformers import FlavaFeatureExtractor, FlavaProcessor
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from transformers.models.flava.feature_extraction_flava import (
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from transformers.models.flava.image_processing_flava import (
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FLAVA_CODEBOOK_MEAN,
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FLAVA_CODEBOOK_STD,
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FLAVA_IMAGE_MEAN,
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@@ -69,7 +69,6 @@ class FlavaProcessorTest(unittest.TestCase):
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"mask_group_max_aspect_ratio": None,
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"codebook_do_resize": True,
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"codebook_size": 112,
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"codebook_resample": None,
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"codebook_do_center_crop": True,
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"codebook_crop_size": 112,
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"codebook_do_map_pixels": True,
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