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Add Image Processors (#19796)

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* 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>
This commit is contained in:
amyeroberts
2022-11-02 11:57:36 +00:00
committed by GitHub
parent 2e3452af0f
commit a6b7759880
65 changed files with 7060 additions and 3590 deletions
Download Patch File Download Diff File Expand all files Collapse all files

67
tests/models/segformer/test_feature_extraction_segformer.py
View File

@@ -43,12 +43,13 @@ class SegformerFeatureExtractionTester(unittest.TestCase):
min_resolution=30,
max_resolution=400,
do_resize=True,
size=30,
size=None,
do_normalize=True,
image_mean=[0.5, 0.5, 0.5],
image_std=[0.5, 0.5, 0.5],
reduce_labels=False,
do_reduce_labels=False,
):
size = size if size is not None else {"height": 30, "width": 30}
self.parent = parent
self.batch_size = batch_size
self.num_channels = num_channels
@@ -59,7 +60,7 @@ class SegformerFeatureExtractionTester(unittest.TestCase):
self.do_normalize = do_normalize
self.image_mean = image_mean
self.image_std = image_std
self.reduce_labels = reduce_labels
self.do_reduce_labels = do_reduce_labels
def prepare_feat_extract_dict(self):
return {
@@ -68,7 +69,7 @@ class SegformerFeatureExtractionTester(unittest.TestCase):
"do_normalize": self.do_normalize,
"image_mean": self.image_mean,
"image_std": self.image_std,
"reduce_labels": self.reduce_labels,
"do_reduce_labels": self.do_reduce_labels,
}
@@ -112,7 +113,7 @@ class SegformerFeatureExtractionTest(FeatureExtractionSavingTestMixin, unittest.
self.assertTrue(hasattr(feature_extractor, "do_normalize"))
self.assertTrue(hasattr(feature_extractor, "image_mean"))
self.assertTrue(hasattr(feature_extractor, "image_std"))
self.assertTrue(hasattr(feature_extractor, "reduce_labels"))
self.assertTrue(hasattr(feature_extractor, "do_reduce_labels"))
def test_batch_feature(self):
pass
@@ -132,8 +133,8 @@ class SegformerFeatureExtractionTest(FeatureExtractionSavingTestMixin, unittest.
(
1,
self.feature_extract_tester.num_channels,
self.feature_extract_tester.size,
self.feature_extract_tester.size,
self.feature_extract_tester.size["height"],
self.feature_extract_tester.size["width"],
),
)
@@ -144,8 +145,8 @@ class SegformerFeatureExtractionTest(FeatureExtractionSavingTestMixin, unittest.
(
self.feature_extract_tester.batch_size,
self.feature_extract_tester.num_channels,
self.feature_extract_tester.size,
self.feature_extract_tester.size,
self.feature_extract_tester.size["height"],
self.feature_extract_tester.size["width"],
),
)
@@ -164,8 +165,8 @@ class SegformerFeatureExtractionTest(FeatureExtractionSavingTestMixin, unittest.
(
1,
self.feature_extract_tester.num_channels,
self.feature_extract_tester.size,
self.feature_extract_tester.size,
self.feature_extract_tester.size["height"],
self.feature_extract_tester.size["width"],
),
)
@@ -176,8 +177,8 @@ class SegformerFeatureExtractionTest(FeatureExtractionSavingTestMixin, unittest.
(
self.feature_extract_tester.batch_size,
self.feature_extract_tester.num_channels,
self.feature_extract_tester.size,
self.feature_extract_tester.size,
self.feature_extract_tester.size["height"],
self.feature_extract_tester.size["width"],
),
)
@@ -196,8 +197,8 @@ class SegformerFeatureExtractionTest(FeatureExtractionSavingTestMixin, unittest.
(
1,
self.feature_extract_tester.num_channels,
self.feature_extract_tester.size,
self.feature_extract_tester.size,
self.feature_extract_tester.size["height"],
self.feature_extract_tester.size["width"],
),
)
@@ -208,8 +209,8 @@ class SegformerFeatureExtractionTest(FeatureExtractionSavingTestMixin, unittest.
(
self.feature_extract_tester.batch_size,
self.feature_extract_tester.num_channels,
self.feature_extract_tester.size,
self.feature_extract_tester.size,
self.feature_extract_tester.size["height"],
self.feature_extract_tester.size["width"],
),
)
@@ -230,16 +231,16 @@ class SegformerFeatureExtractionTest(FeatureExtractionSavingTestMixin, unittest.
(
1,
self.feature_extract_tester.num_channels,
self.feature_extract_tester.size,
self.feature_extract_tester.size,
self.feature_extract_tester.size["height"],
self.feature_extract_tester.size["width"],
),
)
self.assertEqual(
encoding["labels"].shape,
(
1,
self.feature_extract_tester.size,
self.feature_extract_tester.size,
self.feature_extract_tester.size["height"],
self.feature_extract_tester.size["width"],
),
)
self.assertEqual(encoding["labels"].dtype, torch.long)
@@ -253,16 +254,16 @@ class SegformerFeatureExtractionTest(FeatureExtractionSavingTestMixin, unittest.
(
self.feature_extract_tester.batch_size,
self.feature_extract_tester.num_channels,
self.feature_extract_tester.size,
self.feature_extract_tester.size,
self.feature_extract_tester.size["height"],
self.feature_extract_tester.size["width"],
),
)
self.assertEqual(
encoding["labels"].shape,
(
self.feature_extract_tester.batch_size,
self.feature_extract_tester.size,
self.feature_extract_tester.size,
self.feature_extract_tester.size["height"],
self.feature_extract_tester.size["width"],
),
)
self.assertEqual(encoding["labels"].dtype, torch.long)
@@ -278,16 +279,16 @@ class SegformerFeatureExtractionTest(FeatureExtractionSavingTestMixin, unittest.
(
1,
self.feature_extract_tester.num_channels,
self.feature_extract_tester.size,
self.feature_extract_tester.size,
self.feature_extract_tester.size["height"],
self.feature_extract_tester.size["width"],
),
)
self.assertEqual(
encoding["labels"].shape,
(
1,
self.feature_extract_tester.size,
self.feature_extract_tester.size,
self.feature_extract_tester.size["height"],
self.feature_extract_tester.size["width"],
),
)
self.assertEqual(encoding["labels"].dtype, torch.long)
@@ -303,16 +304,16 @@ class SegformerFeatureExtractionTest(FeatureExtractionSavingTestMixin, unittest.
(
2,
self.feature_extract_tester.num_channels,
self.feature_extract_tester.size,
self.feature_extract_tester.size,
self.feature_extract_tester.size["height"],
self.feature_extract_tester.size["width"],
),
)
self.assertEqual(
encoding["labels"].shape,
(
2,
self.feature_extract_tester.size,
self.feature_extract_tester.size,
self.feature_extract_tester.size["height"],
self.feature_extract_tester.size["width"],
),
)
self.assertEqual(encoding["labels"].dtype, torch.long)