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Fix a couple of typos and add an illustrative test (#26941)

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* fix a typo and add an illustrative test

* appease black

* reduce code duplication and add Annotion type back with a pending deprecation warning

* remove unused code

* change warning type

* black formatting fix

* change enum deprecation approach to support 3.8 and earlier

* add stacklevel

* fix black issue

* fix ruff issues

* fix ruff issues

* move tests to own mixin

* include yolos

* fix black formatting issue

* fix black formatting issue

* use logger instead of warnings and include target version for deprecation
This commit is contained in:
rjenc29
2023-12-11 15:51:51 +00:00
committed by GitHub
parent 39acfe84ba
commit 7e35f37071
12 changed files with 279 additions and 191 deletions
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61
tests/models/detr/test_image_processing_detr.py
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@@ -21,7 +21,7 @@ import unittest
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingTestMixin, prepare_image_inputs
from ...test_image_processing_common import AnnotationFormatTestMixin, ImageProcessingTestMixin, prepare_image_inputs
if is_torch_available():
@@ -127,7 +127,7 @@ class DetrImageProcessingTester(unittest.TestCase):
@require_torch
@require_vision
class DetrImageProcessingTest(ImageProcessingTestMixin, unittest.TestCase):
class DetrImageProcessingTest(AnnotationFormatTestMixin, ImageProcessingTestMixin, unittest.TestCase):
image_processing_class = DetrImageProcessor if is_vision_available() else None
def setUp(self):
@@ -159,6 +159,63 @@ class DetrImageProcessingTest(ImageProcessingTestMixin, unittest.TestCase):
self.assertEqual(image_processor.size, {"shortest_edge": 42, "longest_edge": 84})
self.assertEqual(image_processor.do_pad, False)
def test_should_raise_if_annotation_format_invalid(self):
image_processor_dict = self.image_processor_tester.prepare_image_processor_dict()
with open("./tests/fixtures/tests_samples/COCO/coco_annotations.txt", "r") as f:
detection_target = json.loads(f.read())
annotations = {"image_id": 39769, "annotations": detection_target}
params = {
"images": Image.open("./tests/fixtures/tests_samples/COCO/000000039769.png"),
"annotations": annotations,
"return_tensors": "pt",
}
image_processor_params = {**image_processor_dict, **{"format": "_INVALID_FORMAT_"}}
image_processor = self.image_processing_class(**image_processor_params)
with self.assertRaises(ValueError) as e:
image_processor(**params)
self.assertTrue(str(e.exception).startswith("_INVALID_FORMAT_ is not a valid AnnotationFormat"))
def test_valid_coco_detection_annotations(self):
# prepare image and target
image = Image.open("./tests/fixtures/tests_samples/COCO/000000039769.png")
with open("./tests/fixtures/tests_samples/COCO/coco_annotations.txt", "r") as f:
target = json.loads(f.read())
params = {"image_id": 39769, "annotations": target}
# encode them
image_processing = DetrImageProcessor.from_pretrained("facebook/detr-resnet-50")
# legal encodings (single image)
_ = image_processing(images=image, annotations=params, return_tensors="pt")
_ = image_processing(images=image, annotations=[params], return_tensors="pt")
# legal encodings (batch of one image)
_ = image_processing(images=[image], annotations=params, return_tensors="pt")
_ = image_processing(images=[image], annotations=[params], return_tensors="pt")
# legal encoding (batch of more than one image)
n = 5
_ = image_processing(images=[image] * n, annotations=[params] * n, return_tensors="pt")
# example of an illegal encoding (missing the 'image_id' key)
with self.assertRaises(ValueError) as e:
image_processing(images=image, annotations={"annotations": target}, return_tensors="pt")
self.assertTrue(str(e.exception).startswith("Invalid COCO detection annotations"))
# example of an illegal encoding (unequal lengths of images and annotations)
with self.assertRaises(ValueError) as e:
image_processing(images=[image] * n, annotations=[params] * (n - 1), return_tensors="pt")
self.assertTrue(str(e.exception) == "The number of images (5) and annotations (4) do not match.")
@slow
def test_call_pytorch_with_coco_detection_annotations(self):
# prepare image and target