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Add object detection + segmentation transforms (#20003)

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* Add transforms for object detection

* Update src/transformers/image_transforms.py

Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Better var names & docstring

* Remove unused var desc in docstring

* Update src/transformers/image_transforms.py

Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
This commit is contained in:
amyeroberts
2022-11-15 12:50:03 +00:00
committed by GitHub
parent 163ac3d3ee
commit 4c7e8d0900
3 changed files with 228 additions and 2 deletions
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70
tests/test_image_transforms.py
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@@ -36,9 +36,13 @@ if is_vision_available():
from transformers.image_transforms import (
center_crop,
center_to_corners_format,
corners_to_center_format,
get_resize_output_image_size,
id_to_rgb,
normalize,
resize,
rgb_to_id,
to_channel_dimension_format,
to_pil_image,
)
@@ -178,6 +182,11 @@ class ImageTransformsTester(unittest.TestCase):
def test_normalize(self):
image = np.random.randint(0, 256, (224, 224, 3)) / 255
# Test that exception is raised if inputs are incorrect
# Not a numpy array image
with self.assertRaises(ValueError):
normalize(5, 5, 5)
# Number of mean values != number of channels
with self.assertRaises(ValueError):
normalize(image, mean=(0.5, 0.6), std=1)
@@ -219,3 +228,64 @@ class ImageTransformsTester(unittest.TestCase):
self.assertIsInstance(cropped_image, np.ndarray)
self.assertEqual(cropped_image.shape, (300, 260, 3))
self.assertTrue(np.allclose(cropped_image, expected_image))
def test_center_to_corners_format(self):
bbox_center = np.array([[10, 20, 4, 8], [15, 16, 3, 4]])
expected = np.array([[8, 16, 12, 24], [13.5, 14, 16.5, 18]])
self.assertTrue(np.allclose(center_to_corners_format(bbox_center), expected))
# Check that the function and inverse function are inverse of each other
self.assertTrue(np.allclose(corners_to_center_format(center_to_corners_format(bbox_center)), bbox_center))
def test_corners_to_center_format(self):
bbox_corners = np.array([[8, 16, 12, 24], [13.5, 14, 16.5, 18]])
expected = np.array([[10, 20, 4, 8], [15, 16, 3, 4]])
self.assertTrue(np.allclose(corners_to_center_format(bbox_corners), expected))
# Check that the function and inverse function are inverse of each other
self.assertTrue(np.allclose(center_to_corners_format(corners_to_center_format(bbox_corners)), bbox_corners))
def test_rgb_to_id(self):
# test list input
rgb = [125, 4, 255]
self.assertEqual(rgb_to_id(rgb), 16712829)
# test numpy array input
color = np.array(
[
[
[213, 54, 165],
[88, 207, 39],
[156, 108, 128],
],
[
[183, 194, 46],
[137, 58, 88],
[114, 131, 233],
],
]
)
expected = np.array([[10827477, 2608984, 8416412], [3064503, 5782153, 15303538]])
self.assertTrue(np.allclose(rgb_to_id(color), expected))
def test_id_to_rgb(self):
# test int input
self.assertEqual(id_to_rgb(16712829), [125, 4, 255])
# test array input
id_array = np.array([[10827477, 2608984, 8416412], [3064503, 5782153, 15303538]])
color = np.array(
[
[
[213, 54, 165],
[88, 207, 39],
[156, 108, 128],
],
[
[183, 194, 46],
[137, 58, 88],
[114, 131, 233],
],
]
)
self.assertTrue(np.allclose(id_to_rgb(id_array), color))