192 lines
8.0 KiB
Python
192 lines
8.0 KiB
Python
# Copyright 2021 The MediaPipe Authors.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""Tests for mediapipe.python._framework_bindings.image."""
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import gc
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import os
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import random
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import sys
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from absl.testing import absltest
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import cv2
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import numpy as np
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import PIL.Image
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# resources dependency
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from mediapipe.python._framework_bindings import image
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from mediapipe.python._framework_bindings import image_frame
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Image = image.Image
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ImageFormat = image_frame.ImageFormat
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# TODO: Add unit tests specifically for memory management.
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class ImageTest(absltest.TestCase):
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def test_create_image_from_gray_cv_mat(self):
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w, h = random.randrange(3, 100), random.randrange(3, 100)
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mat = cv2.cvtColor(
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np.random.randint(2**8 - 1, size=(h, w, 3), dtype=np.uint8),
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cv2.COLOR_RGB2GRAY)
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mat[2, 2] = 42
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gray8_image = Image(image_format=ImageFormat.GRAY8, data=mat)
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self.assertTrue(np.array_equal(mat, gray8_image.numpy_view()))
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with self.assertRaisesRegex(IndexError, 'index dimension mismatch'):
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print(gray8_image[w, h, 1])
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with self.assertRaisesRegex(IndexError, 'out of bounds'):
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print(gray8_image[w, h])
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self.assertEqual(42, gray8_image[2, 2])
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def test_create_image_from_rgb_cv_mat(self):
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w, h, channels = random.randrange(3, 100), random.randrange(3, 100), 3
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mat = cv2.cvtColor(
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np.random.randint(2**8 - 1, size=(h, w, channels), dtype=np.uint8),
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cv2.COLOR_RGB2BGR)
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mat[2, 2, 1] = 42
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rgb_image = Image(image_format=ImageFormat.SRGB, data=mat)
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self.assertTrue(np.array_equal(mat, rgb_image.numpy_view()))
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with self.assertRaisesRegex(IndexError, 'out of bounds'):
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print(rgb_image[w, h, channels])
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self.assertEqual(42, rgb_image[2, 2, 1])
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def test_create_image_from_rgb48_cv_mat(self):
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w, h, channels = random.randrange(3, 100), random.randrange(3, 100), 3
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mat = cv2.cvtColor(
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np.random.randint(2**16 - 1, size=(h, w, channels), dtype=np.uint16),
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cv2.COLOR_RGB2BGR)
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mat[2, 2, 1] = 42
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rgb48_image = Image(image_format=ImageFormat.SRGB48, data=mat)
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self.assertTrue(np.array_equal(mat, rgb48_image.numpy_view()))
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with self.assertRaisesRegex(IndexError, 'out of bounds'):
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print(rgb48_image[w, h, channels])
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self.assertEqual(42, rgb48_image[2, 2, 1])
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def test_create_image_from_gray_pil_image(self):
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w, h = random.randrange(3, 100), random.randrange(3, 100)
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img = PIL.Image.fromarray(
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np.random.randint(2**8 - 1, size=(h, w), dtype=np.uint8), 'L')
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gray8_image = Image(image_format=ImageFormat.GRAY8, data=np.asarray(img))
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self.assertTrue(np.array_equal(np.asarray(img), gray8_image.numpy_view()))
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with self.assertRaisesRegex(IndexError, 'index dimension mismatch'):
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print(gray8_image[w, h, 1])
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with self.assertRaisesRegex(IndexError, 'out of bounds'):
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print(gray8_image[w, h])
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def test_create_image_from_rgb_pil_image(self):
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w, h, channels = random.randrange(3, 100), random.randrange(3, 100), 3
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img = PIL.Image.fromarray(
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np.random.randint(2**8 - 1, size=(h, w, channels), dtype=np.uint8),
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'RGB')
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rgb_image = Image(image_format=ImageFormat.SRGB, data=np.asarray(img))
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self.assertTrue(np.array_equal(np.asarray(img), rgb_image.numpy_view()))
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with self.assertRaisesRegex(IndexError, 'out of bounds'):
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print(rgb_image[w, h, channels])
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def test_create_image_from_rgba64_pil_image(self):
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w, h, channels = random.randrange(3, 100), random.randrange(3, 100), 4
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img = PIL.Image.fromarray(
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np.random.randint(2**16 - 1, size=(h, w, channels), dtype=np.uint16),
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'RGBA')
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rgba_image = Image(
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image_format=ImageFormat.SRGBA64,
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data=np.asarray(img).astype(np.uint16))
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self.assertTrue(np.array_equal(np.asarray(img), rgba_image.numpy_view()))
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with self.assertRaisesRegex(IndexError, 'out of bounds'):
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print(rgba_image[1000, 1000, 1000])
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def test_image_numby_view(self):
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w, h, channels = random.randrange(3, 100), random.randrange(3, 100), 3
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mat = cv2.cvtColor(
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np.random.randint(2**8 - 1, size=(h, w, channels), dtype=np.uint8),
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cv2.COLOR_RGB2BGR)
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rgb_image = Image(image_format=ImageFormat.SRGB, data=mat)
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output_ndarray = rgb_image.numpy_view()
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self.assertTrue(np.array_equal(mat, rgb_image.numpy_view()))
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# The output of numpy_view() is a reference to the internal data and it's
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# unwritable after creation.
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with self.assertRaisesRegex(ValueError,
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'assignment destination is read-only'):
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output_ndarray[0, 0, 0] = 0
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copied_ndarray = np.copy(output_ndarray)
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copied_ndarray[0, 0, 0] = 0
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def test_cropped_gray8_image(self):
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w, h = random.randrange(20, 100), random.randrange(20, 100)
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channels, offset = 3, 10
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mat = cv2.cvtColor(
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np.random.randint(2**8 - 1, size=(h, w, channels), dtype=np.uint8),
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cv2.COLOR_RGB2GRAY)
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gray8_image = Image(
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image_format=ImageFormat.GRAY8,
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data=np.ascontiguousarray(mat[offset:-offset, offset:-offset]))
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self.assertTrue(
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np.array_equal(mat[offset:-offset, offset:-offset],
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gray8_image.numpy_view()))
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def test_cropped_rgb_image(self):
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w, h = random.randrange(20, 100), random.randrange(20, 100)
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channels, offset = 3, 10
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mat = cv2.cvtColor(
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np.random.randint(2**8 - 1, size=(h, w, channels), dtype=np.uint8),
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cv2.COLOR_RGB2BGR)
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rgb_image = Image(
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image_format=ImageFormat.SRGB,
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data=np.ascontiguousarray(mat[offset:-offset, offset:-offset, :]))
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self.assertTrue(
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np.array_equal(mat[offset:-offset, offset:-offset, :],
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rgb_image.numpy_view()))
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# For image frames that store contiguous data, the output of numpy_view()
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# points to the pixel data of the original image frame object. The life cycle
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# of the data array should tie to the image frame object.
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def test_image_numpy_view_with_contiguous_data(self):
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w, h = 640, 480
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mat = np.random.randint(2**8 - 1, size=(h, w, 3), dtype=np.uint8)
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rgb_image = Image(image_format=ImageFormat.SRGB, data=mat)
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self.assertTrue(rgb_image.is_contiguous())
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initial_ref_count = sys.getrefcount(rgb_image)
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self.assertTrue(np.array_equal(mat, rgb_image.numpy_view()))
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# Get 2 data array objects and verify that the image frame's ref count is
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# increased by 2.
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np_view = rgb_image.numpy_view()
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self.assertEqual(sys.getrefcount(rgb_image), initial_ref_count + 1)
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np_view2 = rgb_image.numpy_view()
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self.assertEqual(sys.getrefcount(rgb_image), initial_ref_count + 2)
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del np_view
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del np_view2
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gc.collect()
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# After the two data array objects getting destroyed, the current ref count
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# should euqal to the initial ref count.
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self.assertEqual(sys.getrefcount(rgb_image), initial_ref_count)
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# For image frames that store non contiguous data, the output of numpy_view()
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# stores a copy of the pixel data of the image frame object. The life cycle of
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# the data array doesn't tie to the image frame object.
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def test_image_numpy_view_with_non_contiguous_data(self):
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w, h = 641, 481
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mat = np.random.randint(2**8 - 1, size=(h, w, 3), dtype=np.uint8)
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rgb_image = Image(image_format=ImageFormat.SRGB, data=mat)
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self.assertFalse(rgb_image.is_contiguous())
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initial_ref_count = sys.getrefcount(rgb_image)
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self.assertTrue(np.array_equal(mat, rgb_image.numpy_view()))
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np_view = rgb_image.numpy_view()
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self.assertEqual(sys.getrefcount(rgb_image), initial_ref_count)
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del np_view
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gc.collect()
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self.assertEqual(sys.getrefcount(rgb_image), initial_ref_count)
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if __name__ == '__main__':
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absltest.main()
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