def test_edgeBackgroundYBelow0_stretch(self):
roi = [0, 40, 10, 60]
# Compare patches.
actual_patch, transform = utilBoxes.cropPatch(self.image,
roi,
'background',
target_height=40,
target_width=40)
expected_patch = TestCropPatch.makeGradientImage(height=30,
width=40,
min_y=0,
min_x=40,
max_y=15,
max_x=60)
expected_patch = np.pad(expected_patch,
pad_width=((10, 0), (0, 0), (0, 0)),
mode='constant')
norm = (actual_patch.mean() + expected_patch.mean()) / 2.
actual_patch = actual_patch / norm
expected_patch = expected_patch / norm
np.testing.assert_array_almost_equal(actual_patch,
expected_patch,
decimal=0)
# Compare roi.
actual_roi = TestCropPatch.transformRoi(transform, roi)
expected_roi = [10, 0, 30, 40]
self.assertEqual(actual_roi, expected_roi)
def test_edgeOriginal_float(self):
roi = [40.6, 30, 60, 70.6]
# Compare patches.
actual_patch, transform = utilBoxes.cropPatch(self.image, roi,
'original', None, None)
expected_patch = TestCropPatch.makeGradientImage(height=19,
width=41,
min_y=41,
min_x=30)
np.testing.assert_array_equal(actual_patch, expected_patch)
# Compare roi.
actual_roi = TestCropPatch.transformRoi(transform, roi)
expected_roi = [0, 0, 19, 41]
self.assertEqual(actual_roi, expected_roi)
def test_edgeOriginal_identity(self):
roi = [0, 0, self.HEIGHT, self.WIDTH]
# Compare patches.
actual_patch, transform = utilBoxes.cropPatch(self.image, roi,
'original', None, None)
expected_patch = TestCropPatch.makeGradientImage(
self.HEIGHT, self.WIDTH)
np.testing.assert_array_equal(actual_patch, expected_patch)
# Compare roi.
actual_roi = TestCropPatch.transformRoi(transform, roi)
expected_roi = roi
self.assertEqual(actual_roi, expected_roi)
# Make sure transform matches.
np.testing.assert_array_equal(transform, np.eye(3, 3, dtype=float))
def test_edgeOriginal_outOfBoundary4(self):
roi = [40, 170, 60, 210]
# Compare patches.
actual_patch, transform = utilBoxes.cropPatch(self.image, roi,
'original', None, None)
expected_patch = TestCropPatch.makeGradientImage(height=20,
width=30,
min_y=40,
min_x=170)
expected_patch = np.pad(expected_patch, ((0, 0), (0, 10), (0, 0)))
self.assertEqual(actual_patch.shape, expected_patch.shape)
np.testing.assert_array_equal(actual_patch, expected_patch)
# Compare roi.
actual_roi = TestCropPatch.transformRoi(transform, roi)
expected_roi = [0, 0, 20, 40]
self.assertEqual(actual_roi, expected_roi)
def test_edgeBackgroundX_noStretch(self):
roi = [40, 45, 60, 55]
# Compare patches.
actual_patch, transform = utilBoxes.cropPatch(self.image,
roi,
'background',
target_height=20,
target_width=20)
expected_patch = TestCropPatch.makeGradientImage(height=20,
width=20,
min_y=40,
min_x=40)
np.testing.assert_array_equal(actual_patch, expected_patch)
# Compare roi.
actual_roi = TestCropPatch.transformRoi(transform, roi)
expected_roi = [0, 5, 20, 15]
self.assertEqual(actual_roi, expected_roi)
def test_edgeDistortY(self):
roi = [45, 40, 55, 60]
# Compare patches.
actual_patch, transform = utilBoxes.cropPatch(self.image,
roi,
'distort',
target_height=20,
target_width=20)
expected_patch = TestCropPatch.makeGradientImage(height=20,
width=20,
min_y=45,
min_x=40,
max_y=55)
np.testing.assert_array_equal(actual_patch, expected_patch)
# Compare roi.
actual_roi = TestCropPatch.transformRoi(transform, roi)
expected_roi = [0, 0, 20, 20]
self.assertEqual(actual_roi, expected_roi)
def test_edgeBackgroundXBelow0_noStretch(self):
roi = [40, 0, 60, 10]
# Compare patches.
actual_patch, transform = utilBoxes.cropPatch(self.image,
roi,
'background',
target_height=20,
target_width=20)
expected_patch = TestCropPatch.makeGradientImage(height=20,
width=15,
min_y=40)
expected_patch = np.pad(expected_patch,
pad_width=((0, 0), (5, 0), (0, 0)),
mode='constant')
np.testing.assert_array_equal(actual_patch, expected_patch)
# Compare roi.
actual_roi = TestCropPatch.transformRoi(transform, roi)
expected_roi = [0, 5, 20, 15]
self.assertEqual(actual_roi, expected_roi)
def test_edgeConstant_noStretch(self):
roi = [40, 30, 60, 70]
# Compare patches.
actual_patch, transform = utilBoxes.cropPatch(self.image,
roi,
'constant',
target_height=40,
target_width=40)
expected_patch = TestCropPatch.makeGradientImage(height=20,
width=40,
min_y=40,
min_x=30)
expected_patch = np.pad(expected_patch,
pad_width=((10, 10), (0, 0), (0, 0)),
mode='constant')
np.testing.assert_array_equal(actual_patch, expected_patch)
# Compare roi.
actual_roi = TestCropPatch.transformRoi(transform, roi)
expected_roi = [10, 0, 30, 40]
self.assertEqual(actual_roi, expected_roi)
def test_edgeConstant_allImage_noPad(self):
HEIGHT = 4
WIDTH = 10
roi = [0, 0, HEIGHT, WIDTH]
actual_patch, transform = utilBoxes.cropPatch(self.image[0:HEIGHT,
0:WIDTH],
roi,
'constant',
target_height=HEIGHT * 2,
target_width=WIDTH)
expected_patch = TestCropPatch.makeGradientImage(height=HEIGHT,
width=WIDTH,
min_y=0,
min_x=0)
expected_patch = np.pad(expected_patch,
pad_width=((HEIGHT // 2, HEIGHT // 2), (0, 0),
(0, 0)),
mode='constant')
self.assertEqual(actual_patch.shape, expected_patch.shape)
np.testing.assert_array_equal(actual_patch, expected_patch)
# Compare roi.
actual_roi = TestCropPatch.transformRoi(transform, roi)
expected_roi = [HEIGHT // 2, 0, HEIGHT * 3 // 2, WIDTH]
self.assertEqual(actual_roi, expected_roi)
def test_edgeConstant_targetSizeNone(self):
roi = [40, 30, 60, 70]
with self.assertRaises(RuntimeError):
utilBoxes.cropPatch(self.image, roi, 'constant', None, None)