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| from __future__ import absolute_import, division | |
| import unittest | |
| import numpy as np | |
| import pytest | |
| from PIL import Image | |
| from davisinteractive.utils.visualization import ( | |
| _pascal_color_map, draw_scribble, overlay_mask, plot_scribble) | |
| import matplotlib # isort:skip | |
| matplotlib.use('Agg') | |
| import matplotlib.pyplot as plt # isort:skip | |
| class TestPascalColormap(unittest.TestCase): | |
| def test_default(self): | |
| colormap = _pascal_color_map() | |
| assert colormap.shape == (256, 3) | |
| assert colormap.dtype == np.uint8 | |
| assert np.all(colormap[0] == [0, 0, 0]) | |
| assert np.all(colormap[1] == [128, 0, 0]) | |
| assert np.all(colormap[2] == [0, 128, 0]) | |
| assert np.all(colormap[3] == [128, 128, 0]) | |
| assert np.all(colormap[255] == [224, 224, 192]) | |
| def test_normalized(self): | |
| colormap = _pascal_color_map(normalized=True) | |
| assert colormap.shape == (256, 3) | |
| assert colormap.dtype == np.float32 | |
| assert np.all(np.isclose(colormap[0], [0, 0, 0])) | |
| assert np.all(np.isclose(colormap[1], [128 / 255, 0, 0])) | |
| assert np.all(np.isclose(colormap[2], [0, 128 / 255, 0])) | |
| assert np.all(np.isclose(colormap[3], [128 / 255, 128 / 255, 0])) | |
| assert np.all( | |
| np.isclose(colormap[255], [224 / 255, 224 / 255, 192 / 255])) | |
| class TestPlotScribble(unittest.TestCase): | |
| def test_plot(self): | |
| scribble = { | |
| 'scribbles': [[], [{ | |
| 'path': [[0, 0], [0, 0.1]], | |
| 'object_id': 1, | |
| 'start_time': 0, | |
| 'end_time': 1000 | |
| }, { | |
| 'path': [[0, 0], [0, 0.1]], | |
| 'object_id': 1, | |
| 'start_time': 0, | |
| 'end_time': 1000 | |
| }], [], [], [{ | |
| 'path': [[0, 0], [0, 0.1]], | |
| 'object_id': 2, | |
| 'start_time': 0, | |
| 'end_time': 1000 | |
| }, { | |
| 'path': [[0, 0], [0, 0.1]], | |
| 'object_id': 3, | |
| 'start_time': 0, | |
| 'end_time': 1000 | |
| }], [{ | |
| 'path': [[0, 0], [0, 0.1]], | |
| 'object_id': 2, | |
| 'start_time': 0, | |
| 'end_time': 1000 | |
| }], []], | |
| 'sequence': | |
| 'test', | |
| } | |
| _, ax = plt.subplots(1) | |
| plot_scribble(ax, scribble, 1, output_size=(100, 200)) | |
| plot_scribble(ax, scribble, 1) | |
| with pytest.raises(ValueError): | |
| plot_scribble(ax, scribble, 10) | |
| class TestDrawScribble(unittest.TestCase): | |
| def test_draw(self): | |
| scribble = { | |
| 'scribbles': [[], [{ | |
| 'path': [[0, 0], [0, 0.1]], | |
| 'object_id': 1, | |
| 'start_time': 0, | |
| 'end_time': 1000 | |
| }, { | |
| 'path': [[0, 0], [0, 0.1]], | |
| 'object_id': 1, | |
| 'start_time': 0, | |
| 'end_time': 1000 | |
| }], [], [], [{ | |
| 'path': [[0, 0], [0, 0.1]], | |
| 'object_id': 2, | |
| 'start_time': 0, | |
| 'end_time': 1000 | |
| }, { | |
| 'path': [[0, 0], [0, 0.1]], | |
| 'object_id': 3, | |
| 'start_time': 0, | |
| 'end_time': 1000 | |
| }], [{ | |
| 'path': [[0, 0], [0, 0.1]], | |
| 'object_id': 2, | |
| 'start_time': 0, | |
| 'end_time': 1000 | |
| }], []], | |
| 'sequence': | |
| 'test', | |
| } | |
| img = Image.fromarray(np.zeros((480, 854, 3), dtype=np.uint8)) | |
| img_draw = draw_scribble(img, scribble, 1) | |
| img_draw = draw_scribble(img, scribble, 0) | |
| self.assertEqual(img_draw, img) | |
| class TestOverlay(unittest.TestCase): | |
| def test_shape_mismatch(self): | |
| im = np.random.randint(0, 255, (100, 200, 3), dtype=np.uint8) | |
| ann = np.zeros((100, 201)) | |
| with pytest.raises(ValueError): | |
| overlay_mask(im, ann) | |
| def test_wrong_channel_dimensions(self): | |
| im = np.random.randint(0, 255, (100, 200, 4), dtype=np.uint8) | |
| ann = np.zeros((100, 200)) | |
| with pytest.raises(ValueError): | |
| overlay_mask(im, ann) | |
| def test_empty_mask(self): | |
| im = np.random.randint(0, 255, (100, 200, 3), dtype=np.uint8) | |
| ann = np.zeros((100, 200)) | |
| img = overlay_mask(im, ann) | |
| assert img.shape == im.shape | |
| assert img.dtype == im.dtype | |
| assert np.all(img == im) | |
| def test_full_mask(self): | |
| im = np.random.randint(0, 255, (100, 200, 3), dtype=np.uint8) | |
| ann = np.ones((100, 200)) | |
| img = overlay_mask(im, ann, alpha=1.) | |
| assert img.shape == im.shape | |
| assert img.dtype == im.dtype | |
| assert np.all(img == im) | |
| img = overlay_mask(im, ann, alpha=0.) | |
| assert img.shape == im.shape | |
| assert img.dtype == im.dtype | |
| assert np.all(img == [128, 0, 0]) | |
| img = overlay_mask(im, ann, alpha=0., colors=[[45, 43, 76], [1, 2, 3]]) | |
| assert img.shape == im.shape | |
| assert img.dtype == im.dtype | |
| assert np.all(img == [1, 2, 3]) | |
| def test_mask(self): | |
| im = np.random.randint(0, 255, (100, 200, 3), dtype=np.uint8) | |
| ann = np.zeros((100, 200)) | |
| ann[50:70, 50:150] = 1 | |
| img = overlay_mask(im, ann, alpha=.5) | |
| assert img.shape == im.shape | |
| assert img.dtype == im.dtype | |
| assert np.all(img[ann == 0] == im[ann == 0]) | |
| assert not np.all(img[ann != 0] == im[ann != 0]) | |