def test_hue():
img = image_loader(os.path.join(TEST_DATA_PATH, "images", "flower2.jpg"))
transform = Hue()
res_img = transform(img)
assert np.array(res_img)[100][0] == 39
def test_compose():
img = image_loader(os.path.join(TEST_DATA_PATH, "images", "flower2.jpg"))
transforms = ComposeTransforms([Saturation(), np.mean])
res_compose = transforms(img)
transform_sat_only = Saturation()
res_img = transform_sat_only(img)
# compute average brightness
res = np.mean(res_img)
assert res == res_compose
def test_simple_blur(image_files):
expected_results = [3754.4, 1392.5, 13544.2, ]
transform = SimpleBlur()
for idx, eachimg in enumerate(image_files):
img = image_loader(eachimg)
res = transform(img)
# compute average brightness
assert pytest.approx(res, 0.1) == expected_results[idx]
def test_Brightness():
img = image_loader(os.path.join(TEST_DATA_PATH, "images", "flower2.jpg"))
transform = Brightness()
res_img = transform(img)
# compute average brightness
res = np.mean(res_img)
assert pytest.approx(res, 0.1) == 117.1
res_img = transform(np.array(img))
# compute average brightness
res = np.mean(res_img)
assert pytest.approx(res, 0.1) == 117.1
def test_simple_blur(image_files):
expected_results = [
3754.4,
449.4,
700.7,
1392.5,
382.6,
239.1,
300.9,
851.9,
594.9,
729.9,
895.8,
13544.2,
]
transform = SimpleBlur()
for idx, eachimg in enumerate(image_files):
img = image_loader(eachimg)
res = transform(img)
assert pytest.approx(res, 0.1) == expected_results[
idx], f"index:{idx} res:{res} expected: {expected_results[idx]}"