未验证 提交 e357cfdd 编写于 作者: W Wenyu 提交者: GitHub

update unittest for uint8 problem (#32790)

上级 5fc734ce
...@@ -525,10 +525,10 @@ class TestFunctional(unittest.TestCase): ...@@ -525,10 +525,10 @@ class TestFunctional(unittest.TestCase):
image_load('tmp.jpg', backend=1) image_load('tmp.jpg', backend=1)
def test_normalize(self): def test_normalize(self):
np_img = (np.random.rand(28, 24, 3)).astype('uint8') np_img = (np.random.rand(28, 24, 3) * 255).astype('uint8')
pil_img = Image.fromarray(np_img) pil_img = Image.fromarray(np_img)
tensor_img = F.to_tensor(pil_img) tensor_img = F.to_tensor(pil_img)
tensor_img_hwc = F.to_tensor(pil_img, data_format='HWC') tensor_img_hwc = F.to_tensor(pil_img, data_format='HWC') * 255
mean = [0.5, 0.5, 0.5] mean = [0.5, 0.5, 0.5]
std = [0.5, 0.5, 0.5] std = [0.5, 0.5, 0.5]
...@@ -539,17 +539,17 @@ class TestFunctional(unittest.TestCase): ...@@ -539,17 +539,17 @@ class TestFunctional(unittest.TestCase):
normalized_img_pil = F.normalize(pil_img, mean, std, data_format='HWC') normalized_img_pil = F.normalize(pil_img, mean, std, data_format='HWC')
normalized_img_np = F.normalize( normalized_img_np = F.normalize(
np_img, mean, std, data_format='HWC', to_rgb=True) np_img, mean, std, data_format='HWC', to_rgb=False)
np.testing.assert_almost_equal( np.testing.assert_almost_equal(
np.array(normalized_img_pil), normalized_img_np) np.array(normalized_img_pil), normalized_img_np)
np.testing.assert_almost_equal(normalized_img_tensor.numpy(), np.testing.assert_almost_equal(
normalized_img_np) normalized_img_tensor.numpy(), normalized_img_np, decimal=4)
def test_center_crop(self): def test_center_crop(self):
np_img = (np.random.rand(28, 24, 3)).astype('uint8') np_img = (np.random.rand(28, 24, 3) * 255).astype('uint8')
pil_img = Image.fromarray(np_img) pil_img = Image.fromarray(np_img)
tensor_img = F.to_tensor(pil_img, data_format='CHW') tensor_img = F.to_tensor(pil_img, data_format='CHW') * 255
np_cropped_img = F.center_crop(np_img, 4) np_cropped_img = F.center_crop(np_img, 4)
pil_cropped_img = F.center_crop(pil_img, 4) pil_cropped_img = F.center_crop(pil_img, 4)
...@@ -557,23 +557,25 @@ class TestFunctional(unittest.TestCase): ...@@ -557,23 +557,25 @@ class TestFunctional(unittest.TestCase):
np.testing.assert_almost_equal(np_cropped_img, np.testing.assert_almost_equal(np_cropped_img,
np.array(pil_cropped_img)) np.array(pil_cropped_img))
np.testing.assert_almost_equal(np_cropped_img, np.testing.assert_almost_equal(
tensor_cropped_img.numpy().transpose( np_cropped_img,
(1, 2, 0))) tensor_cropped_img.numpy().transpose((1, 2, 0)),
decimal=4)
def test_pad(self): def test_pad(self):
np_img = (np.random.rand(28, 24, 3)).astype('uint8') np_img = (np.random.rand(28, 24, 3) * 255).astype('uint8')
pil_img = Image.fromarray(np_img) pil_img = Image.fromarray(np_img)
tensor_img = F.to_tensor(pil_img, 'CHW') tensor_img = F.to_tensor(pil_img, 'CHW') * 255
np_padded_img = F.pad(np_img, [1, 2], padding_mode='reflect') np_padded_img = F.pad(np_img, [1, 2], padding_mode='reflect')
pil_padded_img = F.pad(pil_img, [1, 2], padding_mode='reflect') pil_padded_img = F.pad(pil_img, [1, 2], padding_mode='reflect')
tensor_padded_img = F.pad(tensor_img, [1, 2], padding_mode='reflect') tensor_padded_img = F.pad(tensor_img, [1, 2], padding_mode='reflect')
np.testing.assert_almost_equal(np_padded_img, np.array(pil_padded_img)) np.testing.assert_almost_equal(np_padded_img, np.array(pil_padded_img))
np.testing.assert_almost_equal(np_padded_img, np.testing.assert_almost_equal(
tensor_padded_img.numpy().transpose( np_padded_img,
(1, 2, 0))) tensor_padded_img.numpy().transpose((1, 2, 0)),
decimal=3)
tensor_padded_img = F.pad(tensor_img, 1, padding_mode='reflect') tensor_padded_img = F.pad(tensor_img, 1, padding_mode='reflect')
tensor_padded_img = F.pad(tensor_img, [1, 2, 1, 2], tensor_padded_img = F.pad(tensor_img, [1, 2, 1, 2],
...@@ -584,9 +586,9 @@ class TestFunctional(unittest.TestCase): ...@@ -584,9 +586,9 @@ class TestFunctional(unittest.TestCase):
pil_padded_img = F.pad(pil_p_img, [1, 2], padding_mode='reflect') pil_padded_img = F.pad(pil_p_img, [1, 2], padding_mode='reflect')
def test_resize(self): def test_resize(self):
np_img = (np.zeros([28, 24, 3])).astype('uint8') np_img = (np.zeros([28, 24, 3]) * 255).astype('uint8')
pil_img = Image.fromarray(np_img) pil_img = Image.fromarray(np_img)
tensor_img = F.to_tensor(pil_img, 'CHW') tensor_img = F.to_tensor(pil_img, 'CHW') * 255
np_reseized_img = F.resize(np_img, 40) np_reseized_img = F.resize(np_img, 40)
pil_reseized_img = F.resize(pil_img, 40) pil_reseized_img = F.resize(pil_img, 40)
...@@ -595,12 +597,14 @@ class TestFunctional(unittest.TestCase): ...@@ -595,12 +597,14 @@ class TestFunctional(unittest.TestCase):
np.testing.assert_almost_equal(np_reseized_img, np.testing.assert_almost_equal(np_reseized_img,
np.array(pil_reseized_img)) np.array(pil_reseized_img))
np.testing.assert_almost_equal(np_reseized_img, np.testing.assert_almost_equal(
tensor_reseized_img.numpy().transpose( np_reseized_img,
(1, 2, 0))) tensor_reseized_img.numpy().transpose((1, 2, 0)),
np.testing.assert_almost_equal(np_reseized_img, decimal=3)
tensor_reseized_img2.numpy().transpose( np.testing.assert_almost_equal(
(1, 2, 0))) np_reseized_img,
tensor_reseized_img2.numpy().transpose((1, 2, 0)),
decimal=3)
gray_img = (np.zeros([28, 32])).astype('uint8') gray_img = (np.zeros([28, 32])).astype('uint8')
gray_resize_img = F.resize(gray_img, 40) gray_resize_img = F.resize(gray_img, 40)
......
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