def test_grayscale(self):
trans = transforms.Compose([transforms.Grayscale()])
self.do_transform(trans)
trans_gray = transforms.Grayscale()
fake_img = self.create_image((500, 400, 3))
fake_img_gray = trans_gray(fake_img)
np.testing.assert_equal(self.get_shape(fake_img_gray)[1], 500)
np.testing.assert_equal(self.get_shape(fake_img_gray)[2], 400)
trans_gray3 = transforms.Grayscale(3)
fake_img = self.create_image((500, 400, 3))
fake_img_gray = trans_gray3(fake_img)
def test_grayscale(self):
trans = transforms.Compose([transforms.Grayscale()])
self.do_transform(trans)
trans_gray = transforms.Grayscale()
fake_img = np.random.rand(500, 400, 3).astype('float32')
fake_img_gray = trans_gray(fake_img)
np.testing.assert_equal(len(fake_img_gray.shape), 3)
np.testing.assert_equal(fake_img_gray.shape[0], 500)
np.testing.assert_equal(fake_img_gray.shape[1], 400)
trans_gray3 = transforms.Grayscale(3)
fake_img = np.random.rand(500, 400, 3).astype('float32')
fake_img_gray = trans_gray3(fake_img)
def test_exception(self):
trans = transforms.Compose([transforms.Resize(-1)])
trans_batch = transforms.Compose([transforms.Resize(-1)])
with self.assertRaises(Exception):
self.do_transform(trans)
with self.assertRaises(Exception):
self.do_transform(trans_batch)
with self.assertRaises(ValueError):
transforms.Pad([1.0, 2.0, 3.0])
with self.assertRaises(TypeError):
fake_img = self.create_image((100, 120, 3))
F.pad(fake_img, '1')
with self.assertRaises(TypeError):
fake_img = self.create_image((100, 120, 3))
F.pad(fake_img, 1, {})
with self.assertRaises(TypeError):
fake_img = self.create_image((100, 120, 3))
F.pad(fake_img, 1, padding_mode=-1)
with self.assertRaises(ValueError):
fake_img = self.create_image((100, 120, 3))
F.pad(fake_img, [1.0, 2.0, 3.0])
with self.assertRaises(TypeError):
tensor_img = paddle.rand((3, 100, 100))
F.pad(tensor_img, '1')
with self.assertRaises(TypeError):
tensor_img = paddle.rand((3, 100, 100))
F.pad(tensor_img, 1, {})
with self.assertRaises(TypeError):
tensor_img = paddle.rand((3, 100, 100))
F.pad(tensor_img, 1, padding_mode=-1)
with self.assertRaises(ValueError):
tensor_img = paddle.rand((3, 100, 100))
F.pad(tensor_img, [1.0, 2.0, 3.0])
with self.assertRaises(ValueError):
transforms.RandomRotation(-2)
with self.assertRaises(ValueError):
transforms.RandomRotation([1, 2, 3])
with self.assertRaises(ValueError):
trans_gray = transforms.Grayscale(5)
fake_img = self.create_image((100, 120, 3))
trans_gray(fake_img)
with self.assertRaises(TypeError):
transform = transforms.RandomResizedCrop(64)
transform(1)
def test_exception(self):
trans = transforms.Compose([transforms.Resize(-1)])
trans_batch = transforms.BatchCompose([transforms.Resize(-1)])
with self.assertRaises(Exception):
self.do_transform(trans)
with self.assertRaises(Exception):
self.do_transform(trans_batch)
with self.assertRaises(ValueError):
transforms.ContrastTransform(-1.0)
with self.assertRaises(ValueError):
transforms.SaturationTransform(-1.0),
with self.assertRaises(ValueError):
transforms.HueTransform(-1.0)
with self.assertRaises(ValueError):
transforms.BrightnessTransform(-1.0)
with self.assertRaises(ValueError):
transforms.Pad([1.0, 2.0, 3.0])
with self.assertRaises(TypeError):
fake_img = np.random.rand(100, 120, 3).astype('float32')
F.pad(fake_img, '1')
with self.assertRaises(TypeError):
fake_img = np.random.rand(100, 120, 3).astype('float32')
F.pad(fake_img, 1, {})
with self.assertRaises(TypeError):
fake_img = np.random.rand(100, 120, 3).astype('float32')
F.pad(fake_img, 1, padding_mode=-1)
with self.assertRaises(ValueError):
fake_img = np.random.rand(100, 120, 3).astype('float32')
F.pad(fake_img, [1.0, 2.0, 3.0])
with self.assertRaises(ValueError):
transforms.RandomRotate(-2)
with self.assertRaises(ValueError):
transforms.RandomRotate([1, 2, 3])
with self.assertRaises(ValueError):
trans_gray = transforms.Grayscale(5)
fake_img = np.random.rand(100, 120, 3).astype('float32')
trans_gray(fake_img)
def test_exception(self):
trans = transforms.Compose([transforms.Resize(-1)])
trans_batch = transforms.Compose([transforms.Resize(-1)])
with self.assertRaises(Exception):
self.do_transform(trans)
with self.assertRaises(Exception):
self.do_transform(trans_batch)
with self.assertRaises(ValueError):
transforms.Pad([1.0, 2.0, 3.0])
with self.assertRaises(TypeError):
fake_img = self.create_image((100, 120, 3))
F.pad(fake_img, '1')
with self.assertRaises(TypeError):
fake_img = self.create_image((100, 120, 3))
F.pad(fake_img, 1, {})
with self.assertRaises(TypeError):
fake_img = self.create_image((100, 120, 3))
F.pad(fake_img, 1, padding_mode=-1)
with self.assertRaises(ValueError):
fake_img = self.create_image((100, 120, 3))
F.pad(fake_img, [1.0, 2.0, 3.0])
with self.assertRaises(TypeError):
tensor_img = paddle.rand((3, 100, 100))
F.pad(tensor_img, '1')
with self.assertRaises(TypeError):
tensor_img = paddle.rand((3, 100, 100))
F.pad(tensor_img, 1, {})
with self.assertRaises(TypeError):
tensor_img = paddle.rand((3, 100, 100))
F.pad(tensor_img, 1, padding_mode=-1)
with self.assertRaises(ValueError):
tensor_img = paddle.rand((3, 100, 100))
F.pad(tensor_img, [1.0, 2.0, 3.0])
with self.assertRaises(ValueError):
transforms.RandomAffine(-10)
with self.assertRaises(ValueError):
transforms.RandomAffine([-30, 60], translate=[2, 2])
with self.assertRaises(ValueError):
transforms.RandomAffine(10, translate=[0.2, 0.2], scale=[-2, -1]),
with self.assertRaises(ValueError):
transforms.RandomAffine(10, translate=[0.2, 0.2], scale=[1, 2, 3]),
with self.assertRaises(ValueError):
transforms.RandomAffine(10,
translate=[0.2, 0.2],
scale=[0.5, 0.5],
shear=[1, 2, 3]),
with self.assertRaises(ValueError):
transforms.RandomAffine(10,
translate=[0.5, 0.3],
scale=[0.7, 1.3],
shear=[-10, 10, 0, 20, 40])
with self.assertRaises(ValueError):
transforms.RandomRotation(-2)
with self.assertRaises(ValueError):
transforms.RandomRotation([1, 2, 3])
with self.assertRaises(ValueError):
trans_gray = transforms.Grayscale(5)
fake_img = self.create_image((100, 120, 3))
trans_gray(fake_img)
with self.assertRaises(TypeError):
transform = transforms.RandomResizedCrop(64)
transform(1)
def test_exception(self):
trans = transforms.Compose([transforms.Resize(-1)])
trans_batch = transforms.Compose([transforms.Resize(-1)])
with self.assertRaises(Exception):
self.do_transform(trans)
with self.assertRaises(Exception):
self.do_transform(trans_batch)
with self.assertRaises(ValueError):
transforms.ContrastTransform(-1.0)
with self.assertRaises(ValueError):
transforms.SaturationTransform(-1.0),
with self.assertRaises(ValueError):
transforms.HueTransform(-1.0)
with self.assertRaises(ValueError):
transforms.BrightnessTransform(-1.0)
with self.assertRaises(ValueError):
transforms.Pad([1.0, 2.0, 3.0])
with self.assertRaises(TypeError):
fake_img = self.create_image((100, 120, 3))
F.pad(fake_img, '1')
with self.assertRaises(TypeError):
fake_img = self.create_image((100, 120, 3))
F.pad(fake_img, 1, {})
with self.assertRaises(TypeError):
fake_img = self.create_image((100, 120, 3))
F.pad(fake_img, 1, padding_mode=-1)
with self.assertRaises(ValueError):
fake_img = self.create_image((100, 120, 3))
F.pad(fake_img, [1.0, 2.0, 3.0])
with self.assertRaises(TypeError):
tensor_img = paddle.rand((3, 100, 100))
F.pad(tensor_img, '1')
with self.assertRaises(TypeError):
tensor_img = paddle.rand((3, 100, 100))
F.pad(tensor_img, 1, {})
with self.assertRaises(TypeError):
tensor_img = paddle.rand((3, 100, 100))
F.pad(tensor_img, 1, padding_mode=-1)
with self.assertRaises(ValueError):
tensor_img = paddle.rand((3, 100, 100))
F.pad(tensor_img, [1.0, 2.0, 3.0])
with self.assertRaises(ValueError):
transforms.RandomAffine(-10)
with self.assertRaises(ValueError):
transforms.RandomAffine([-30, 60], translate=[2, 2])
with self.assertRaises(ValueError):
transforms.RandomAffine(10, translate=[0.2, 0.2], scale=[1, 2, 3]),
with self.assertRaises(ValueError):
transforms.RandomAffine(10,
translate=[0.2, 0.2],
scale=[0.5, 0.5],
shear=[1, 2, 3]),
with self.assertRaises(ValueError):
transforms.RandomAffine(10,
translate=[0.5, 0.3],
scale=[0.7, 1.3],
shear=[-10, 10, 0, 20, 40])
with self.assertRaises(ValueError):
transforms.RandomAffine(10,
translate=[0.5, 0.3],
scale=[0.7, 1.3],
shear=[-10, 10, 20, 40],
fill=114,
center=(1, 2, 3))
with self.assertRaises(ValueError):
transforms.RandomRotation(-2)
with self.assertRaises(ValueError):
transforms.RandomRotation([1, 2, 3])
with self.assertRaises(ValueError):
trans_gray = transforms.Grayscale(5)
fake_img = self.create_image((100, 120, 3))
trans_gray(fake_img)
with self.assertRaises(TypeError):
transform = transforms.RandomResizedCrop(64)
transform(1)
with self.assertRaises(ValueError):
transform = transforms.BrightnessTransform([-0.1, -0.2])
with self.assertRaises(TypeError):
transform = transforms.BrightnessTransform('0.1')
with self.assertRaises(ValueError):
transform = transforms.BrightnessTransform('0.1', keys=1)
with self.assertRaises(NotImplementedError):
transform = transforms.BrightnessTransform('0.1', keys='a')
with self.assertRaises(Exception):
transform = transforms.RandomErasing(scale=0.5)
with self.assertRaises(Exception):
transform = transforms.RandomErasing(ratio=0.8)
with self.assertRaises(Exception):
transform = transforms.RandomErasing(scale=(10, 0.4))
with self.assertRaises(Exception):
transform = transforms.RandomErasing(ratio=(3.3, 0.3))
with self.assertRaises(Exception):
transform = transforms.RandomErasing(prob=1.5)
with self.assertRaises(Exception):
transform = transforms.RandomErasing(value="0")
def test_exception(self):
trans = transforms.Compose([transforms.Resize(-1)])
trans_batch = transforms.Compose([transforms.Resize(-1)])
with self.assertRaises(Exception):
self.do_transform(trans)
with self.assertRaises(Exception):
self.do_transform(trans_batch)
with self.assertRaises(ValueError):
transforms.ContrastTransform(-1.0)
with self.assertRaises(ValueError):
transforms.SaturationTransform(-1.0),
with self.assertRaises(ValueError):
transforms.HueTransform(-1.0)
with self.assertRaises(ValueError):
transforms.BrightnessTransform(-1.0)
with self.assertRaises(ValueError):
transforms.Pad([1.0, 2.0, 3.0])
with self.assertRaises(TypeError):
fake_img = self.create_image((100, 120, 3))
F.pad(fake_img, '1')
with self.assertRaises(TypeError):
fake_img = self.create_image((100, 120, 3))
F.pad(fake_img, 1, {})
with self.assertRaises(TypeError):
fake_img = self.create_image((100, 120, 3))
F.pad(fake_img, 1, padding_mode=-1)
with self.assertRaises(ValueError):
fake_img = self.create_image((100, 120, 3))
F.pad(fake_img, [1.0, 2.0, 3.0])
with self.assertRaises(TypeError):
tensor_img = paddle.rand((3, 100, 100))
F.pad(tensor_img, '1')
with self.assertRaises(TypeError):
tensor_img = paddle.rand((3, 100, 100))
F.pad(tensor_img, 1, {})
with self.assertRaises(TypeError):
tensor_img = paddle.rand((3, 100, 100))
F.pad(tensor_img, 1, padding_mode=-1)
with self.assertRaises(ValueError):
tensor_img = paddle.rand((3, 100, 100))
F.pad(tensor_img, [1.0, 2.0, 3.0])
with self.assertRaises(ValueError):
transforms.RandomRotation(-2)
with self.assertRaises(ValueError):
transforms.RandomRotation([1, 2, 3])
with self.assertRaises(ValueError):
trans_gray = transforms.Grayscale(5)
fake_img = self.create_image((100, 120, 3))
trans_gray(fake_img)
with self.assertRaises(TypeError):
transform = transforms.RandomResizedCrop(64)
transform(1)
with self.assertRaises(ValueError):
transform = transforms.BrightnessTransform([-0.1, -0.2])
with self.assertRaises(TypeError):
transform = transforms.BrightnessTransform('0.1')
with self.assertRaises(ValueError):
transform = transforms.BrightnessTransform('0.1', keys=1)
with self.assertRaises(NotImplementedError):
transform = transforms.BrightnessTransform('0.1', keys='a')
