def test_pad(self):
trans = transforms.Compose([transforms.Pad(2)])
self.do_transform(trans)
fake_img = self.create_image((200, 150, 3))
trans_pad = transforms.Pad(10)
fake_img_padded = trans_pad(fake_img)
np.testing.assert_equal(self.get_shape(fake_img_padded), (220, 170, 3))
trans_pad1 = transforms.Pad([1, 2])
trans_pad2 = transforms.Pad([1, 2, 3, 4])
img = trans_pad1(fake_img)
img = trans_pad2(img)
def test_pad(self):
trans = transforms.Compose([transforms.Pad(2)])
self.do_transform(trans)
fake_img = np.random.rand(200, 150, 3).astype('float32')
trans_pad = transforms.Pad(10)
fake_img_padded = trans_pad(fake_img)
np.testing.assert_equal(fake_img_padded.shape, (220, 170, 3))
trans_pad1 = transforms.Pad([1, 2])
trans_pad2 = transforms.Pad([1, 2, 3, 4])
img = trans_pad1(fake_img)
img = trans_pad2(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_keys(self):
fake_img1 = self.create_image((200, 150, 3))
fake_img2 = self.create_image((200, 150, 3))
trans_pad = transforms.Pad(10, keys=("image", ))
fake_img_padded = trans_pad((fake_img1, fake_img2))
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')