def test_errors(self):
with self.assertRaises(TypeError):
F.to_tensor(1)
with self.assertRaises(ValueError):
fake_img = Image.fromarray((np.random.rand(28, 28, 3) * 255).astype(
'uint8'))
F.to_tensor(fake_img, data_format=1)
with self.assertRaises(ValueError):
fake_img = paddle.rand((3, 100, 100))
F.pad(fake_img, 1, padding_mode='symmetric')
with self.assertRaises(TypeError):
fake_img = paddle.rand((3, 100, 100))
F.resize(fake_img, {1: 1})
with self.assertRaises(TypeError):
fake_img = Image.fromarray((np.random.rand(28, 28, 3) * 255).astype(
'uint8'))
F.resize(fake_img, '1')
with self.assertRaises(TypeError):
F.resize(1, 1)
with self.assertRaises(TypeError):
F.pad(1, 1)
with self.assertRaises(TypeError):
F.crop(1, 1, 1, 1, 1)
with self.assertRaises(TypeError):
F.hflip(1)
with self.assertRaises(TypeError):
F.vflip(1)
with self.assertRaises(TypeError):
F.adjust_brightness(1, 0.1)
with self.assertRaises(TypeError):
F.adjust_contrast(1, 0.1)
with self.assertRaises(TypeError):
F.adjust_hue(1, 0.1)
with self.assertRaises(TypeError):
F.adjust_saturation(1, 0.1)
with self.assertRaises(TypeError):
F.rotate(1, 0.1)
with self.assertRaises(TypeError):
F.to_grayscale(1)
with self.assertRaises(ValueError):
set_image_backend(1)
with self.assertRaises(ValueError):
image_load('tmp.jpg', backend=1)
def test_pad(self):
np_img = (np.random.rand(28, 24, 3)).astype('uint8')
pil_img = Image.fromarray(np_img)
np_padded_img = F.pad(np_img, [1, 2], padding_mode='reflect')
pil_padded_img = F.pad(pil_img, [1, 2], padding_mode='reflect')
np.testing.assert_almost_equal(np_padded_img, np.array(pil_padded_img))
pil_p_img = pil_img.convert('P')
pil_padded_img = F.pad(pil_p_img, [1, 2])
pil_padded_img = F.pad(pil_p_img, [1, 2], padding_mode='reflect')
def _apply_mask(self, mask):
_, height, width = F.to_tensor(mask).shape
ret = F.pad(mask, self.padding)
return F.crop(ret,
top=abs(self.y_offset) if self.y_offset >= 0 else 0,
left=0 if self.x_offset >= 0 else abs(self.x_offset),
height=height,
width=width)
def _apply_image(self, image):
_, height, width = F.to_tensor(image).shape
ret = F.pad(image, self.padding)
return F.crop(ret,
top=abs(self.y_offset) if self.y_offset >= 0 else 0,
left=0 if self.x_offset >= 0 else abs(self.x_offset),
height=height,
width=width)
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_pad(self):
np_img = (np.random.rand(28, 24, 3) * 255).astype('uint8')
pil_img = Image.fromarray(np_img)
tensor_img = F.to_tensor(pil_img, 'CHW') * 255
np_padded_img = F.pad(np_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')
np.testing.assert_almost_equal(np_padded_img, np.array(pil_padded_img))
np.testing.assert_almost_equal(np_padded_img,
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, 2, 1, 2],
padding_mode='reflect')
pil_p_img = pil_img.convert('P')
pil_padded_img = F.pad(pil_p_img, [1, 2])
pil_padded_img = F.pad(pil_p_img, [1, 2], padding_mode='reflect')
def test_errors(self):
with self.assertRaises(TypeError):
F.to_tensor(1)
with self.assertRaises(ValueError):
fake_img = Image.fromarray(
(np.random.rand(28, 28, 3) * 255).astype('uint8'))
F.to_tensor(fake_img, data_format=1)
with self.assertRaises(ValueError):
fake_img = paddle.rand((3, 100, 100))
F.pad(fake_img, 1, padding_mode='symmetric')
with self.assertRaises(TypeError):
fake_img = paddle.rand((3, 100, 100))
F.resize(fake_img, {1: 1})
with self.assertRaises(TypeError):
fake_img = Image.fromarray(
(np.random.rand(28, 28, 3) * 255).astype('uint8'))
F.resize(fake_img, '1')
with self.assertRaises(TypeError):
F.resize(1, 1)
with self.assertRaises(TypeError):
F.pad(1, 1)
with self.assertRaises(TypeError):
F.crop(1, 1, 1, 1, 1)
with self.assertRaises(TypeError):
F.hflip(1)
with self.assertRaises(TypeError):
F.vflip(1)
with self.assertRaises(TypeError):
F.adjust_brightness(1, 0.1)
with self.assertRaises(TypeError):
F.adjust_contrast(1, 0.1)
with self.assertRaises(TypeError):
F.adjust_hue(1, 0.1)
with self.assertRaises(TypeError):
F.adjust_saturation(1, 0.1)
with self.assertRaises(TypeError):
F.affine('45')
with self.assertRaises(TypeError):
F.affine(45, translate=0.3)
with self.assertRaises(TypeError):
F.affine(45, translate=[0.2, 0.2, 0.3])
with self.assertRaises(TypeError):
F.affine(45, translate=[0.2, 0.2], scale=-0.5)
with self.assertRaises(TypeError):
F.affine(45, translate=[0.2, 0.2], scale=0.5, shear=10)
with self.assertRaises(TypeError):
F.affine(45, translate=[0.2, 0.2], scale=0.5, shear=[-10, 0, 10])
with self.assertRaises(TypeError):
F.affine(45,
translate=[0.2, 0.2],
scale=0.5,
shear=[-10, 10],
interpolation=2)
with self.assertRaises(TypeError):
F.affine(45,
translate=[0.2, 0.2],
scale=0.5,
shear=[-10, 10],
center=0)
with self.assertRaises(TypeError):
F.rotate(1, 0.1)
with self.assertRaises(TypeError):
F.to_grayscale(1)
with self.assertRaises(ValueError):
set_image_backend(1)
with self.assertRaises(ValueError):
image_load('tmp.jpg', backend=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.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 _apply_mask(self, mask):
return F.pad(mask, self.padding, 0)
def _apply_image(self, image):
return F.pad(image, self.padding, self.fill, self.padding_mode)
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.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')