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')