| @@ -80,10 +80,10 @@ class Compose: | |||||
| >>> dataset = ds.ImageFolderDataset(dataset_dir, num_parallel_workers=8) | >>> dataset = ds.ImageFolderDataset(dataset_dir, num_parallel_workers=8) | ||||
| >>> # create a list of transformations to be applied to the image data | >>> # create a list of transformations to be applied to the image data | ||||
| >>> transform = py_transforms.Compose([py_vision.Decode(), | >>> transform = py_transforms.Compose([py_vision.Decode(), | ||||
| >>> py_vision.RandomHorizontalFlip(0.5), | |||||
| >>> py_vision.ToTensor(), | |||||
| >>> py_vision.Normalize((0.491, 0.482, 0.447), (0.247, 0.243, 0.262)), | |||||
| >>> py_vision.RandomErasing()]) | |||||
| >>> py_vision.RandomHorizontalFlip(0.5), | |||||
| >>> py_vision.ToTensor(), | |||||
| >>> py_vision.Normalize((0.491, 0.482, 0.447), (0.247, 0.243, 0.262)), | |||||
| >>> py_vision.RandomErasing()]) | |||||
| >>> # apply the transform to the dataset through dataset.map() | >>> # apply the transform to the dataset through dataset.map() | ||||
| >>> dataset = dataset.map(operations=transform, input_columns="image") | >>> dataset = dataset.map(operations=transform, input_columns="image") | ||||
| >>> | >>> | ||||
| @@ -96,7 +96,7 @@ class Compose: | |||||
| >>> py_vision.RandomErasing()] | >>> py_vision.RandomErasing()] | ||||
| >>> | >>> | ||||
| >>> # apply the transform to the dataset through dataset.map() | >>> # apply the transform to the dataset through dataset.map() | ||||
| >>> dataset = dataset.map(operations=transform, input_columns="image") | |||||
| >>> dataset = dataset.map(operations=transform_list, input_columns="image") | |||||
| >>> | >>> | ||||
| >>> # Certain C++ and Python ops can be combined, but not all of them | >>> # Certain C++ and Python ops can be combined, but not all of them | ||||
| >>> # An example of combined operations | >>> # An example of combined operations | ||||
| @@ -106,18 +106,18 @@ class Compose: | |||||
| >>> | >>> | ||||
| >>> data = ds.NumpySlicesDataset(arr, column_names=["cols"], shuffle=False) | >>> data = ds.NumpySlicesDataset(arr, column_names=["cols"], shuffle=False) | ||||
| >>> transformed_list = [py_transforms.OneHotOp(2), c_transforms.Mask(c_transforms.Relational.EQ, 1)] | >>> transformed_list = [py_transforms.OneHotOp(2), c_transforms.Mask(c_transforms.Relational.EQ, 1)] | ||||
| >>> data = data.map(operations=op_list, input_columns=["cols"]) | |||||
| >>> data = data.map(operations=transformed_list, input_columns=["cols"]) | |||||
| >>> | >>> | ||||
| >>> # Here is an example of mixing vision ops | >>> # Here is an example of mixing vision ops | ||||
| >>> data_dir = "/path/to/imagefolder_directory" | >>> data_dir = "/path/to/imagefolder_directory" | ||||
| >>> data1 = ds.ImageFolderDataset(dataset_dir=data_dir, shuffle=False) | >>> data1 = ds.ImageFolderDataset(dataset_dir=data_dir, shuffle=False) | ||||
| >>> input_columns = ["column_names"] | >>> input_columns = ["column_names"] | ||||
| >>> data1 = data1.map(operations=op_list, input_columns=input_columns) | |||||
| >>> op_list=[c_vision.Decode(), | >>> op_list=[c_vision.Decode(), | ||||
| >>> c_vision.Resize((224, 244)), | >>> c_vision.Resize((224, 244)), | ||||
| >>> py_vision.ToPIL(), | >>> py_vision.ToPIL(), | ||||
| >>> np.array, # need to convert PIL image to a NumPy array to pass it to C++ operation | >>> np.array, # need to convert PIL image to a NumPy array to pass it to C++ operation | ||||
| >>> c_vision.Resize((24, 24))] | >>> c_vision.Resize((24, 24))] | ||||
| >>> data1 = data1.map(operations=op_list, input_columns=input_columns) | |||||
| """ | """ | ||||
| @check_compose_list | @check_compose_list | ||||