ImageFolder()用于加载数据集,它说到底还是继承自torch.utils.data.Dataset,后续可以作为Dataset对象直接传入torch.utils.data.DataLoader中。对于ImageFolder(),root是要加载数据集的路径,transforms是对数据进行预处理的方式,函数原型和example如下: # 原型 torchvision.datasets.ImageFolder(root: str, transform: Optional[...
Python 是一种强大而灵活的编程语言，它提供了许多方便的数据结构和操作方法，其中之一就是列表（List）。
ImageFolder 一个通用的数据加载器,数据集中的数据以以下方式组织 使用时要注意图片的存储格式,如上所示 用此函数进行处理的时候,会自动会图片的label命名 0,1,3... 方便接下来的loss计算 class_names = image_datasets['train'
class ImageFolder(Dataset): """A generic data loader where the samples are arranged in this way: .. code-block:: text root/1.ext root/2.ext root/sub_dir/3.ext Args: root (str): Root directory path. loader (Callable, optional): A function to load a sample given its path. Default...
ImageFolder(root = data_folder, transform=transform['train' if train else 'test']) data_loader = torch.utils.data.DataLoader(data, batch_size=batch_size, shuffle=True, **kwargs, drop_last = True if train else False) return data_loader ...
classmxnet.gluon.data.vision.datasets.ImageFolderDataset(root, flag=1, transform=None) 參數: root:(str) - 根目錄的路徑。 flag:({0,1},default 1) - 如果為 0,則始終將加載的圖像轉換為灰度(1 通道)。如果為 1,則始終將加載的圖像轉換為彩色(3 個通道)。
dataset = dset.ImageFolder(root=data_path, transform=transform)elifdataset_type =='lsun':assertos.path.exists(data_path),"data_path does not exist! Given: "+ data_path dataset = dset.LSUN(root=data_path, classes=['bedroom_train'], transform=transform)elifdataset_type =='cifar10':ifnotos...
ImageFolder(root=os.path.join(dataroot, 'train'), transform=get_transform(input_size=input_size)) train_sampler = DistributedSampler(train_data, num_nodes, local_rank) train_loader = torch.utils.data.DataLoader(train_data, batch_size=train_batch_size, sampler=train_sampler, num_workers=...
dataset=ImageFolder(root="./root", transform=transform) dataloader=DataLoader(dataset) print(next(iter(dataloader)).shape)# prints shape of image with single batch You can always alter how the images are labelled and loaded by inherting from ImageFolder class. ...
self.data =datasets.ImageFolder( traindirifsplit=='train'elsevaldir, self.transform) self.labels = [item[1]foriteminself.data.imgs] 開發者ID:gidariss,項目名稱:FewShotWithoutForgetting,代碼行數:23,代碼來源:dataloader.py 示例4: __getitem__ ...