"MXNet" Sixth play _ Data Processing API (to be continued)

Gluon Data loading image data (with tags) load function: Gluon.data.vision.ImageFolderDataset

Give a description of the Imagefolderdataset class,

Init Signature:mxnet.gluon.data.vision.datasets.ImageFolderDataset (Root, Flag=1, transform=none) Source:class Imag Efolderdataset (DataSet. DataSet): "" "A DataSet for loading image files stored in A folder structure like:: Root/car/0001.jpg root /car/xxxa.jpg root/car/yyyb.jpg root/bus/123.jpg root/bus/023.jpg root/bus/wwww.jpg Paramet    ERs----------root:str Path to root directory.        Flag: {0, 1}, default 1 # controls color or grayscale If 0, always convert loaded images to greyscale (1 channel).    If 1, always convert loaded images to colored (3 channels).  transform:callable, default None A function that takes data and label and transforms them::: Transform        = Lambda data, Label: (Data.astype (Np.float32)/255, label) Attributes----------synsets:list # View the category, which is actually the file name List of class names. ' Synsets[i] ' is the name for the integer label ' i ' Items:list of tuples # generated data listOf all images in (filename, label) pairs. """

Instance:

Train_imgs = Gluon.data.vision.ImageFolderDataset (    data_dir+ '/hotdog/train ',    transform=lambda X, y: Transform (X, Y, train_augs)) Test_imgs = Gluon.data.vision.ImageFolderDataset (    data_dir+ '/hotdog/test ',    Transform=lambda x, Y:transform (x, Y, test_augs)) print (TRAIN_IMGS) print (train_imgs.synsets) data = Gluon.data.DataLoader (Train_imgs, Shuffle=true)

<mxnet.gluon.data.vision.datasets.imagefolderdataset object at 0x7fbed5641c18>[' hotdog ', ' Not-hotdog ']

Batch iterator: Gluon.data.DataLoader

With a special method, the Def __iter__(self), whose instance can be iterated, that is, each time the data of a batch is returned, cut on the first dimension.

The first positional parameters document is as follows:

Dataset:dataset        Source Dataset. Note that NumPy and mxnet arrays can be directly used as        a Dataset.

The last generated X_batch feed net (x_batch) propagates forward, y_batch into loss (Output,y_batch) to calculate loss after the reverse propagation.

Second, mxnet data loading

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"MXNet" Sixth play _ Data Processing API (to be continued)