n12_predict_dpn.py 文件源码

def check_aug():
    nfold = 0
    tst_dataset = CSVDataset_tst(f'../../_data/fold{nfold}/train.csv')
    tst = data.DataLoader(tst_dataset, batch_size=1, shuffle=False, num_workers=8)

    for j, val_data in enumerate(tst, 0):
        if j == 3:
            inputs, labels = val_data
            inputs, labels = inputs.numpy()[0], labels.numpy()[0]

            print(inputs.shape, labels.shape, np.amax(inputs), np.amin(inputs), np.mean(inputs))
            for i in range(13):
                plt.subplot(3, 5, 1 + i)
                plt.imshow(np.transpose(inputs[i], (1, 2, 0)))
            break
    plt.show()