cnn_expression_normal.py 文件源码

def do_kfold(proc_images, proc_labels, split=10):
    trainimages = []
    trainlabels = []
    testimages = []
    testlabels = []
    rand_idx = random.sample(range(0, len(proc_images)), len(proc_images))
    proc_images = proc_images[rand_idx]
    proc_labels = proc_labels[rand_idx]
    kf = KFold(n_splits=split)
    for train_index, test_index in kf.split(proc_images):
        x_train, x_test = proc_images[train_index], proc_images[test_index]
        y_train, y_test = proc_labels[train_index], proc_labels[test_index]
        trainimages.append(x_train)
        testimages.append(x_test)
        trainlabels.append(y_train)
        testlabels.append(y_test)

    np.save("trainimages.npy", trainimages)
    np.save("testimages.npy", testimages)
    np.save("trainlabels.npy", trainlabels)
    np.save("testlabels.npy", testlabels)
    return(trainimages, testimages, trainlabels, testlabels)