datasets.py 文件源码

def voc2007_classification_generator2(which, batch_size, input_size,
                            outer_input_size,
                            shuffle=True,# seed=0,
                            color_transform=None, random_mirror=False):
    path = os.path.expandvars('$VOC2007_DIR/ImageSets/Main')

    assert which in ['test', 'val']
    imgs, C = dd.io.load('{}.h5'.format(which), ['/data', '/labels'])

    if shuffle:
        rs = np.random.RandomState()
        while True:
            II = rs.randint(len(imgs), size=batch_size)

            ii, cc = imgs[II], C[II]
            if random_mirror and rs.randint(2) == 1:
                ii = ii[:, :, ::-1]
            yield ii, cc
    else:
        for i in range(len(imgs)//batch_size):
            ss = np.s_[i*batch_size:(i+1)*batch_size]
            yield imgs[ss], C[ss]