data_augmentation.py 文件源码

def vggnet_input(im_tf):
    im_tf = tf.image.convert_image_dtype(im_tf, dtype=tf.float32)
    # im_tf = tf.image.central_crop(im_tf, central_fraction=0.875)
    # im_tf = tf.expand_dims(im_tf, 0)
    # im_tf = tf.image.resize_bilinear(im_tf, [224, 224], align_corners=False)
    # im_tf = tf.squeeze(im_tf, [0])
    im_tf = tf.subtract(im_tf, 0.5)
    im_tf = tf.multiply(im_tf, 2.0)
    im_tf = im_tf * 255.0
    r_, g_, b_ = tf.split(im_tf, 3, axis=2)
    r_ = r_ - VGG_MEAN[2]
    g_ = b_ - VGG_MEAN[1]
    b_ = b_ - VGG_MEAN[0]
    im_tf = tf.concat([r_, g_, b_], axis=2)
    # im_tf = tf.expand_dims(im_tf, 0)
    return im_tf