#-*- coding:utf-8 -*-
'''
  使用TensorFlow進(jìn)行圖像的隨機(jī)旋轉(zhuǎn)示例
'''
 
import tensorflow as tf
import numpy as np
import cv2
import matplotlib.pyplot as plt
 
 
img = cv2.imread('tf.jpg')
img = cv2.resize(img,(220,220))
img = cv2.cvtColor(img,cv2.COLOR_BGR2RGB)
 
def tf_rotate(input_image, min_angle = -np.pi/2, max_angle = np.pi/2):
  '''
  TensorFlow對(duì)圖像進(jìn)行隨機(jī)旋轉(zhuǎn)
  :param input_image: 圖像輸入
  :param min_angle: 最小旋轉(zhuǎn)角度
  :param max_angle: 最大旋轉(zhuǎn)角度
  :return: 旋轉(zhuǎn)后的圖像
  '''
  distorted_image = tf.expand_dims(input_image, 0)
  random_angles = tf.random.uniform(shape=(tf.shape(distorted_image)[0],), minval = min_angle , maxval = max_angle)
  distorted_image = tf.contrib.image.transform(
    distorted_image,
    tf.contrib.image.angles_to_projective_transforms(
      random_angles, tf.cast(tf.shape(distorted_image)[1], tf.float32), tf.cast(tf.shape(distorted_image)[2], tf.float32)
    ))
  rotate_image = tf.squeeze(distorted_image, [0])
  return rotate_image
 
global_init = tf.global_variables_initializer()
with tf.Session() as sess:
  init = tf.initialize_local_variables()
  sess.run([init, global_init])
  coord = tf.train.Coordinator()
  threads = tf.train.start_queue_runners(coord=coord)
  image = tf.placeholder(shape=(220, 220, 3), dtype=tf.float32)
 
  rotate_image = tf_rotate(image, -np.pi/2, np.pi/2)
  output = sess.run(rotate_image, feed_dict={image:img})
  # print('output:',output)
  plt.imshow(output.astype('uint8'))
  plt.title('rotate image')
  plt.show()