title: How to classify a batch of images with the pre trained TensorFlow Inception network?
body: <p>I use the latest pre trained <a href="https://codelabs.developers.google.com/codelabs/tensorflow-for-poets/#0" rel="nofollow noreferrer">Inception model</a>. I use sliding window technique to find different objects on the image (around 3000 windows per image). It takes too much time to process window by window as a sequence. I want to run prediction in parallel. How can I do this? </p>
  
  <p><code>image_data</code> should be the list.</p>
  
  <pre><code>with tf.Session() as sess:
      softmax_tensor = sess.graph.get_tensor_by_name('final_result:0') 
  
      test_img = cv2.resize(img3[window[0][1]:window[1][1], window[0][0]:window[1][0]], dsize=(299,299), interpolation = cv2.INTER_CUBIC)
      np_image_data = np.asarray(test_img)
      np_image_data=cv2.normalize(np_image_data.astype('float'), None, -0.5, .5, cv2.NORM_MINMAX)
      image_data = np.expand_dims(np_image_data,axis=0)  
  
      predictions = sess.run(softmax_tensor, {'Mul:0': image_data})
  </code></pre>