text: #! /usr/bin/env python
  # coding=utf-8
  #================================================================
  #   Copyright (C) 2018 * Ltd. All rights reserved.
  #
  #   Editor      : VIM
  #   File name   : video_demo.py
  #   Author      : YunYang1994
  #   Created date: 2018-11-30 15:56:37
  #   Description :
  #
  #================================================================
  
  import cv2
  import time
  import numpy as np
  import core.utils as utils
  import tensorflow as tf
  from PIL import Image
  
  
  return_elements = ["input/input_data:0", "pred_sbbox/Reshape:0", "pred_mbbox/Reshape:0", "pred_lbbox/Reshape:0"]
  pb_file         = "./yolov3_coco.pb"
  video_path      = "./docs/images/road.mp4"
  # video_path      = 0
  num_classes     = 80
  input_size      = 416
  graph           = tf.Graph()
  return_tensors  = utils.read_pb_return_tensors(graph, pb_file, return_elements)
  
  with tf.Session(graph=graph) as sess:
      vid = cv2.VideoCapture(video_path)
      while True:
          return_value, frame = vid.read()
          if return_value:
              frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
              image = Image.fromarray(frame)
          else:
              raise ValueError("No image!")
          frame_size = frame.shape[:2]
          image_data = utils.image_preporcess(np.copy(frame), [input_size, input_size])
          image_data = image_data[np.newaxis, ...]
          prev_time = time.time()
  
          pred_sbbox, pred_mbbox, pred_lbbox = sess.run(
              [return_tensors[1], return_tensors[2], return_tensors[3]],
                      feed_dict={ return_tensors[0]: image_data})
  
          pred_bbox = np.concatenate([np.reshape(pred_sbbox, (-1, 5 + num_classes)),
                                      np.reshape(pred_mbbox, (-1, 5 + num_classes)),
                                      np.reshape(pred_lbbox, (-1, 5 + num_classes))], axis=0)
  
          bboxes = utils.postprocess_boxes(pred_bbox, frame_size, input_size, 0.3)
          bboxes = utils.nms(bboxes, 0.45, method='nms')
          image = utils.draw_bbox(frame, bboxes)
  
          curr_time = time.time()
          exec_time = curr_time - prev_time
          result = np.asarray(image)
          info = "time: %.2f ms" %(1000*exec_time)
          cv2.namedWindow("result", cv2.WINDOW_AUTOSIZE)
          result = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
          cv2.imshow("result", result)
          if cv2.waitKey(1) & 0xFF == ord('q'): break
  
  
  
  
  