Finished

2018-Python-Practice-master/main.py

@@ -3,14 +3,10 @@
 from datetime import datetime
 
 import tensorflow as tf
+from styler.video import Video
+from styler.utils import save_video
 
-'''
-1. import `Video` and `save_video` from the correct module of package "styler"
-'''
-from ... import Video
-from ... import save_video
-
-
+vedio_path = './input/jaguar.mp4'
 model_file = 'data/vg-30.pb'
 model_name = 'vg-30'
 logging.basicConfig(
@@ -38,30 +34,20 @@ def main():
         out = graph.get_tensor_by_name("import/%s/output:0" % model_name)
         shape = image.get_shape().as_list()
 
-        '''
-        2. set the `path` to  your input
-        '''
-        with Video(...) as v:
+        with Video(vedio_path) as v:
             frames = v.read_frames(image_h=shape[1], image_w=shape[2])
 
         logging.info("Processing image")
         start_time = datetime.now()
 
-        '''
-        3. Write a list comprehension to iterate through all frames,
-           and make it be processed by Tensorflow.
-        '''
         processed = [
             session.run(out, feed_dict={image: [frame]})
-            ...
+            for frame in frames
         ]
 
-        '''
-        4. Pass the results as a argument into function
-        '''
         save_video('result.mp4',
                    fps=30, h=shape[1], w=shape[2],
-                   frames=...)
+                   frames=processed)
 
         logging.info("Processing took %f" % (
             (datetime.now() - start_time).total_seconds()))

2018-Python-Practice-master/styler/video.py

@@ -19,18 +19,13 @@ def __len__(self):
         return len(self.frames)
 
     def read_frames(self, image_h, image_w):
-        '''
-        5.
-         - Read video frames from `self.cap` and collect frames into list
-         - Apply `resize()` on each frame before add it to list
-         - Also assign frames to "self" object
-         - Return your results
-        '''
-        frames = []
-        # 5-1 /5-2 Read video and collect them
-
-        self.frames = ...  # 5-3 let object have the result
-        return ...  # return your results
+        while self.cap.isOpened():
+            ret, frame = self.cap.read()
+            if ret:
+                self.frames.append(resize(frame, image_h, image_w))
+            else: break
+
+        return self.frames
 
     def __exit__(self, exc_type, exc_val, exc_tb):
         self.cap.release()