update generator doc

content/en/docs/bmf/multiple_features/graph_mode/generatemode/_index.md

@@ -9,26 +9,27 @@ weight: 1
 The generator method has common similarities and differences, mainly using ```start()``` (usually ```run()```):
 
 ```python
-frames = (
-     bmf. graph()
-         .decode({'input_path': "../files/img.mp4"})['video']
-         .ff_filter('scale', 299, 299) # or you can use '.scale(299, 299)'
-         .start() # this will return a packet generator
+pkts = (
+  bmf.graph()
+      .decode({'input_path': "../files/big_bunny_10s_30fps.mp4"})['video']
+      .ff_filter('scale', 299, 299)  # or you can use '.scale(299, 299)'
+      .start()  # this will return a packet generator
 )
 ```
 
 The generated frames can be used like iterators:
 
 ```python
-for i, frame in enumerate(frames):
-     # convert frame to a nd array
-     if frame is not None:
-         np_frame = frame.to_ndarray(format='rgb24')
-
-         # we can add some more processing here, e.g. predicting
-         print('frame', i, 'shape', np_frame.shape)
-     else:
-         break
+for i, pkt in enumerate(pkts):
+  # convert frame to a nd array
+  if pkt.is_(bmf.VideoFrame) and i < 10:
+      vf = pkt.get(bmf.VideoFrame)
+      rgb = mp.PixelInfo(mp.kPF_RGB24)
+      np_vf = vf.reformat(rgb).frame().plane(0).numpy()
+      # we can add some more processing here, e.g. predicting
+      print("frame", i, "shape", np_vf.shape)
+  else:
+      break
 ```
 
 If you need the complete code, you can refer to [test_generator.py]（#tbytodo)