update readme with dc2

README.md

@@ -16,51 +16,38 @@ This operator extracts features for video or text with [Frozen In Time](https://
 
 Load a video from path './demo_video.mp4' to generate a video embedding. 
 
-Read the text 'kids feeding and playing with the horse' to generate a text embedding. 
-
- *Write the pipeline in simplified style*:
-
 - Encode video (default):
 ```python
-import towhee
-towhee.dc(['./demo_video.mp4']) \
-      .video_decode.ffmpeg(sample_type='uniform_temporal_subsample', args={'num_samples': 4}) \
-      .runas_op(func=lambda x: [y for y in x]) \
-      .video_text_embedding.frozen_in_time(model_name='frozen_in_time_base_16_244', modality='video', device='cpu') \
-      .show()
+from towhee.dc2 import pipe, ops, DataCollection
 
-```
-<img src="./result1.png" width="800px"/>
+p = (
+    pipe.input('video_path') \
+        .map('video_path', 'flame_gen', ops.video_decode.ffmpeg(sample_type='uniform_temporal_subsample', args={'num_samples': 4})) \
+        .map('flame_gen', 'flame_list', lambda x: [y for y in x]) \
+        .map('flame_list', 'vec', ops.video_text_embedding.frozen_in_time(model_name='frozen_in_time_base_16_244', modality='video', device='cpu')) \
+        .output('video_path', 'flame_list', 'vec')
+)
 
-- Encode text:
-```python
-import towhee
+DataCollection(p('./demo_video.mp4')).show()
 
-towhee.dc(['kids feeding and playing with the horse']) \
-      .video_text_embedding.frozen_in_time(model_name='frozen_in_time_base_16_244', modality='text', device='cpu') \
-      .show()
 ```
-<img src="./result2.png" width="800px"/>
+<img src="./video_emb_result.png" width="800px"/>
 
-*Write a same pipeline with explicit inputs/outputs name specifications:*
+Read the text 'kids feeding and playing with the horse' to generate a text embedding. 
 
+- Encode text:
 ```python
-import towhee
-
-towhee.dc['path'](['./demo_video.mp4']) \
-      .video_decode.ffmpeg['path', 'frames'](sample_type='uniform_temporal_subsample', args={'num_samples': 4}) \
-      .runas_op['frames', 'frames'](func=lambda x: [y for y in x]) \
-      .video_text_embedding.frozen_in_time['frames', 'vec'](model_name='frozen_in_time_base_16_244', modality='video', device='cpu') \
-      .select['path', 'vec']() \
-      .show(formatter={'path': 'video_path'})
-
-towhee.dc['text'](["kids feeding and playing with the horse"]) \
-      .video_text_embedding.frozen_in_time['text','vec'](model_name='frozen_in_time_base_16_244', modality='text', device='cpu') \
-      .select['text', 'vec']() \
-      .show()
+from towhee.dc2 import pipe, ops, DataCollection
+
+p = (
+    pipe.input('text') \
+        .map('text', 'vec', ops.video_text_embedding.frozen_in_time(model_name='frozen_in_time_base_16_244', modality='text', device='cpu')) \
+        .output('text', 'vec')
+)
+
+DataCollection(p('kids feeding and playing with the horse')).show()
 ```
-<img src="./result3.png" width="800px"/>
-<img src="./result4.png" width="800px"/>
+<img src="./text_emb_result.png" width="800px"/>
 
 
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