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update readme with dc2

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ChengZi 2 years ago
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  1. 49
      README.md
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      text_emb_output.png
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      vect_explicit_video.png
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      vect_simplified_text.png
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49
README.md

@ -24,40 +24,33 @@ Read the text 'kids feeding and playing with the horse' to generate an text embe
*Write the pipeline in simplified style*: *Write the pipeline in simplified style*:
```python ```python
import towhee
from towhee.dc2 import pipe, ops, DataCollection
towhee.dc(['./demo_video.mp4']) \
.video_decode.ffmpeg(sample_type='uniform_temporal_subsample', args={'num_samples': 12}) \
.runas_op(func=lambda x: [y for y in x]) \
.clip4clip(model_name='clip_vit_b32', modality='video', device='cpu') \
.show()
p = (
pipe.input('text') \
.map('text', 'vec', ops.video_text_embedding.clip4clip(model_name='clip_vit_b32', modality='text', device='cuda:1')) \
.output('text', 'vec')
)
towhee.dc(['kids feeding and playing with the horse']) \
.clip4clip(model_name='clip_vit_b32', modality='text', device='cpu') \
.show()
```
![](vect_simplified_video.png)
![](vect_simplified_text.png)
DataCollection(p('kids feeding and playing with the horse')).show()
*Write a same pipeline with explicit inputs/outputs name specifications:*
```
![](text_emb_output.png)
```python ```python
import towhee
towhee.dc['path'](['./demo_video.mp4']) \
.video_decode.ffmpeg['path', 'frames'](sample_type='uniform_temporal_subsample', args={'num_samples': 12}) \
.runas_op['frames', 'frames'](func=lambda x: [y for y in x]) \
.clip4clip['frames', 'vec'](model_name='clip_vit_b32', modality='video', device='cpu') \
.show()
towhee.dc['text'](["kids feeding and playing with the horse"]) \
.clip4clip['text','vec'](model_name='clip_vit_b32', modality='text', device='cpu') \
.select['text', 'vec']() \
.show()
```
from towhee.dc2 import pipe, ops, DataCollection
![](vect_explicit_video.png)
![](vect_explicit_text.png)
p = (
pipe.input('video_path') \
.map('video_path', 'flame_gen', ops.video_decode.ffmpeg(sample_type='uniform_temporal_subsample', args={'num_samples': 12})) \
.map('flame_gen', 'flame_list', lambda x: [y for y in x]) \
.map('flame_list', 'vec', ops.video_text_embedding.clip4clip(model_name='clip_vit_b32', modality='video', device='cuda:2')) \
.output('video_path', 'flame_list', 'vec')
)
DataCollection(p('./demo_video.mp4')).show()
```
![](video_emb_ouput.png)
<br /> <br />

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