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update the readme.

Signed-off-by: wxywb <xy.wang@zilliz.com>
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wxywb 2 years ago
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  1. 18
      README.md
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      tabular.png

18
README.md

@ -17,9 +17,16 @@ This operator can compare two ordered sequences, then detect the range which fea
```python ```python
placeholder
# simulate a video feature by 10 frames of 512d vectors.
videos_embeddings = np.random.randn(10,512)
videos_embeddings = videos_embeddings / np.linalg.norm(videos_embeddings,axis=1).reshape(10,-1)
towhee.dc['src','dest']([[videos_embeddings,videos_embeddings]]) \
.video_copy_detection.temporal_network[('src','dest'), ('range', 'range_score')]() \
.show()
``` ```
<img src="./tabular.png" alt="result" style="height:60px;"/>
<br /> <br />
@ -70,7 +77,7 @@ A Temporal Network operator takes two numpy.ndarray(shape(N,D) N: number of feat
**Parameters:** **Parameters:**
***src_video_vec data:*** *numpy.ndarray*
***src_video_vec*** *numpy.ndarray*
​ Source video feature vectors. ​ Source video feature vectors.
@ -79,10 +86,13 @@ A Temporal Network operator takes two numpy.ndarray(shape(N,D) N: number of feat
​ Destination video feature vectors. ​ Destination video feature vectors.
**Returns:** *List[List[Int]], List[float] *
**Returns:**
The returned aligned range and similarity score.
***aligned_ranges:*** *List[List[Int]]*
​ The returned aligned range.
***aligned_scores:*** *List[float]*
​ The returned similarity scores(length same as aligned_ranges).

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