# Select video

*author: Chen Zhang*


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## Description

This operator select input list by simply aggregating, sorting and then filtering it.
<br />


## Code Example

For two input lists: video urls and scores, aggregate url by reduce_function, then sort aggregated scores, then select top k results.

```python
from towhee import pipe, ops, DataCollection

p = (
    pipe.input('video_urls', 'scores') \
        .map(('video_urls', 'scores'), 'res', ops.video_copy_detection.select_video(top_k=2, reduce_function='mean', reverse=True)) \
        .output('video_urls', 'scores', 'res')
)

DataCollection(p(['a', 'a', 'c', 'a', 'b', 'b', 'c', 'c'], [2, 8, 9.3, 5, 2, 1, 0, -1])).show()
```

![](mean.png)   

```python
from towhee import pipe, ops, DataCollection

p = (
    pipe.input('video_urls', 'scores') \
        .map(('video_urls', 'scores'), 'res', ops.video_copy_detection.select_video(top_k=2, reduce_function='sum', reverse=True)) \
        .output('video_urls', 'scores', 'res')
)

DataCollection(p(['a', 'a', 'c', 'a', 'b', 'b', 'c', 'c'], [2, 8, 9.3, 5, 2, 1, 0, -1])).show()
```  
![](mean.png) 

```python
from towhee import pipe, ops, DataCollection

p = (
    pipe.input('video_urls', 'scores') \
        .map(('video_urls', 'scores'), 'res', ops.video_copy_detection.select_video(top_k=2, reduce_function='max', reverse=True)) \
        .output('video_urls', 'scores', 'res')
)

DataCollection(p(['a', 'a', 'c', 'a', 'b', 'b', 'c', 'c'], [2, 8, 9.3, 5, 2, 1, 0, -1])).show()
```

![](max.png) 


```python
from towhee import pipe, ops, DataCollection

p = (
    pipe.input('video_urls', 'scores') \
        .map(('video_urls', 'scores'), 'res', ops.video_copy_detection.select_video(top_k=2, reduce_function='min', reverse=True)) \
        .output('video_urls', 'scores', 'res')
)

DataCollection(p(['a', 'a', 'c', 'a', 'b', 'b', 'c', 'c'], [2, 8, 9.3, 5, 2, 1, 0, -1])).show()
```

![](min.png) 


<br />



## Factory Constructor

Create the operator via the following factory method

***select_video(top_k: int, reduce_function: str, reverse: bool)***

**Parameters:**

​   ***top_k:*** *int*

​   Select top k result.


​   ***reduce_function:*** *str*

​   Aggregate function name, support name:
- sum
- mean
- max
- min

​   ***reverse:*** *bool*

​   Whether sorted result is reversed.

<br />



## Interface


**Parameters:**

​	***video_urls:*** *List[str]*

​  Video urls.

​	***scores:*** *List[float]*

​  Every video scores.


**Returns:** *List[str]*

​   Selected video url results.





# More Resources

- [Extracting Event Highlights Using iYUNDONG Sports App - Zilliz blog](https://zilliz.com/blog/Extracting-Events-Highlights-Using-iYUNDONG-Sports-App): iYUNDONG continually seeks to support its users with real-time image retrieval services. When it decided to develop its App, it chose Milvus to build its core image search system. Discover how Milvus, an open-source vector database, can help build an intelligent image retrieval system that can extract sport event highlights.
- [4 Steps to Building a Video Search System - Zilliz blog](https://zilliz.com/blog/building-video-search-system-with-milvus): Searching for videos by image with Milvus
- [Vector Database Use Cases: Video Similarity Search - Zilliz](https://zilliz.com/vector-database-use-cases/video-similarity-search): Experience a 10x performance boost and unparalleled precision when your video similarity search system is powered by Zilliz Cloud.