# Filter Tiny Segments

*author: Chen Zhang*


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## Description

This operator can filter tiny detected segments with format of list of `[start_second_1, start_second_2, end_second_1, end_second_2]`
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## Code Example


```python
import towhee
towhee.dc['pred']([[[0, 0, 100, 100], [0, 0, 10, 10], [0, 0, 60, 10]]]) \
      .video_copy_detection.filter_tiny_segments['pred', 'filtered_pred'](filter_s_thresh=20) \
      .show()
```

![](result.png)



## Factory Constructor

Create the operator via the following factory method

***filter_tiny_segments(filter_s_thresh, segment_len_rate)***


**Parameters:**

​   ***filter_s_thresh:*** *float*

​   Use a thresh to filter detected box which is smaller than it.

​   ***segment_len_rate:*** *float*

​   Filter expect longer then segment_len_rate * video length. Only useful for filter expect near video length segments.

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## Interface

A Temporal Network operator takes two numpy.ndarray(shape(N,D) N: number of features. D: dimension of features) and get the duplicated ranges and scores.


**Parameters:**

​	***pred_value:*** *List*

​  List of predicted segment second infos of a video pair

​  ***sim_hw:*** *Tuple*

​  Similarity matrix height and weight of a video pair. If sample rate is 1s, sim_hw is also the lengths of these videos.


**Returns:**

​	***res_pred_list:*** *List*

​   List of filtered predicted segment second infos