![Tensorflow non maximum suppression Tensorflow non maximum suppression](https://user-images.githubusercontent.com/25801568/44536982-51463c80-a706-11e8-9118-8e7d68dea868.png)
A scalar integer Tensor representing the maximum number of boxes to be selected by non - max suppression. SSD and Yolo object detection networks ( from 12). I have tried digging around their repo as well with no luck so I ended up just getting the code from my editor.
![Tensorflow non maximum suppression Tensorflow non maximum suppression](https://devjin-blog.com/static/profile-2b2699682c76132b1611c336a9b8bb28.png)
I used PyCharm so I simply did . Autres résultats sur stackoverflow. TensorFlow Object Detection API - GitHub github. System information The bugs are not related to my system. This was mentioned in several issues under the name : non max suppression work . Most implementations use a CUDA-based non - maximum suppression (NMS) for. An optional `float`.
Detailed description: NonMaxSuppression layer. Tensorflow Object Detection API might be helpful for . In this algorithm we propose additional . The module performs non - maxima suppression inside the module. As users we then have to use techniques such as non - max suppression to get. Non-Maximum Suppres-. Answering my own question (though open to better solutions): import tensorflow as tf import numpy as np def non_max_suppression(input, window_size): . It then performs NMS ( non - maximum suppression ) which prunes away most of . NMS: non maximum suppression.
![Tensorflow non maximum suppression Tensorflow non maximum suppression](https://pic2.zhimg.com/v2-d86ade3cb8291c5e984f027b4c1731a1_r.jpg)
After non - max suppression , it then outputs recognized objects together with the bounding.