利用keras建立 faster rcnn网络，训练完成后，将检测api释放为rest接口，方便后端调用
1. wget https://www.python.org/ftp/python/3.5.2/Python-3.5.2.tar.xz
2. tar Jxvf Python-3.5.2.tar.xz
3. cd Python-3.5.2
4. ./configure --prefix=/usr/local/python3
5. make && make install # 成功提示：Ignoring ensurepip failure: pip 7.1.2 requires SSL/TLS
6. ln -s /usr/local/python3/bin/pip3.5 /usr/local/bin/pip3.5
7. ln -s /usr/local/python3/bin/python3.5 /usr/local/bin/python3
8. pip3.5 install --upgrade pip
9. pip3.5 install keras
10. pip3.5 install tensorflow
11. pip3.5 install flask
12. pip3.5 install flask_httpauth
13. pip3.5 install werkzeug
14.pip install opencv-python数据集为VOC2007，数据格式如下：
顶层目录
Annotations —目标真值区域
ImageSets —-类别标签
JPEGImages —–图像
生成数据集，可参考博客
https://blog.csdn.net/xvshu/article/details/81298625
python train_frcnn.py -p $your_train_voc2007_path
python test_frcnn.py -p $your_test_img_path
测试结果：
python frcnn_api.py
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