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carla-test-project's Introduction

基于CARLA的测试方法实现

环境要求

  • github上面的keras-yolo3 https://github.com/qqwweee/keras-yolo3
  • tensorflow
  • 相对应的cuda和cudnn
  • staticTest需要在python环境中安装pyqt5
  • 将仓库文件放在keras主文件夹下即可

  • 静态测试
静态测试是对于一组图片进行的目标测试,效果如下

其主要思路就是用pyqt5作为界面设计,将CARLA中获得的图片逐张进行目标检测,对应的文件为staticTest.py
  • 动态测试
动态测试是将将CARLA中的图片取出进行处理,再进行目标检测,具体的效果如下

其中主要的思路就是讲获得的图片数据放入到数组中,按照顺序进行展现,其中比较关键的代码如下,可以较快的加快buffer数据转化为图像的速度,对应的文件是videoTest.py
array = np.frombuffer(cur.raw_data, dtype=np.dtype("uint8"))
array = np.reshape(array, (cur.height, cur.width, 4))
  • 对抗样本测试
在测试中引入了对抗样本,具体效果如下

其主要思路是用演化算法的对抗样本生成手法,在图像中加入噪声,使得目标识别网络失灵,从而检测目标算法鲁棒性,对应的文件为adversialTest.py

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