When reading through the EVE documents I noticed this:
1.2.1 EVE 功能描述
1.360p检测速度>30FPS(工作主频 >300MHZ)
2.支持经典的HAAR特征分类器检测,特征数最高可达3200个
3.支持最大分辨率4K输入和内部缩放,支持感兴趣区域检测
4.支持4通道积分图计算,每秒处理13亿个特征
5.支持3通道特征计算
6.支持用户自定义目标尺寸,支持432个不同种类的检测框
7.支持最小64x64像素单图像检测
8.功耗低,360p全图检测<57mv
9.分类器可视化设计,提供一整套完整训练、调试、测试与评估工具
10.可定制化分类器,支持任意小变形刚性目标检测(人脸、车辆、车牌、行人、
It is a HAAR feature classifier. That is an old system from before the development of tensorflow type systems. So it is not clear if tensorflow can make use of the EVE hardware, it depends on how they implemented HAAR, is it microcode or a ROM? Only an AW engineer will know the answer. It does support customizable classifiers so it may be microcode.
On the other hand, a HAAR classifier is fine for our use case. But we need to be able to retrain it.
1.2.1 EVE 功能描述
1.360p检测速度>30FPS(工作主频 >300MHZ)
2.支持经典的HAAR特征分类器检测,特征数最高可达3200个
3.支持最大分辨率4K输入和内部缩放,支持感兴趣区域检测
4.支持4通道积分图计算,每秒处理13亿个特征
5.支持3通道特征计算
6.支持用户自定义目标尺寸,支持432个不同种类的检测框
7.支持最小64x64像素单图像检测
8.功耗低,360p全图检测<57mv
9.分类器可视化设计,提供一整套完整训练、调试、测试与评估工具
10.可定制化分类器,支持任意小变形刚性目标检测(人脸、车辆、车牌、行人、
It is a HAAR feature classifier. That is an old system from before the development of tensorflow type systems. So it is not clear if tensorflow can make use of the EVE hardware, it depends on how they implemented HAAR, is it microcode or a ROM? Only an AW engineer will know the answer. It does support customizable classifiers so it may be microcode.
On the other hand, a HAAR classifier is fine for our use case. But we need to be able to retrain it.