基于u版yolo框架作为目标检测器,pytorch版本deepsort做reID和目标跟踪器,完成实时视频数人的应用
This is a project to deploy object tracking algorithm with yolov5 and TensorRT. Sort and Deep-sort algorithm are used to track the objects.(本项目用tensorrt进行目标跟踪的部署,检测器采用yolov5,跟踪器采用sort和deep-sort)
开源视频人脸跟踪算法,基于mtcnn人脸加测+onet人脸跟踪,移动端速度可以达到150fps+。该项目基于Android工程,提供底层JNI实现,使用者可以自行编译移植到其他平台。算法依赖ncnn深度学习计算库,体积小,易于集成。
开源视频人脸跟踪算法,基于mtcnn人脸检测+onet人脸跟踪,在i7-9700k的cpu检测速度可高达250fps
darknet2ncnn将darknet 模型转换为ncnn模型,实现darknet网络模型在移动端的快速部署
🍅 Ncnn deployment on mobile,support:YOLOv5s,YOLOv4-tiny,MobileNetV2-YOLOv3-nano,Simple-Pose,Yolact,ChineseOCR-lite,ENet,Landmark106 and DBFace on camera.
MobileNetV2-YOLOv3-Nano的Darknet实现:移动终端设计的目标检测网络,计算量0.5BFlops!支持NCNN及MNN部署,华为P40在MNN开启ARM82
Some great implement of deep learning algorithm in Nvidia jetson nano platform. Such as face recognition, object detection, etc.
TensorRT YOLOv4, YOLOv3, SSD, MTCNN, and GoogLeNet