JA-cmd-wq/yolov8-helmet-rk3588-multithread

推理 180 FPS , 全链路 175 FPS , rk3588部署yolov5，利用线程池实现npu推理加速；Deploying YOLOv5 on RKNN-3588, utilizing a thread pool to achieve NPU inference acceleration.

Real-time YOLOv8n UAV detection on the RK3588S NPU | saturates the sensor at 46 FPS | ~140 MB RAM | fully hardware-accelerated (ISP+RGA+NPU) | on-device LLM scene summaries

YOLOv8 using TensorRT accelerate !

ncnn android yolov8 realtime detection, segmentation, pose estimation, classification and obb

🔥🔥🔥TensorRT for YOLOv8、YOLOv8-Pose、YOLOv8-Seg、YOLOv8-Cls、YOLOv7、YOLOv6、YOLOv5、YOLONAS......🚀🚀🚀CUDA IS ALL YOU NEED.🍎🍎🍎

Cross-Platform Production-ready C++ inference engine for YOLO models (v5-v12, YOLO26). Unified API for detection, segmentation, pose estimation, OBB, and classification. Built on ONNX Runtime and OpenCV. Optimized for CPU/GPU with quantization support.

🚀 Easier & Faster YOLO Deployment Toolkit for NVIDIA 🛠️

mono / stereo depth estimation + yolo object detection with deployment on Jeston nano / TX2 / GeForce by TensorRT