# 切换到install/rk3588/Linux/rknn_yolo_demo目录下,复制前面转换出的yolov8n_rknnopt_RK3588_i8.rknn模型文件到目录下, # 然后执行命令: cat@lubancat:xxx/install/rk3588/Linux/rknn_yolo_demo$ ./rknn_yolo_demo yolov8 q8 ./yolov8n_rknnopt_RK3588_i8.rknn ./model/bus640.jpg _80e_coco.rknn...
deep-learningnpuppyoloerk3588rk3568rk3566orange-pi-5rknpu2rock-5radxa-zero-3wradxa-zero-3-npurock5c UpdatedJun 19, 2024 C++ Paddle YOLO set: YOLOv3, PPYOLO, PPYOLOE, YOLOX, YOLOv5, YOLOv7 and so on. yolomulti-object-trackingtracking-by-detectionyolov3yolov5ppyoloyoloxbytetrackppyolov2...
cd python python convert.py <onnx_model> <TARGET_PLATFORM> <dtype(optional)> # such as: python convert.py ../model/ppyoloe_s.onnx rk3588 # output model will be saved as ../model/ppyoloe.rknn Description: <onnx_model>: Specify ONNX model path. <TARGET_PLATFORM>: Specify NPU ...
cd python python convert.py <onnx_model> <TARGET_PLATFORM> <dtype(optional)> # such as: python convert.py ../model/ppyoloe_s.onnx rk3588 # output model will be saved as ../model/ppyoloe.rknn Description: <onnx_model>: Specify ONNX model path. <TARGET_PLATFORM>: Specify NPU ...