English | [简体中文](README_CN.md) # RKYOLO Python Deployment Example Two steps before deployment - 1. Software and hardware should meet the requirements. Refer to [FastDeploy Environment Requirements](../../../../../docs/cn/build_and_install/rknpu2.md) This directory provides examples that `infer.py` fast finishes the deployment of Picodet on RKNPU. The script is as follows ```bash git clone https://github.com/PaddlePaddle/FastDeploy.git cd FastDeploy/examples/vision/detection/rkyolo/python # download picture wget https://gitee.com/paddlepaddle/PaddleDetection/raw/release/2.4/demo/000000014439.jpg # infer yolov5 wget https://bj.bcebos.com/paddlehub/fastdeploy/rknpu2/yolov5-s-relu.zip unzip yolov5-s-relu.zip python3 infer_rkyolov5.py --model_file yolov5-s-relu/yolov5s_relu_tk2_RK3588_i8.rknn \ --image 000000014439.jpg # infer yolov7 wget https://bj.bcebos.com/paddlehub/fastdeploy/rknpu2/yolov7-tiny.zip unzip yolov7-tiny.zip python3 infer_rkyolov7.py --model_file yolov7-tiny/yolov7-tiny_tk2_RK3588_i8.rknn \ --image 000000014439.jpg # infer yolox wget https://bj.bcebos.com/paddlehub/fastdeploy/rknpu2/yolox-s.zip unzip yolox-s.zip python3 infer_rkyolox.py --model_file yolox-s/yoloxs_tk2_RK3588_i8.rknn \ --image 000000014439.jpg ``` ## common problem If you use the YOLOv5 model you have trained, you may encounter the problem of 'segmentation fault' after running the demo of FastDeploy. It is likely that the number of labels is inconsistent. You can use the following solution: ```python model.postprocessor.class_num = 3 ``` ## Note The model needs to be in NHWC format on RKNPU. The normalized image will be embedded in the RKNN model. Therefore, when we deploy with FastDeploy, call DisablePermute(C++) or `disable_permute(Python)` to disable normalization and data format conversion during preprocessing. ## Other Documents - [PaddleDetection Model Description](..) - [PaddleDetection C++ Deployment](../cpp) - [model prediction Results](../../../../../docs/api/vision_results/) - [Convert PaddleDetection RKNN Model Files](../README.md)