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
# Download the example code for deployment
git clone https://github.com/PaddlePaddle/FastDeploy.git
cd FastDeploy/examples/vision/detection/rkyolo/python

# Download images
wget https://gitee.com/paddlepaddle/PaddleDetection/raw/release/2.4/demo/000000014439.jpg

# copy model
cp -r ./model /path/to/FastDeploy/examples/vision/detection/rkyolo/python

# Inference
python3 infer.py --model_file ./model/  \
                  --image 000000014439.jpg
```


## 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)