person_monitor_fy/dependence/PaddleDetection/deploy/EXPORT_ONNX_MODEL_en.md

PaddleDetection Model Export as ONNX Format Tutorial

PaddleDetection Model support is saved in ONNX format and the list of current test support is as follows | Model | OP Version | NOTE | | :---- | :----- | :--- | | YOLOv3 | 11 | Only batch=1 inferring is supported. Model export needs fixed shape | | PPYOLO | 11 | Only batch=1 inferring is supported. A MatrixNMS will be converted to an NMS with slightly different precision; Model export needs fixed shape | | PPYOLOv2 | 11 | Only batch=1 inferring is supported. MatrixNMS will be converted to NMS with slightly different precision; Model export needs fixed shape | | PPYOLO-Tiny | 11 | Only batch=1 inferring is supported. Model export needs fixed shape | | FCOS | 11 |Only batch=1 inferring is supported | | PAFNet | 11 |- | | TTFNet | 11 |-| | SSD | 11 |Only batch=1 inferring is supported |

The function of saving ONNX is provided by Paddle2ONNX. If there is feedback on related problems during conversion, Communicate with engineers in Paddle2ONNX's Github project via ISSUE.

Export Tutorial

Step 1. Export the Paddle deployment model

Export procedure reference documentTutorial on PaddleDetection deployment model export, take YOLOv3 of COCO dataset training as an example

cd PaddleDetection
python tools/export_model.py -c configs/yolov3/yolov3_darknet53_270e_coco.yml \
                             -o weights=https://paddledet.bj.bcebos.com/models/yolov3_darknet53_270e_coco.pdparams \
                             TestReader.inputs_def.image_shape=[3,608,608] \
                             --output_dir inference_model

The derived models were saved in inference_model/yolov3_darknet53_270e_coco/, with the structure as follows

yolov3_darknet
  ├── infer_cfg.yml          # Model configuration file information
  ├── model.pdiparams        # Static diagram model parameters
  ├── model.pdiparams.info   # Parameter Information is not required
  └── model.pdmodel          # Static diagram model file

checkTestReader.inputs_def.image_shape, For YOLO series models, specify this parameter when exporting; otherwise, the conversion fails

Step 2. Convert the deployment model to ONNX format

Install Paddle2ONNX (version 0.6 or higher)

pip install paddle2onnx

Use the following command to convert

paddle2onnx --model_dir inference_model/yolov3_darknet53_270e_coco \
            --model_filename model.pdmodel \
            --params_filename model.pdiparams \
            --opset_version 11 \
            --save_file yolov3.onnx

The transformed model is under the current pathyolov3.onnx