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88 lines
5.1 KiB
Markdown
Executable File
88 lines
5.1 KiB
Markdown
Executable File
English | [简体中文](README_CN.md)
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# PaddleDetection Python Deployment Example
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Before deployment, two steps require confirmation.
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- 1. Software and hardware should meet the requirements. Please refer to [FastDeploy Environment Requirements](../../../../../docs/cn/build_and_install/download_prebuilt_libraries.md)
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- 2. Install FastDeploy Python whl package. Refer to [FastDeploy Python Installation](../../../../../docs/cn/build_and_install/download_prebuilt_libraries.md)
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This directory provides examples that `infer_xxx.py` fast finishes the deployment of PPYOLOE/PicoDet models on CPU/GPU and GPU accelerated by TensorRT. The script is as follows
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```bash
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# Download deployment example code
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git clone https://github.com/PaddlePaddle/FastDeploy.git
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cd FastDeploy/examples/vision/detection/paddledetection/python/
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# Download the PPYOLOE model file and test images
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wget https://bj.bcebos.com/paddlehub/fastdeploy/ppyoloe_crn_l_300e_coco.tgz
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wget https://gitee.com/paddlepaddle/PaddleDetection/raw/release/2.4/demo/000000014439.jpg
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tar xvf ppyoloe_crn_l_300e_coco.tgz
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# CPU inference
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python infer_ppyoloe.py --model_dir ppyoloe_crn_l_300e_coco --image 000000014439.jpg --device cpu
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# GPU inference
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python infer_ppyoloe.py --model_dir ppyoloe_crn_l_300e_coco --image 000000014439.jpg --device gpu
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# TensorRT inference on GPU （Attention: It is somewhat time-consuming for the operation of model serialization when running TensorRT inference for the first time. Please be patient.）
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python infer_ppyoloe.py --model_dir ppyoloe_crn_l_300e_coco --image 000000014439.jpg --device gpu --use_trt True
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# Kunlunxin XPU Inference
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python infer_ppyoloe.py --model_dir ppyoloe_crn_l_300e_coco --image 000000014439.jpg --device kunlunxin
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# Huawei Ascend Inference
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python infer_ppyoloe.py --model_dir ppyoloe_crn_l_300e_coco --image 000000014439.jpg --device ascend
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```
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The visualized result after running is as follows
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<div align="center">
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<img src="https://user-images.githubusercontent.com/19339784/184326520-7075e907-10ed-4fad-93f8-52d0e35d4964.jpg", width=480px, height=320px />
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</div>
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## PaddleDetection Python Interface
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```python
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fastdeploy.vision.detection.PPYOLOE(model_file, params_file, config_file, runtime_option=None, model_format=ModelFormat.PADDLE)
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fastdeploy.vision.detection.PicoDet(model_file, params_file, config_file, runtime_option=None, model_format=ModelFormat.PADDLE)
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fastdeploy.vision.detection.PaddleYOLOX(model_file, params_file, config_file, runtime_option=None, model_format=ModelFormat.PADDLE)
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fastdeploy.vision.detection.YOLOv3(model_file, params_file, config_file, runtime_option=None, model_format=ModelFormat.PADDLE)
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fastdeploy.vision.detection.PPYOLO(model_file, params_file, config_file, runtime_option=None, model_format=ModelFormat.PADDLE)
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fastdeploy.vision.detection.FasterRCNN(model_file, params_file, config_file, runtime_option=None, model_format=ModelFormat.PADDLE)
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fastdeploy.vision.detection.MaskRCNN(model_file, params_file, config_file, runtime_option=None, model_format=ModelFormat.PADDLE)
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fastdeploy.vision.detection.SSD(model_file, params_file, config_file, runtime_option=None, model_format=ModelFormat.PADDLE)
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fastdeploy.vision.detection.PaddleYOLOv5(model_file, params_file, config_file, runtime_option=None, model_format=ModelFormat.PADDLE)
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fastdeploy.vision.detection.PaddleYOLOv6(model_file, params_file, config_file, runtime_option=None, model_format=ModelFormat.PADDLE)
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fastdeploy.vision.detection.PaddleYOLOv7(model_file, params_file, config_file, runtime_option=None, model_format=ModelFormat.PADDLE)
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fastdeploy.vision.detection.RTMDet(model_file, params_file, config_file, runtime_option=None, model_format=ModelFormat.PADDLE)
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```
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PaddleDetection model loading and initialization, among which model_file and params_file are the exported Paddle model format. config_file is the configuration yaml file exported by PaddleDetection simultaneously
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**Parameter**
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> * **model_file**(str): Model file path
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> * **params_file**(str): Parameter file path
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> * **config_file**(str): Inference configuration yaml file path
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> * **runtime_option**(RuntimeOption): Backend inference configuration. None by default. (use the default configuration)
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> * **model_format**(ModelFormat): Model format. Paddle format by default
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### predict Function
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PaddleDetection models, including PPYOLOE/PicoDet/PaddleYOLOX/YOLOv3/PPYOLO/FasterRCNN, all provide the following member functions for image detection
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> ```python
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> PPYOLOE.predict(image_data, conf_threshold=0.25, nms_iou_threshold=0.5)
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> ```
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>
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> Model prediction interface. Input images and output results directly.
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>
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> **Parameter**
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>
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> > * **image_data**(np.ndarray): Input data in HWC or BGR format
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> **Return**
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>
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> > Return `fastdeploy.vision.DetectionResult` structure. Refer to [Vision Model Prediction Results](../../../../../docs/api/vision_results/) for the description of the structure.
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## Other Documents
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- [PaddleDetection Model Description](..)
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- [PaddleDetection C++ Deployment](../cpp)
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- [Model Prediction Results](../../../../../docs/api/vision_results/)
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- [How to switch the model inference backend engine](../../../../../docs/cn/faq/how_to_change_backend.md)
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