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69 lines
2.7 KiB
Markdown
69 lines
2.7 KiB
Markdown
English | [简体中文](README_CN.md)
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# BlazeFace 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/en/build_and_install/download_prebuilt_libraries.md)
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- 2. Install FastDeploy Python whl package. Refer to [FastDeploy Python Installation](../../../../../docs/en/build_and_install/download_prebuilt_libraries.md)
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This directory provides examples that `infer.py` fast finishes the deployment of BlazeFace on CPU/GPU.
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```bash
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# Download the example code for deployment
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git clone https://github.com/PaddlePaddle/FastDeploy.git
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cd examples/vision/facedet/blazeface/python/
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# Download BlazeFace model files and test images
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wget https://raw.githubusercontent.com/DefTruth/lite.ai.toolkit/main/examples/lite/resources/test_lite_face_detector_3.jpg
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wget https://bj.bcebos.com/paddlehub/fastdeploy/blazeface-1000e.tgz
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# Use blazeface-1000e model
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# CPU Inference
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python infer.py --model blazeface-1000e/ --image test_lite_face_detector_3.jpg --device cpu
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# GPU Inference
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python infer.py --model blazeface-1000e/ --image test_lite_face_detector_3.jpg --device gpu
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```
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The visualized result after running is as follows
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<img width="640" src="https://user-images.githubusercontent.com/67993288/184301839-a29aefae-16c9-4196-bf9d-9c6cf694f02d.jpg">
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## BlazeFace Python Interface
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```python
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fastdeploy.vision.facedet.BlzaeFace(model_file, params_file=None, runtime_option=None, config_file=None, model_format=ModelFormat.PADDLE)
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```
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BlazeFace model loading and initialization, among which model_file is the exported PADDLE model format
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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. No need to set when the model is in PADDLE format
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> * **config_file**(str): config file path. No need to set when the model is in PADDLE format
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> * **runtime_option**(RuntimeOption): Backend inference configuration. None by default, which is 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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> ```python
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> BlazeFace.predict(input_image)
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> ```
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> Through let BlazeFace.postprocessor.conf_threshold = 0.2，to modify conf_threshold
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>
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> Model prediction interface. Input images and output detection results.
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>
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> **Parameter**
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>
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> > * **input_image**(np.ndarray): Input image in HWC or BGR format
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> **Return**
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>
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> > Return`fastdeploy.vision.FaceDetectionResult` structure. Refer to [Vision Model Prediction Results](../../../../../docs/api/vision_results/) for its description.
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## Other Documents
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- [BlazeFace Model Description](..)
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- [BlazeFace C++ Deployment](../cpp)
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- [Model Prediction Results](../../../../../docs/api/vision_results/)
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