mirror of
				https://github.com/PaddlePaddle/FastDeploy.git
				synced 2025-11-01 04:12:58 +08:00 
			
		
		
		
	 cbf88a46fa
			
		
	
	cbf88a46fa
	
	
	
		
			
			* 第一次提交 * 补充一处漏翻译 * deleted: docs/en/quantize.md * Update one translation * Update en version * Update one translation in code * Standardize one writing * Standardize one writing * Update some en version * Fix a grammer problem * Update en version for api/vision result * Merge branch 'develop' of https://github.com/charl-u/FastDeploy into develop * Checkout the link in README in vision_results/ to the en documents * Modify a title * Add link to serving/docs/ * Finish translation of demo.md * Update english version of serving/docs/ * Update title of readme * Update some links * Modify a title * Update some links * Update en version of java android README * Modify some titles * Modify some titles * Modify some titles * modify article to document * update some english version of documents in examples * Add english version of documents in examples/visions * Sync to current branch * Add english version of documents in examples * Add english version of documents in examples * Add english version of documents in examples * Update some documents in examples * Update some documents in examples * Update some documents in examples * Update some documents in examples * Update some documents in examples * Update some documents in examples * Update some documents in examples * Update some documents in examples * Update some documents in examples
		
			
				
	
	
		
			96 lines
		
	
	
		
			4.1 KiB
		
	
	
	
		
			Markdown
		
	
	
	
	
	
			
		
		
	
	
			96 lines
		
	
	
		
			4.1 KiB
		
	
	
	
		
			Markdown
		
	
	
	
	
	
| English | [简体中文](README_CN.md)
 | |
| 
 | |
| # UltraFace C++ Deployment Example
 | |
| 
 | |
| This directory provides examples that `infer.cc` fast finishes the deployment of UltraFace on CPU/GPU and GPU accelerated by TensorRT. 
 | |
| 
 | |
| Before deployment, two steps require confirmation
 | |
| 
 | |
| - 1. Software and hardware should meet the requirements. Please refer to [FastDeploy Environment Requirements](../../../../../docs/en/build_and_install/download_prebuilt_libraries.md)  
 | |
| - 2. Download the precompiled deployment library and samples code according to your development environment. Refer to [FastDeploy Precompiled Library](../../../../../docs/en/build_and_install/download_prebuilt_libraries.md)
 | |
| 
 | |
| Taking the CPU inference on Linux as an example, the compilation test can be completed by executing the following command in this directory. FastDeploy version 0.7.0 or above (x.x.x>=0.7.0) is required to support this model.
 | |
| 
 | |
| ```bash
 | |
| mkdir build
 | |
| cd build
 | |
| # Download the FastDeploy precompiled library. Users can choose your appropriate version in the `FastDeploy Precompiled Library` mentioned above 
 | |
| wget https://bj.bcebos.com/fastdeploy/release/cpp/fastdeploy-linux-x64-x.x.x.tgz
 | |
| tar xvf fastdeploy-linux-x64-x.x.x.tgz
 | |
| cmake .. -DFASTDEPLOY_INSTALL_DIR=${PWD}/fastdeploy-linux-x64-x.x.x
 | |
| make -j
 | |
| 
 | |
| # Download the official converted UltraFace model files and test images 
 | |
| wget https://bj.bcebos.com/paddlehub/fastdeploy/version-RFB-320.onnx
 | |
| wget https://raw.githubusercontent.com/DefTruth/lite.ai.toolkit/main/examples/lite/resources/test_lite_face_detector_3.jpg
 | |
| 
 | |
| 
 | |
| # CPU inference
 | |
| ./infer_demo version-RFB-320.onnx test_lite_face_detector_3.jpg 0
 | |
| # GPU inference
 | |
| ./infer_demo version-RFB-320.onnx test_lite_face_detector_3.jpg 1
 | |
| # TensorRT inference on GPU
 | |
| ./infer_demo version-RFB-320.onnx test_lite_face_detector_3.jpg 2
 | |
| ```
 | |
| 
 | |
| The visualized result after running is as follows
 | |
| 
 | |
| <img width="640" src="https://user-images.githubusercontent.com/67993288/184301821-0788483b-a72b-42b0-a566-b6430f184f6e.jpg">
 | |
| 
 | |
| The above command works for Linux or MacOS. For SDK use-pattern in Windows, refer to:
 | |
| 
 | |
| - [How to use FastDeploy C++ SDK in Windows](../../../../../docs/en/faq/use_sdk_on_windows.md)
 | |
| 
 | |
| ## UltraFace C++ Interface 
 | |
| 
 | |
| ### UltraFace Class
 | |
| 
 | |
| ```c++
 | |
| fastdeploy::vision::facedet::UltraFace(
 | |
|         const string& model_file,
 | |
|         const string& params_file = "",
 | |
|         const RuntimeOption& runtime_option = RuntimeOption(),
 | |
|         const ModelFormat& model_format = ModelFormat::ONNX)
 | |
| ```
 | |
| 
 | |
| UltraFace model loading and initialization, among which model_file is the exported ONNX model format
 | |
| 
 | |
| **Parameter**
 | |
| 
 | |
| > * **model_file**(str): Model file path 
 | |
| > * **params_file**(str): Parameter file path. Only passing an empty string when the model is in ONNX format
 | |
| > * **runtime_option**(RuntimeOption): Backend inference configuration. None by default, which is the default configuration
 | |
| > * **model_format**(ModelFormat): Model format. ONNX format by default
 | |
| 
 | |
| #### Predict Function
 | |
| 
 | |
| > ```c++
 | |
| > UltraFace::Predict(cv::Mat* im, FaceDetectionResult* result,
 | |
| >              float conf_threshold = 0.25,
 | |
| >              float nms_iou_threshold = 0.5)
 | |
| > ```
 | |
| >
 | |
| > Model prediction interface. Input images and output detection results.
 | |
| >
 | |
| > **Parameter**
 | |
| >
 | |
| > > * **im**: Input images in HWC or BGR format
 | |
| > > * **result**: Detection results, including detection box and confidence of each box. Refer to [Vision Model Prediction Result](../../../../../docs/api/vision_results/) for FaceDetectionResult
 | |
| > > * **conf_threshold**: Filtering threshold of detection box confidence
 | |
| > > * **nms_iou_threshold**: iou threshold during NMS processing
 | |
| 
 | |
| 
 | |
| 
 | |
| ### Class Member Variable
 | |
| 
 | |
| #### Pre-processing Parameter
 | |
| 
 | |
| Users can modify the following pre-processing parameters to their needs, which affects the final inference and deployment results
 | |
| 
 | |
| > > * **size**(vector<int>): This parameter changes the size of the resize used during preprocessing, containing two integer elements for [width, height] with default value [320, 240]
 | |
| 
 | |
| - [Model Description](../../)
 | |
| - [Python Deployment](../python)
 | |
| - [Vision Model Prediction Results](../../../../../docs/api/vision_results/)
 | |
| - [How to switch the model inference backend engine](../../../../../docs/en/faq/how_to_change_backend.md)
 |