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* add yolov5cls * fixed bugs * fixed bugs * fixed preprocess bug * add yolov5cls readme * deal with comments * Add YOLOv5Cls Note * add yolov5cls test Co-authored-by: Jason <jiangjiajun@baidu.com>
90 lines
2.9 KiB
Markdown
90 lines
2.9 KiB
Markdown
# YOLOv5Cls C++部署示例
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本目录下提供`infer.cc`快速完成YOLOv5Cls在CPU/GPU，以及GPU上通过TensorRT加速部署的示例。
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在部署前，需确认以下两个步骤
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- 1. 软硬件环境满足要求，参考[FastDeploy环境要求](../../../../../docs/environment.md)
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- 2. 根据开发环境，下载预编译部署库和samples代码，参考[FastDeploy预编译库](../../../../../docs/quick_start)
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以Linux上CPU推理为例，在本目录执行如下命令即可完成编译测试
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```bash
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mkdir build
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cd build
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wget https://bj.bcebos.com/fastdeploy/release/cpp/fastdeploy-linux-x64-0.2.1.tgz
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tar xvf fastdeploy-linux-x64-0.2.1.tgz
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cmake .. -DFASTDEPLOY_INSTALL_DIR=${PWD}/fastdeploy-linux-x64-0.2.1
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make -j
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#下载官方转换好的yolov5模型文件和测试图片
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wget https://bj.bcebos.com/paddlehub/fastdeploy/yolov5n-cls.onnx
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wget hhttps://gitee.com/paddlepaddle/PaddleClas/raw/release/2.4/deploy/images/ImageNet/ILSVRC2012_val_00000010.jpeg
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# CPU推理
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./infer_demo yolov5n-cls.onnx 000000014439.jpg 0
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# GPU推理
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./infer_demo yolov5n-cls.onnx 000000014439.jpg 1
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# GPU上TensorRT推理
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./infer_demo yolov5n-cls.onnx 000000014439.jpg 2
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```
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运行完成后返回结果如下所示
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```bash
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ClassifyResult(
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label_ids: 265,
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scores: 0.196327,
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)
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```
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以上命令只适用于Linux或MacOS, Windows下SDK的使用方式请参考:
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- [如何在Windows中使用FastDeploy C++ SDK](../../../../../docs/compile/how_to_use_sdk_on_windows.md)
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## YOLOv5Cls C++接口
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### YOLOv5Cls类
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```c++
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fastdeploy::vision::classification::YOLOv5Cls(
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const string& model_file,
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const string& params_file = "",
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const RuntimeOption& runtime_option = RuntimeOption(),
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const ModelFormat& model_format = ModelFormat::ONNX)
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```
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YOLOv5Cls模型加载和初始化，其中model_file为导出的ONNX模型格式。
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**参数**
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> * **model_file**(str): 模型文件路径
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> * **params_file**(str): 参数文件路径，当模型格式为ONNX时，此参数传入空字符串即可
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> * **runtime_option**(RuntimeOption): 后端推理配置，默认为None，即采用默认配置
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> * **model_format**(ModelFormat): 模型格式，默认为ONNX格式
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#### Predict函数
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> ```c++
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> YOLOv5Cls::Predict(cv::Mat* im, int topk = 1)
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> ```
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>
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> 模型预测接口，输入图像直接输出输出分类topk结果。
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>
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> **参数**
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>
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> > * **input_image**(np.ndarray): 输入数据，注意需为HWC，BGR格式
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> > * **topk**(int):返回预测概率最高的topk个分类结果，默认为1
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> **返回**
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>
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> > 返回`fastdeploy.vision.ClassifyResult`结构体，结构体说明参考文档[视觉模型预测结果](../../../../../docs/api/vision_results/)
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## 其它文档
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- [YOLOv5Cls 模型介绍](..)
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- [YOLOv5Cls Python部署](../python)
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- [模型预测结果说明](../../../../../docs/api/vision_results/)
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- [如何切换模型推理后端引擎](../../../../../docs/runtime/how_to_change_backend.md)
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