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[docs][win] add windows c++ sdk demo to examples (#136)
* [docs] format docs with markdown with language tags * [docs][win] add windows c++ sdk demo * [docs][win] add windows c++ sdk demo to examples * [docs][api] update runtime_option docs
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@@ -9,14 +9,14 @@
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以Linux上ResNet50_vd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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```
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```bash
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#下载SDK,编译模型examples代码(SDK中包含了examples代码)
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wget https://bj.bcebos.com/paddlehub/fastdeploy/libs/0.2.0/fastdeploy-linux-x64-gpu-0.2.0.tgz
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tar xvf fastdeploy-linux-x64-gpu-0.2.0.tgz
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cd fastdeploy-linux-x64-gpu-0.2.0/examples/vision/classification/paddleclas/cpp
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mkdir build
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cd build
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cmake .. -DFASTDEPLOY_INSTALL_DIR=${PWD}/../../../../../../../fastdeploy-linux-x64-gpu-0.2.0
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cmake .. -DFASTDEPLOY_INSTALL_DIR=${PWD}/../../../../../../../fastdeploy-linux-x64-gpu-0.2.0
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make -j
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# 下载ResNet50_vd模型文件和测试图片
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@@ -33,11 +33,14 @@ wget https://gitee.com/paddlepaddle/PaddleClas/raw/release/2.4/deploy/images/Ima
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./infer_demo ResNet50_vd_infer ILSVRC2012_val_00000010.jpeg 2
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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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## PaddleClas C++接口
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### PaddleClas类
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```
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```c++
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fastdeploy::vision::classification::PaddleClasModel(
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const string& model_file,
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const string& params_file,
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@@ -58,14 +61,14 @@ PaddleClas模型加载和初始化,其中model_file, params_file为训练模
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#### Predict函数
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> ```
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> ```c++
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> PaddleClasModel::Predict(cv::Mat* im, ClassifyResult* result, int topk = 1)
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> ```
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>
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>
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> 模型预测接口,输入图像直接输出检测结果。
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>
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>
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> **参数**
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>
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>
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> > * **im**: 输入图像,注意需为HWC,BGR格式
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> > * **result**: 分类结果,包括label_id,以及相应的置信度, ClassifyResult说明参考[视觉模型预测结果](../../../../../docs/api/vision_results/)
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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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