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@@ -0,0 +1,34 @@
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+## Tensorrt 推理 resnet 分类模型
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+
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+### 使用tensorrt推理resnet模型流程
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+#### 模型转换
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+```shell
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+trtexec --onnx=resnet.onnx --saveEngine=resnet.engine --fp16 --verbose
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+```
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+#### 代码使用
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+1. 直接推理
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+ ```C++
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+ cv::Mat image = cv::imread("inference/car.jpg");
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+ auto resnet = resnet::load("resnet.engine");
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+ if (resnet == nullptr) return;
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+ auto attr = resnet->forward(cvimg(image));
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+ printf("score : %lf, label : %d\n", attr.confidence, attr.class_label);
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+ /*
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+ [infer.cu:393]: Infer 0x564a443b3440 [StaticShape]
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+ [infer.cu:405]: Inputs: 1
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+ [infer.cu:409]: 0.input.1 : shape {1x3x224x224}
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+ [infer.cu:412]: Outputs: 1
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+ [infer.cu:416]: 0.343 : shape {1x3}
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+ score : 0.997001, label : 2
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+ */
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+ ```
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+
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+2. cpm模式
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+ ```C++
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+ cv::Mat image = cv::imread("inference/car.jpg");
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+
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+ cpm::Instance<resnet::Attribute, resnet::Image, resnet::Infer> cpmi;
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+ bool ok = cpmi.start([] { return resnet::load("resnet.engine"); }, max_infer_batch);
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+
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+ cpmi.commit(cvimg(image)).get();
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+ ```
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