Attach libtorch inference results (#138)

* Attach libtorch inference results

* Update README.md

README.md

@@ -105,7 +105,7 @@ torch.save(model.state_dict(), 'yolov5s_updated.pt')
 
 ### Inference on `LibTorch` backend 🚀
 
-We provide a [notebook](notebooks/inference-pytorch-export-libtorch.ipynb) to demonstrate how the model is transformed into `torchscript`. And we provide an [C++ example](./deployment) of how to infer with the transformed `torchscript` model. For details see the [GitHub Actions](.github/workflows/ci_test.yml).
+We provide a [notebook](notebooks/inference-pytorch-export-libtorch.ipynb) to demonstrate how the model is transformed into `torchscript`. And we provide an [C++ example](./deployment/libtorch) of how to infer with the transformed `torchscript` model. For details see the [GitHub Actions](.github/workflows/ci_test.yml).
 
 ## 🎨 Model Graph Visualization
 
@@ -120,4 +120,4 @@ Now, `yolort` can draw the model graph directly, checkout our [model-graph-visua
 
 ## 🤗 Contributing
 
-We appreciate all contributions. If you are planning to contribute back bug-fixes, please do so without any further discussion. If you plan to contribute new features, utility functions or extensions, please first open an issue and discuss the feature with us. *BTW, leave a 🌟 if you liked it, this means a lot to us, and this is the easiest way to support us* :)
+We appreciate all contributions. If you are planning to contribute back bug-fixes, please do so without any further discussion. If you plan to contribute new features, utility functions or extensions, please first open an issue and discuss the feature with us. *BTW, leave a 🌟 if you liked it, and this is the easiest way to support us* :)

deployment/libtorch/main.cpp

@@ -189,8 +189,10 @@ int main(int argc, char* argv[]) {
   // It should be known that it takes longer time at first time
   std::cout << ">>> Inference takes : " << duration.count() << " ms" << std::endl;
 
-  auto detections = output.toTuple()->elements()[1];
-  std::cout << ">>> OKey, detections: " << detections << std::endl;
+  auto detections = output.toTuple()->elements().at(1).toList().get(0).toGenericDict();
+  std::cout << ">>> detections labels: " << detections.at("labels") << std::endl;
+  std::cout << ">>> detections boxes: " << detections.at("boxes") << std::endl;
+  std::cout << ">>> detections scores: " << detections.at("scores") << std::endl;
 
   return 0;
 }