- Recognition and tracking of 2-digits target for automatic aeroplane for the Chinese Aeromodelling Design Competition (CADC)
- Detection model trained using Darknet-YOLO
- 2 digits recognition, automatic parameter searching using NNI , model built using Pytorch, trained on SVHN (The Street View House Numbers)
- Acceleration : TensorRT (tkDNN) (FP16), C++, multi-threading
- Real-time (20-25FPS) on TX2 (edge computing platform), ~ 200FPS on RTX 2070
- Build darknet by allowing OpenCV, GPU and cuDNN
- Add the following code to public method of class
DetectionNNintkDNN-master/include/tkDNN/DetectionNN.hand build tkDNN
void setthreshold(float threshold) confThreshold=threshold;- Instead of using the libtorch downloaded, rebuild Torch by setting to allow
CXX11_ABIinTorchConfig.cmake
if ("${CMAKE_CXX_COMPILER_ID}" STREQUAL "GNU")
set(TORCH_CXX_FLAGS "-D_GLIBCXX_USE_CXX11_ABI=1")
endif()