README.md

What trt_vehicle can do:

1. Vehicle detector
2. Vehicle plate detector and recognizer
3. Vehicle scanner based on side view of body
4. Vehicle color and type classifier
5. Vehicle feature encoder used for search(1:N) or comparison(1:1)

How to install tensorrt and cuda ?

Refer to NVIDIA official web

1. download files according to your GPUs (below for this repo) cuda_11.1.0_455.23.05_linux.run, cudnn-11.1-linux-x64-v8.0.5.39.tgz, TensorRT-7.2.1.6.Ubuntu-18.04.x86_64-gnu.cuda-11.1.cudnn8.0.tar.gz
2. run ./cuda_11.1.0_455.23.05_linux.run install cuda(at /usr/local) and driver, maybe need to reboot machine some times
3. upzip cudnn-11.1-linux-x64-v8.0.5.39.tgz , copy all header files to '/usr/local/cuda/include' and copy all lib files to '/usr/local/cuda/lib64'
4. unzip TensorRT-7.2.1.6.Ubuntu-18.04.x86_64-gnu.cuda-11.1.cudnn8.0.tar.gz at /usr/local, create softlink by ln -s /usr/local/TensorRT-7.2.1.6 /usr/local/tensorRT
5. add export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/tensorRT/lib:/usr/local/cuda/lib64:/usr/local/lib, export CPATH=$CPATH:/usr/local/cuda/include:/usr/local/tensorRT/include to ~/.bashrc
6. run source ~/.bashrc

CUDA 11.1 + TensorRT 7.2.1 for this repository (tested)

CUDA 11.1 + TensorRT 8.5 for this repository (tested)

How to generate trt model from onnx ?

trtexec --onnx=./vehicle.onnx --saveEngine=vehicleXXX.trt --buildOnly=true

How to build trt_vehicle ?

we can build trt_vehicle separately.

0. set the right library path and include path for TensorRT in CMakeLists.txt
1. mkdir build && cd build
2. cmake ..
3. make -j8

all lib files saved to build/libs, all samples saved to build/samples. please refer to videopipe about how to run samples for trt_vehicle.

Sample screenshot

vehicle detect

vehicle plate detect

vehicle scan

vehicle color and type classify

vehicle compare

vehicle search

vehicle cluster