54 lines
2.1 KiB
Markdown
Executable File
54 lines
2.1 KiB
Markdown
Executable File
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## What `trt_vehicle` can do:
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1. Vehicle detector
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2. Vehicle plate detector and recognizer
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3. Vehicle scanner based on side view of body
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4. Vehicle color and type classifier
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5. Vehicle feature encoder used for search(1:N) or comparison(1:1)
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## How to install tensorrt and cuda ?
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Refer to NVIDIA official web
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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`
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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
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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'
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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`
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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`
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6. run `source ~/.bashrc`
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>> CUDA 11.1 + TensorRT 7.2.1 for this repository (tested)
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>>
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>> CUDA 11.1 + TensorRT 8.5 for this repository (tested)
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## How to generate trt model from onnx ?
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```shell
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trtexec --onnx=./vehicle.onnx --saveEngine=vehicleXXX.trt --buildOnly=true
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```
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## How to build trt_vehicle ?
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we can build trt_vehicle separately.
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0. set the right library path and include path for TensorRT in `CMakeLists.txt`
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1. `mkdir build && cd build`
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2. `cmake ..`
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3. `make -j8`
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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.
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## Sample screenshot ##
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### vehicle detect
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### vehicle plate detect
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### vehicle scan
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### vehicle color and type classify
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### vehicle compare
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### vehicle search
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### vehicle cluster
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