- TensorRT engine inference with ONNX model conversion
- Dockerized environment with: CUDA 10.2, TensorRT 7, OpenCV 3.4 built with CUDA
- ResNet50 preprocessing and postprocessing implementation
- Ultraface preprocessing and postprocessing implementation
- Pull container image from the repo packages
docker pull ghcr.io/mrlaki5/tensorrt-onnx-dockerized-inference:latest- Download TensorRT 7 installation from link
- Place downloaded TensorRT 7 deb file into root dir of this repo
- Build
cd ./docker
./build.shFrom the root of the repo start docker container with the command below
./docker/run.sh./ResNet50_test- Input image
- Output: Siamese cat, Siamese (confidence: 0.995392)


- Note: for this test, camera device is required. Test will start GUI showing camera stream overlaped with face detections.
./Ultraface_test