https://github.com/SonwYang/YoloX-TensorRT-webcam
https://github.com/SonwYang/YoloX-TensorRT-webcam
tensorrt8x webcam windows
Last synced: over 1 year ago
JSON representation
- Host: GitHub
- URL: https://github.com/SonwYang/YoloX-TensorRT-webcam
- Owner: SonwYang
- Created: 2021-11-22T07:40:56.000Z (over 4 years ago)
- Default Branch: main
- Last Pushed: 2021-11-24T00:24:44.000Z (over 4 years ago)
- Last Synced: 2024-10-27T23:23:31.168Z (over 1 year ago)
- Topics: tensorrt8x, webcam, windows
- Language: C++
- Homepage:
- Size: 18 MB
- Stars: 9
- Watchers: 3
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# YOLOX-TensorRT(8.2.0.6) in webcam
The repo is a complement to the official repo. There are three differences:
- Windows 10
- TensorRT 8.2.0.6
- Webcam
## Step 1: Prepare serialized engine file
Follow the trt [python demo README](https://github.com/Megvii-BaseDetection/YOLOX/blob/main/demo/TensorRT/python/README.md) to convert and save the serialized engine file.
Check the 'model_trt.engine' file generated from Step 1, which will be automatically saved at the current demo dir.
## Step 2: build the demo
Please follow the [TensorRT Installation Guide](https://docs.nvidia.com/deeplearning/tensorrt/install-guide/index.html) to install TensorRT.
And you should set the TensorRT path and CUDA path in CMakeLists.txt.
If you train your custom dataset, you may need to modify the value of `num_class`.
```c++
const int num_class = 80;
```
Install opencv with ```sudo apt-get install libopencv-dev``` (we don't need a higher version of opencv like v3.3+).
build the demo:
## Step 2: build the demo
Please follow the [TensorRT Installation Guide](https://docs.nvidia.com/deeplearning/tensorrt/install-guide/index.html) to install TensorRT.
And you should set the TensorRT path, OpenCV path and CUDA path in CMakeLists.txt.
If you train your custom dataset, you may need to modify the value of `num_class`.
```c++
const int num_class = 80;
```
build the demo:
1. Building the project through cmake -gui.exe
2. Generating yolox.exe from VS
run the demo:
```shell
yolox.exe ../model_trt.engine -i
```
or
```shell
yolox.exe -i
```