Python scripts performing object detection using the YOLOv6 model in ONNX.

Original image: https://commons.wikimedia.org/wiki/File:Motorcyclists_lane_splitting_in_Bangkok,_Thailand.jpg

• About the YOLOv6 name: https://github.com/meituan/YOLOv6/blob/main/docs/About_naming_yolov6.md
• The input images are directly resized to match the input size of the model. I skipped adding the pad to the input image, it might affect the accuracy of the model if the input image has a different aspect ratio compared to the input size of the model. Always try to get an input size with a ratio close to the input images you will use.
• The original YOLOv6 repository is still in development, so things might not work in the future.

• Check the requirements.txt file.
• For ONNX, if you have a NVIDIA GPU, then install the onnxruntime-gpu, otherwise use the onnxruntime library.
• Additionally, pafy and youtube-dl are required for youtube video inference.

git clone https://github.com/ibaiGorordo/ONNX-YOLOv6-Object-Detection.git
cd ONNX-YOLOv6-Object-Detection
pip install -r requirements.txt

For Nvidia GPU computers: pip install onnxruntime-gpu

Otherwise: pip install onnxruntime

pip install youtube_dl
pip install git+https://github.com/zizo-pro/pafy@b8976f22c19e4ab5515cacbfae0a3970370c102b

The original model was converted to ONNX using the following Colab notebook from the original repository, run the notebook and save the download model into the models folder:

• Convert YOLOv6 ONNX for Inference
• The License of the models is GPL-3.0 license: License

The original Pytorch model can be found in this repository: YOLOv6 Repository

• Image inference:

python image_object_detection.py

• Webcam inference:

python webcam_object_detection.py

• Video inference: https://youtu.be/yYo0XQp97vo

python video_object_detection.py

Original video: https://youtu.be/yXEb0fWLJIY

• Comparison with YOLOv5: https://youtu.be/yd1DhOf8mW4

python video_object_detection.py

Convert YOLOv5 model to ONNX:

• YOLOv6 model: https://github.com/meituan/YOLOv6
• YOLOv5 model: https://github.com/ultralytics/yolov5