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https://github.com/ibaiGorordo/ONNX-YOLOv6-Object-Detection

Python scripts performing object detection using the YOLOv6 model in ONNX.
https://github.com/ibaiGorordo/ONNX-YOLOv6-Object-Detection

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

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# ONNX YOLOv6 Object Detection

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



![! ONNX YOLOv6 Object Detection](https://github.com/ibaiGorordo/ONNX-YOLOv6-Object-Detection/blob/main/doc/img/detected_objects.jpg)

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



# Important

- 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.



# Requirements



 * Check the **requirements.txt** file. 

 * For ONNX, if you have a NVIDIA GPU, then install the **onnxruntime-gpu**, otherwise use the **onnxruntime** library.

 

# Installation

```

git clone https://github.com/ibaiGorordo/ONNX-YOLOv6-Object-Detection.git

cd ONNX-YOLOv6-Object-Detection

pip install -r requirements.txt

```

### ONNX Runtime

For Nvidia GPU computers:

`pip install onnxruntime-gpu`



Otherwise:

`pip install onnxruntime`



# ONNX model 

~~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](https://github.com/ibaiGorordo/ONNX-YOLOv6-Object-Detection/tree/main/models):~~

- ~~**Convert YOLOv6 ONNX for Inference** [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1pke1ffMeI2dXkIAbzp6IHWdQ0u8S6I0n?usp=sharing)~~



You can find the ONNX models in the Assets section of the official repository Releases (e.g. [Release 2.1](https://github.com/meituan/YOLOv6/releases/tag/0.2.1)). Download the ONNX file and save the download model into the [models  folder](https://github.com/ibaiGorordo/ONNX-YOLOv6-Object-Detection/tree/main/models):

- Additionally, if you want to convert the model to ONNX yourself, you can follow the instructions in: https://github.com/meituan/YOLOv6/tree/main/deploy/ONNX

- The License of the models is GPL-3.0 license: [License](https://github.com/meituan/YOLOv6/blob/main/LICENSE)



# Pytorch model

The original Pytorch model can be found in this repository: [YOLOv6 Repository](https://github.com/meituan/YOLOv6)

 

# Examples



 * **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

 ```

 ![!YOLOv6 detection video](https://github.com/ibaiGorordo/ONNX-YOLOv6-Object-Detection/blob/main/doc/img/yolov6s_video.gif)

 

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



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

 ```

 python comparison_with_yolov5.py

 ```

Convert YOLOv5 model to ONNX: [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1V-F3erKkPun-vNn28BoOc6ENKmfo8kDh?usp=sharing)



# References:

* YOLOv6 model: https://github.com/meituan/YOLOv6

* YOLOv5 model: https://github.com/ultralytics/yolov5