https://github.com/nguyenquangtung/compare-yolov9-and-yolov8

https://github.com/nguyenquangtung/compare-yolov9-and-yolov8

Last synced: 11 days ago
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• Host: GitHub
• URL: https://github.com/nguyenquangtung/compare-yolov9-and-yolov8
• Owner: nguyenquangtung
• Created: 2024-02-25T14:24:58.000Z (9 months ago)
• Default Branch: main
• Last Pushed: 2024-02-25T14:40:07.000Z (9 months ago)
• Last Synced: 2024-02-25T15:37:48.778Z (9 months ago)
• Language: Jupyter Notebook
• Size: 2.86 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Compare-YOLOv9-and-YOLOv8

https://github.com/WongKinYiu/yolov9 

![image](https://github.com/nguyenquangtung/Compare-YOLOv9-and-YOLOv8/assets/59195029/ec1654f7-399b-45b3-8a3b-a784accb3337)

The "YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information" paper, introducing the novel computer vision model architecture YOLOv9, was published by Chien-Yao Wang, I-Hau Yeh, and Hong-Yuan Mark Liao on February 21st, 2024. Following its release, the source code became accessible, enabling users to train their own YOLOv9 models. As per the research team, YOLOv9 demonstrates superior performance in mean Average Precision (mAP) compared to established YOLO models like YOLOv8, YOLOv7, and YOLOv5, as assessed against the MS COCO dataset.

This is a repository that compares both YOLOv8 and YOLOv9 models on a set of custom data to quickly look at the improvement of YOLOv9 with YOLOv8.

![image](https://github.com/nguyenquangtung/Compare-YOLOv9-and-YOLOv8/assets/59195029/ef832e7e-cd5e-483b-88be-11f96a8b51ad)

references: 

- https://blog.roboflow.com/train-yolov9-model/

- https://github.com/WongKinYiu/yolov9

- https://github.com/ultralytics/ultralytics