| # YOLOv9 | |
| Implementation of paper - [YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information](https://arxiv.org/abs/2402.13616) | |
| <div align="center"> | |
| <a href="./"> | |
| <img src="https://huggingface.co/adonaivera/yolov9/resolve/main/performance.png" width="79%"/> | |
| </a> | |
| </div> | |
| ## Performance | |
| MS COCO | |
| | Model | Test Size | AP<sup>val</sup> | AP<sub>50</sub><sup>val</sup> | AP<sub>75</sub><sup>val</sup> | Param. | FLOPs | | |
| | :-- | :-: | :-: | :-: | :-: | :-: | :-: | | |
| | [**YOLOv9-S**]() | 640 | **46.8%** | **63.4%** | **50.7%** | **7.2M** | **26.7G** | | |
| | [**YOLOv9-M**]() | 640 | **51.4%** | **68.1%** | **56.1%** | **20.1M** | **76.8G** | | |
| | [**YOLOv9-C**](https://github.com/WongKinYiu/yolov9/releases/download/v0.1/yolov9-c.pt) | 640 | **53.0%** | **70.2%** | **57.8%** | **25.5M** | **102.8G** | | |
| | [**YOLOv9-E**](https://github.com/WongKinYiu/yolov9/releases/download/v0.1/yolov9-e.pt) | 640 | **55.6%** | **72.8%** | **60.6%** | **58.1M** | **192.5G** | |