YOLO Model Zoo
Welcome to the YOLOv9 Model Zoo! Here, you will find a variety of pre-trained models tailored to different use cases and performance needs. Each model comes with detailed information about its training regime, performance metrics, and usage instructions.
Standard Models
These models are trained on common datasets like COCO and provide a balance between speed and accuracy.
| Model | Test Size | APval | AP50val | AP75val | Param. | FLOPs |
|---|---|---|---|---|---|---|
| YOLOv9-T | 640 | 38.3% | 53.1% | 41.3% | 2.0M | 7.7G |
| YOLOv9-S | 640 | 46.8% | 63.4% | 50.7% | 7.1M | 26.4G |
| YOLOv9-M | 640 | 51.4% | 68.1% | 56.1% | 20.0M | 76.3G |
| YOLOv9-C | 640 | 53.0% | 70.2% | 57.8% | 25.3M | 102.1G |
| YOLOv9-E | 640 | 55.6% | 72.8% | 60.6% | 57.3M | 189.0G |
| YOLOv7 | 640 | 51.4% | 69.7% | 55.9% | ||
| YOLOv7-X | 640 | 53.1% | 71.2% | 57.8% | ||
| YOLOv7-W6 | 1280 | 54.9% | 72.6% | 60.1% | ||
| YOLOv7-E6 | 1280 | 56.0% | 73.5% | 61.2% | ||
| YOLOv7-D6 | 1280 | 56.6% | 74.0% | 61.8% | ||
| YOLOv7-E6E | 1280 | 56.8% | 74.4% | 62.1% |
Download and Usage Instructions
To use these models, download them from the links provided and use the following command to run detection:
$yolo detect weights=path/to/model.pt img=640 conf=0.25 source=your_image.jpg