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Add Open Images Dataset V7 pretrained model usage examples (#17090)

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Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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Mohammed Yasin 2024-10-23 00:27:55 +08:00 • committed by GitHub
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docs/en/datasets/detect/open-images-v7.md
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@ -29,6 +29,35 @@ keywords: Open Images V7, Google dataset, computer vision, YOLO11 models, object
| [YOLOv8l](https://github.com/ultralytics/assets/releases/download/v8.2.0/yolov8l-oiv7.pt) | 640 | 34.9 | 596.9 | 2.43 | 44.1 | 167.4 |
| [YOLOv8x](https://github.com/ultralytics/assets/releases/download/v8.2.0/yolov8x-oiv7.pt) | 640 | 36.3 | 860.6 | 3.56 | 68.7 | 260.6 |
You can use these pretrained for inference or fine-tuning as follows.
!!! example "Pretrained Model Usage Example"
=== "Python"
```python
from ultralytics import YOLO
# Load an Open Images Dataset V7 pretrained YOLOv8n model
model = YOLO("yolov8n-oiv7.pt")
# Run prediction
results = model.predict(source="image.jpg")
# Start training from the pretrained checkpoint
results = model.train(data="coco8.yaml", epochs=100, imgsz=640)
```
=== "CLI"
```bash
# Predict using an Open Images Dataset V7 pretrained model
yolo detect predict source=image.jpg model=yolov8n-oiv7.pt
# Start training from an Open Images Dataset V7 pretrained checkpoint
yolo detect train data=coco8.yaml model=yolov8n-oiv7.pt epochs=100 imgsz=640
```
![Open Images V7 classes visual](https://github.com/ultralytics/docs/releases/download/0/open-images-v7-classes-visual.avif)
## Key Features