From 901b68aa5c8d5bf334660be11a2228aa76c520ed Mon Sep 17 00:00:00 2001 From: Mohammed Yasin <32206511+Y-T-G@users.noreply.github.com> Date: Wed, 23 Oct 2024 00:27:55 +0800 Subject: [PATCH] Add Open Images Dataset V7 pretrained model usage examples (#17090) Co-authored-by: Glenn Jocher --- docs/en/datasets/detect/open-images-v7.md | 29 +++++++++++++++++++++++ 1 file changed, 29 insertions(+) diff --git a/docs/en/datasets/detect/open-images-v7.md b/docs/en/datasets/detect/open-images-v7.md index 7083a6354c..1751a2d0a4 100644 --- a/docs/en/datasets/detect/open-images-v7.md +++ b/docs/en/datasets/detect/open-images-v7.md @@ -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