Add https://youtu.be/LGGxqLZtvuw to docs & bbox dimension retrieval utilities. (#9679)
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
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3 changed files with 65 additions and 11 deletions
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@ -8,6 +8,18 @@ keywords: Ultralytics, YOLOv8, Object Detection, Pose Estimation, PushUps, PullU
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Monitoring workouts through pose estimation with [Ultralytics YOLOv8](https://github.com/ultralytics/ultralytics/) enhances exercise assessment by accurately tracking key body landmarks and joints in real-time. This technology provides instant feedback on exercise form, tracks workout routines, and measures performance metrics, optimizing training sessions for users and trainers alike.
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<p align="center">
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<br>
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<iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/LGGxqLZtvuw"
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title="YouTube video player" frameborder="0"
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allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share"
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allowfullscreen>
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</iframe>
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<br>
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<strong>Watch:</strong> Workouts Monitoring using Ultralytics YOLOv8 | Pushups, Pullups, Ab Workouts
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</p>
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## Advantages of Workouts Monitoring?
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- **Optimized Performance:** Tailoring workouts based on monitoring data for better results.
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@ -59,6 +59,28 @@ convert_coco(#(1)!
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For additional information about the `convert_coco` function, [visit the reference page](../reference/data/converter.md#ultralytics.data.converter.convert_coco)
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### Get Bounding Box Dimensions
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```{.py .annotate }
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from ultralytics.utils.plotting import Annotator
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from ultralytics import YOLO
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import cv2
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model = YOLO('yolov8n.pt') # Load pretrain or fine-tune model
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# Process the image
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source = cv2.imread('path/to/image.jpg')
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results = model(source)
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# Extract results
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annotator = Annotator(source, example=model.names)
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for box in results[0].boxes.xyxy.cpu():
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width, height, area = annotator.get_bbox_dimension(box)
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print("Bounding Box Width {}, Height {}, Area {}".format(
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width.item(), height.item(), area.item()))
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```
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### Convert Bounding Boxes to Segments
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With existing `x y w h` bounding box data, convert to segments using the `yolo_bbox2segment` function. The files for images and annotations need to be organized like this:
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