https://github.com/rathod-shubham/yolov8_od
Ultralytics YOLOv8 is a cutting-edge, state-of-the-art (SOTA) model. YOLOv8 is designed to be fast, accurate, and easy to use, making it an excellent choice for a wide range of object detection and tracking, instance segmentation, image classification and pose estimation tasks.
https://github.com/rathod-shubham/yolov8_od
computer-vision deep-learning machine-learning model-development neural-network python3 yolo yolov8
Last synced: 7 months ago
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Ultralytics YOLOv8 is a cutting-edge, state-of-the-art (SOTA) model. YOLOv8 is designed to be fast, accurate, and easy to use, making it an excellent choice for a wide range of object detection and tracking, instance segmentation, image classification and pose estimation tasks.
- Host: GitHub
- URL: https://github.com/rathod-shubham/yolov8_od
- Owner: RATHOD-SHUBHAM
- Created: 2023-09-18T13:55:21.000Z (about 2 years ago)
- Default Branch: master
- Last Pushed: 2024-12-29T15:02:45.000Z (9 months ago)
- Last Synced: 2025-01-22T07:37:22.722Z (9 months ago)
- Topics: computer-vision, deep-learning, machine-learning, model-development, neural-network, python3, yolo, yolov8
- Language: Jupyter Notebook
- Homepage:
- Size: 13.2 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Yolov8
Anchor Free Detection
YOLOv8 is an anchor-free model. This means it predicts directly the center of an object instead of the offset from a known anchor box.
Visualization of an anchor box in YOLO
Anchor boxes were a notoriously tricky part of earlier YOLO models, since they may represent the distribution of the target benchmark's boxes but not the distribution of the custom dataset.