https://github.com/rathod-shubham/yolo-nas-2

About YOLO_NAS is an architecture for object detection that automatically searches for optimal neural network structures, while Segment Anything Model is a versatile model for segmenting various objects in images.
https://github.com/rathod-shubham/yolo-nas-2

computer-vision deep-learning machine-learning neural-architecture-search python3 sam segment-anything-model segmentation webapp yolo-nas

Last synced: 7 months ago
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About YOLO_NAS is an architecture for object detection that automatically searches for optimal neural network structures, while Segment Anything Model is a versatile model for segmenting various objects in images.

• Host: GitHub
• URL: https://github.com/rathod-shubham/yolo-nas-2
• Owner: RATHOD-SHUBHAM
• Created: 2023-09-18T22:40:19.000Z (about 2 years ago)
• Default Branch: master
• Last Pushed: 2023-09-19T00:35:12.000Z (about 2 years ago)
• Last Synced: 2025-01-22T07:37:20.160Z (9 months ago)
• Topics: computer-vision, deep-learning, machine-learning, neural-architecture-search, python3, sam, segment-anything-model, segmentation, webapp, yolo-nas
• Language: Python
• Homepage:
• Size: 47.8 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# Yolo-NAS-2

# 1. Car Damage Detection:

1] YoloNAS is trained to detect Car Damage.\

2] The Output from YoloNAS is passed on to SAM to create a mask over the detected damage.



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# 2. Car Parts Segmentation

1] YoloNAS is trained to detect Car Parts.\

2] The Output from YoloNAS is passed on to SAM to create a mask over the detected part.