GitHub / ajosegun / PCBQualityControl
PCBQualityControl uses the latest segmentation models to solve this problem of void detection. This solution trained Yolov8 on the target to automatically select (bounding box). SAM then uses the output of YOLO to segment the image, exposing the void and component areas. A quality control report is generated based on the voids to components ratio.
JSON API: http://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ajosegun%2FPCBQualityControl
PURL: pkg:github/ajosegun/PCBQualityControl
Stars: 4
Forks: 0
Open issues: 1
License: None
Language: Jupyter Notebook
Size: 66.2 MB
Dependencies parsed at: Pending
Created at: about 2 years ago
Updated at: over 1 year ago
Pushed at: about 2 years ago
Last synced at: over 1 year ago
Commit Stats
Commits: 25
Authors: 3
Mean commits per author: 8.33
Development Distribution Score: 0.16
More commit stats: https://commits.ecosyste.ms/hosts/GitHub/repositories/ajosegun/PCBQualityControl
Topics: quality, quality-control, segment-anything, segmentation-based-detection, yolov8n