yolov8-industrial-finetune

yolov8-industrial-finetune is a Computer vision skill for AI agents, published by KeploreAI-Lab in the MindAct repository on GitHub. Skillspace rates yolov8-industrial-finetune D (66/100) and it passed the safety scan; the rating is based on static analysis only.

Use this skill for defect detection and instance segmentation on industrial products — magnets, metal parts, PCBs, ceramics, plastics, or any manufactured component with surface defects. The default base model is YOLOv8n-seg. When input images are single-channel (grayscale) TIF files — common with industrial cameras and microscopes — this skill applies the correct first-layer weight adaptation: average the 3-channel pretrained weights across the channel dimension and use that to initialize a 1-channel input model, then fine-tune. This is better than training from scratch or naively converting the image to RGB. Trigger this skill when the user mentions: "defect detection", "surface inspection", "magnet", "metal part", "PCB inspection", "TIF images", "single channel", "grayscale industrial", "fine-tune YOLOv8", "1-channel input", "instance segmentation defects", "train on my dataset". Always prefer this over generic training advice for industrial inspection tasks.

Grade

D

Quality

66 / 100

Safety

Passed

GitHub stars

85

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