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Cv Solar Panel Defect Detection
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Cv Solar Panel Defect Detection

Developed by Bazaar
This is an image classification model built with PyTorch and HuggingPics, specifically designed for detecting defects in solar panels.
Image Classification
Transformers
#Solar Panel Quality Inspection#Defect Grading Detection#Industrial Vision Inspection
Downloads 26
Release Time : 9/5/2023

Model Overview

The model can classify solar panel images into four states: no defect, minor defect, moderate defect, and severe defect, achieving an accuracy of 80.9%.

Model Features

High Accuracy
Achieves 80.9% accuracy in defect detection tasks.
Multi-Level Classification
Can distinguish between no defect, minor defect, moderate defect, and severe defect states.
Ease of Use
Built with the HuggingPics framework for easy deployment and usage.

Model Capabilities

Image Classification
Defect Detection
Solar Panel Quality Assessment

Use Cases

Solar Industry
Production Line Quality Inspection
Automatically detects product defects on solar panel production lines.
Improves inspection efficiency and reduces labor costs.
Maintenance Inspection
Conducts regular inspections of installed solar panels.
Identifies potential issues early and extends service life.
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