Textile_Defect_Detection

The main goal of this project is to explore self-supervised learning on texture images in order to solve textile defect detection problems and learn a robust representation of texture in lieu of traditional image processing features.

By analyzing the surface image of the textile, our solution (Using ML Model) would be able to segregate the defected products, and it would:

Reduce the dependency on manual labor which is required to do monitoring / inspection

Reduce / Eliminate defects in manufacturing process

By analyzing the surface image of the textile in the manufacturing process, our solution (Machine Learning Model) would be able to eliminate the defects, and it would be able to reduce dependency on manual labor.

Our solution will also complement the up-scaling of overall manufacturing process as there will be no people dependency.

 State benefits of our solution:

• Getting exercise. We are made to be active – and long periods of inactivity can lead to all sorts of health issues. ...
• Reduced stress levels. 
• Pride in the tangible results of your work. ..