GitHub / arssite / Dirty-CleanFlooringImageProcessingUsingYolov5
Uses YOLOv5 to classify floor cleanliness into five categories based on visual cues. It includes an annotated dataset, trained model,& evaluation outputs. Code covers data preprocessing, training, & testing. A comparative analysis highlights YOLOv5's advantages over traditional methods, providing an efficient solution automated floor cleanliness.
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PURL: pkg:github/arssite/Dirty-CleanFlooringImageProcessingUsingYolov5
Stars: 0
Forks: 0
Open issues: 0
License: cc0-1.0
Language: Jupyter Notebook
Size: 30.4 MB
Dependencies parsed at: Pending
Created at: 7 months ago
Updated at: 7 months ago
Pushed at: 7 months ago
Last synced at: 3 months ago
Topics: deep-neural-networks, github, google-colab, jupyter-notebook, labelimg, matplotlib-pyplot, numpy-library, opencv-python, pandas-python, pytorch, scikit-learn, tensorflow, yolov5