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Course project for 198:534 at Rutgers University. This project is aimed at reproducing the results of the paper titled "Open Set Logo Detection and Retrieval" and extending on the same.

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kunjmehta/logo-detection-and-classification

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Logo Detection and Classification

Code for the CS 534: Computer Vision project at Rutgers University. Reproduced and extended on the results presented in the paper Open Set Logo Detection and Retrieval


Work Done

  • Reproduced and improved the mean average precision (mAP) of open set logo detection from the original paper by 24 percentage points using YOLOv5 detector
  • Obtained a classification accuracy of 22.56% for 47 classes of the Flickr-47 dataset using a logo classification architecture consisting of YOLOv5 and template matching focused on both abstract and textual logos

Tech Stack

  • Python 3
  • PyTorch
  • seaborn

Report and Presentation

You can access the report here and presentation here.

Structure and Acknowledgements

  • utils: Contains code for file handling and bounding box annotation
  • logo_classification.py: Contains code for the classification of logos in the Flickr-47 dataset
  • YOLOv5_Custom_Training.ipynb: Contains application of YOLOv5 to the open set dataset and reports the improvement in mAP.

Made as a team with @animesharma

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Course project for 198:534 at Rutgers University. This project is aimed at reproducing the results of the paper titled "Open Set Logo Detection and Retrieval" and extending on the same.

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