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Traffic Sign Recognition

Codebase For Team CSPDarknet53's Interpretation Of The AI In Geoservices Challenge From The Artificial Intelligence International Junior Contest


Contents

  • Code

  • Website Demo

  • Details


Code

Model Pipeline & Training:

  • EfficientNetB2.ipynb : Notebook To Bring Together The Pipeline

  • Pipeline :

    • constants.py : Some Constant Values
    • dataset.py : Data Preprocessing / Loading
    • generate_submission.py : Generates Submissions For The Contest
    • models.py : Model Dictionary & Class
    • train.py : Model Training Module
    • utils.py : Helper Functions

Website :

  • inference.py : Helper Function For Flask App

  • main.py : Flask App Backend

  • App :

    • Test Images (From WikiPedia)
    • Class2Label Dictionary
    • English Conversion For Classes
    • Russian Conversion For Classes

  • Frontend Code :

    • index.html : FrontEnd For Website HomePage
    • result.html : FrontEnd For Predictions

  • Styling :

    • Images For Website
    • Styles For Website

Website Demo

AIIJC.Website.Demo.mp4

Details

Model

Pre-Trained Model : EfficientNetB0 With Custom Head

Image Size: (224, 224)

Image Preprocessing: pseudo-labelling, albumentations

Training Time: 14 hours

Training Accuracy: 99.86%

Validation Accuracy: 99.72%

Testing Accuracy: 99.2%