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A vision use-case | German license plates classifier 🚘

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Technical test @ ParkDepot

A deep learning classifier on German license plates 🚘 🇩🇪

Task

  • Detect if a plate has 1, 2 or 3 letters for the city description :
  • Implement a deep learning classifier

Dataset

  • Real plates
  • Synthetic plates, taht have been generated to construct a bigger dataset
  • Input, example of such a plate:

Used method

  • A strong preprocessing pipeline to split data into usable training/validation sets and to transform data dimension
  • A manually implemented ResNet model, following the original paper
    • Redefinition of the residual blocks and stacks in PyTorch
  • Use of a classic SGD optimizer (lr=1e-2, momentum=0.9, weight_decay=1e-2)
  • Use of Google GPU capacity, hence the Google Colab notebook.

Results

  • High final accuracy (0.999%) on test data

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A vision use-case | German license plates classifier 🚘

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