Optical Character Recognition (OCR)

Michiel Jacobs
Master of Chemistry: Chemical Theory, (Bio)Molecular Design and Synthesis
Faculty of Sciences and Bio-Engineering Sciences

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How to do inference

1. Setup the conda environment with: conda env create -f environment.yml
2. Activate the environment: conda activate dl-proj
3. Run inference.py. By default, it will make predictions on the handwriting of me and some of my collegues.
4. To use your own image, change the IMAGEPATH variable to were you have stored the image. The only requirement is that the image should be a square. (Let's say as captured by some object detection.)

Project overview

• The experimental folder contains some preliminary code for exploration of the dataset and a basic model.
• The production folder contains the code to train the model, training was done on Hydra for speed.
• The inference folder contains the code to make predictions from.

Sources

The code for calculating the accuracy was inspired on the official tutorial.
LeNet-5 from the paper: LeCun, Y.; Bottou, L.; Bengio, Y.; Haffner, P. Gradient-Based Learning Applied to Document Recognition. Proc. IEEE 1998, 86 (11), 2278–2323. https://doi.org/10.1109/5.726791.