In 2019 I did my academic internship on machine learning

What it does

I extracts information from students-id(s) within images.

How I built it

I built the project using object detection, instance segmentation, image classification and image alignment.

Challenges I ran into

I had two main difficulties while developing the project and writing this tutorial: My personal computer has no GPU, so I had to rely on Google Colaboratory to train my models. Also, due to the issue of everything licenced under the MIT licence, I had to create my own datasets for the project.

Accomplishments that I'm proud of

I'm really proud to have developed and implemented a methodology for information extraction from scratch using my best machine learning library, Pytorch. Mostly because Information Extraction is real has been a real challenge in the discipline of computer vision for so many years now.

What I learned

I've mostly learned how to optimize my Pytorch code. I also learned a few tricks for developing Information Extraction Systems.

What's next for Pytorch-Information-Extraction

What comes next for this tutorial is surely the following: Make the detection module more robust to truncated documents. Develop and train a custom OCR engine using Pytorch.

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