Hello, I’m Muhammad Demir, a Software Engineering graduate from the University of Central Punjab with a strong focus on Computer Vision and Deep Learning. I enjoy turning real-world problems into practical ML solutions, with hands-on experience in dataset labeling, training object detectors with YOLOv8, and building robust Python pipelines using OpenCV, PyTorch, and NumPy.
I’m actively developing full-stack web capabilities with Python, Django, and React, and I’ve contributed to web projects like DrinkMate and a Receipt Parser. I volunteer my time, and I’m excited to apply my ML and software development skills in industry while continuing to learn and grow.
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Uses open source PaddleOCR as the Optical Character Recognizer. Identifies Financial or
Accounting related entries and their contextual data from receipt and extracts them.
Then applies Spacy as an NLP model on the produced text to extract meaningful field data. Uses
Regex and rule-based extraction techniques as support and fallback.
Main Script Language: Python
Stack Languages: Django and React
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