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marcadrianpeters/README.md

Hi there, Iโ€™m Marc ๐Ÿ‘‹

Software Developer with a focus on Computer Vision.

MABRI.VISION GmbH | Aachen, Germany


๐Ÿ“– About Me

Iโ€™m passionate about applying computer vision and deep learning to solve real-world industrial challenges.
I hold a B.Sc. in Electrical Engineering, Information Technology and Computer Engineering from RWTH Aachen University. My expertise includes image processing pipelines, anomaly detection, and 3D vision using HALCON, OpenCV, Python, and C++.


๐Ÿ’ผ Experience

  • MABRI.VISION GmbH (Software & Application Engineer, Full-Time)

  • MABRI.VISION GmbH (Working Student)
    Developed and integrated a 2.5D point-cloud pipeline; prototyped CV routines that secured new projects; engineered anomaly detection, calibration, segmentation, and 3D routines in HALCON.

  • RWTH Aachen University (Student Assistant)
    Migrated a C++/Qt codebase to Linux; built a Qt-based GUI for cluster task automation.

  • Tutoring
    Guided students in basic programming, C, and C++.


๐ŸŽ“ Education

  • Bachelor of Science โ€“ Electrical Engineering, Information Technology and Computer Engineering
    RWTH Aachen University (Octโ€ฏ2020 โ€“ Octโ€ฏ2025)

  • Bachelor of Science โ€“ Mathematics (discontinued)
    RWTH Aachen University (Octโ€ฏ2018 โ€“ Octโ€ฏ2020)


๐Ÿ“š Bachelor Thesis

Machine Learning Approaches for Wound Segmentation
Developed a deep learning pipeline to segment wounds and skin from background; additionally investigated unsupervised ML methods for tissue segmentation in chronic wounds. Final grade: 1.0


๐Ÿ“ Projects

  • superpixel_labeling_tool
    Developed this tool to accelerate data labeling for my thesis using superpixel segmentation, dramatically increasing annotation speed and consistency.

๐Ÿ› ๏ธ Tech & Tools

  • Languages: Python, C++
  • Computer Vision & Deep Learning: HALCON, OpenCV, PyTorch
  • Dev & Infrastructure: Git, Linux, Qt

๐Ÿ“ซ Letโ€™s Connect


Popular repositories Loading

  1. superpixel_labeling_tool superpixel_labeling_tool Public

    This project provides an interactive GUI tool to accelerate image annotation by leveraging superpixel segmentation. It uses SLIC-based superpixels to divide images into coherent regions, enabling uโ€ฆ

    Python

  2. marcadrianpeters marcadrianpeters Public

  3. segmentation_models.pytorch segmentation_models.pytorch Public

    Forked from qubvel-org/segmentation_models.pytorch

    Semantic segmentation models with 500+ pretrained convolutional and transformer-based backbones.

    Python