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Hi there 👋

I'm Mikel, creator of BoxMOT, an engineer with a focus on applied and R&D in machine learning. On GitHub, I'm recognized for integrating SOTA real-time object detection, segmentation, and pose estimation models with SOTA tracking modules. In my free time, I enjoy reading about depth psychology and lifting heavy weights. I am an open source advocate.

📫 How to reach me: [email protected]

Mike's Projects

albumentations icon albumentations

Fast image augmentation library and an easy-to-use wrapper around other libraries. Documentation: https://albumentations.ai/docs/ Paper about the library: https://www.mdpi.com/2078-2489/11/2/125

boxmot icon boxmot

BoxMOT: pluggable SOTA tracking modules for segmentation, object detection and pose estimation models

da-rnn icon da-rnn

📃 PyTorch Implementation of DA-RNN (arXiv:1704.02971)

lstm_tutorial icon lstm_tutorial

Tutorials for signal prediction with LSTM networks in keras

map_maker icon map_maker

Map maker achitecture for a Robosoft Kompai robot placed in the simulated factory environment of MRDS

mmtracking icon mmtracking

OpenMMLab Video Perception Toolbox. It supports Single Object Tracking (SOT), Multiple Object Tracking (MOT), Video Object Detection (VID) with a unified framework.

onnx2tf icon onnx2tf

Self-Created Tools to convert ONNX files (NCHW) to TensorFlow/TFLite/Keras format (NHWC). The purpose of this tool is to solve the massive Transpose extrapolation problem in onnx-tensorflow (onnx-tf). I don't need a Star, but give me a pull request.

py-motmetrics icon py-motmetrics

:bar_chart: Benchmark multiple object trackers (MOT) in Python

trackeval icon trackeval

HOTA (and other) evaluation metrics for Multi-Object Tracking (MOT).

ultralytics icon ultralytics

NEW - YOLOv8 🚀 in PyTorch > ONNX > CoreML > TFLite

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