Name: Muhammad Rizwan Munawar
Type: User
Company: @ultralytics
Bio: Passionate Computer Vision Engineer | Solving Real-World Challenges🔎| Python | Published Research | Open Source Contributor🌟| AI Developer 💪
Twitter: muhammdrizwanmr
Location: Wah Cantt, Islamabad Pakistan
Blog: https://muhammadrizwanmunawar.medium.com/
Muhammad Rizwan Munawar's Projects
Ultralytics assets
Cats vs dogs classification using deep learning. Data augmentation and convolutional neural networks.
Covid-19 chest x_rays images multi-class classification while classes are (COVID, Pneumonia, normal)
Data Analysis and model building on CSV datasets.
Frames extraction from multiple videos
Extraction of frames from single video using OpenCV
Face detection and recognition using OpenCV.
Fast Segment Anything
Houses Price Prediction using Linear Regression
Houses price prediction web app
SDK for Ultralytics HUB
the official pytorch implementation of “Mamba-YOLO:SSMs-based for Object Detection”
My Repositories stars, commits, pull requests, Information
Skin Cancer binary(Benign vs malignant) Classification using convolutional neural networks
Spark foundation Internship Tasks of domain (Computer Vision & IoT Field).
NEW - YOLOv8 🚀 in PyTorch > ONNX > OpenVINO > CoreML > TFLite
FPS Comparision with same specification of YOLOX, YOLOR, YOLOv5 and YOLOv7
YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
YOLOv5 Object Tracking + Detection + Object Blurring + Streamlit Dashboard Using OpenCV, PyTorch and Streamlit
YOLOv7 Object Blurring Using PyTorch and OpenCV
YOLOv7 Object Cropping Using OpenCV
YOLOv7 Object Tracking Using PyTorch, OpenCV and Sort Tracking
YOLOv7 Pose estimation using OpenCV, PyTorch
YOLOv7 Instance Segmentation using OpenCV and PyTorch
Use YOLOv8 in real-time, for object detection, instance segmentation, pose estimation and image classification, via ONNX Runtime.
YOLOv8 Object Tracking Using PyTorch, OpenCV and Ultralytics