[ICLR 2026] VisionReasoner: Unified Reasoning-Integrated Visual Perception via Reinforcement Learning
An algorithm that uses YoloV5 and DeepSORT to count and measure the number of vehicles in a video stream, it detects the vehicles with YoloV5 and tracks them with DeepSORT to maintain a count of unique vehicles in the video. It also calculates the frames per second (FPS) of the video stream.
CVPR2023 Zero-shot Counting
[AAAI 2025] Official code for "OmniCount: Multi-label Object Counting with Semantic-Geometric Priors"
Counting number of Objects using Python-OpenCV
A computer vision deep learning model to automatically count the number of rebars.
This is my first repository and it is based on object detection and object tracking of vehicles. It will first detect and count the vehicles.
Counting Sheep without Sleep. This project utilizing YOLO and several image processing techniques to accurately track, count and segment sheep.
Image Processing Mini Projects | Python, OpenCV, NumPy, Matplotlib
annotation environment for object counting
In this repo I am sharing a simple code for detecting and counting cars.
Image processing using various algorithms on openCV
Vehicle counting system that tracks and analyzes vehicle data, including license plate numbers, vehicle types and counts.
This work is an extension of the project https://github.com/ablanco1950/LicensePlate_Yolov8_Filters_PaddleOCR adding the possibility to detect the speed, tracking and counting cars. Has been updated to feature and leverage improvements brought by Roboflow and Ultralytics.
Counting of Human Faces in a Frame
Evaluating adipocyte differentiation of bone marrow-derived mesenchymal stem cells by a deep learning method for automatic lipid droplet counting
Prototype of an object counting system for warehouse stock counting, using retrained YOLOv5 Small + custom Malaysian coins dataset.
annotation environment for object counting
A real-time vehicle detection and tracking system built using YOLOv4 and OpenCV, designed to identify, track, and count vehicles from video streams. The system demonstrates computer vision techniques for intelligent traffic monitoring and smart transportation applications.
Project I did during 5th semester for course Introduction to image processing (Wprowadzenie do przetwarzania obrazów). Final MARPE was 0.5625%.
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