A real-time finger counting system using YOLO-based object detection. The project detects hand gestures and counts fingers from live video or images.

YoloV8 Nesne Tespiti İle Parmak Sayma

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Sibayan et al. Thesis: Milkfish Fingerlings Counter Using the Instance Segmentation of YOLOv7 and Custom Dataset of Milkfish Fingerlings within Agoo La Union. Version 7 Notebook: This version will be trained using the version 2 of the milkfish fingerlings v2 custom dataset for higher accuracy.

This project uses computer vision and machine learning to detect the number of fingers shown by a hand in real-time and plays a unique sound for each detected finger count. It combines the power of OpenCV, YOLO, and audio libraries to create an interactive and fun experience for gesture-based sound control.

This project is an innovative solution for real-time finger counting, leveraging the strengths of YOLO (You Only Look Once) and MediaPipe to provide accurate and efficient results directly from a webcam feed. It offers a seamless integration of these advanced technologies to create a user-friendly and robust tool for various applications.