🦉Gracefully face reCAPTCHA challenge with ultralytics YOLOv8-seg, CLIPs VIT-B/16 and CLIP-Seg/RD64. Implemented in playwright or an easy-to-use API.

WIDER-FACE Face Detector Based On YOLOV8

This project implements a face emotion detection system using YOLOv11, trained on a custom dataset to classify emotions into five distinct classes. The model utilizes the Ultralytics YOLO framework for real-time inference.

[ultralytics v8.3.75][yolov8/yolo11-pose][WIDER FACE]Upgrade YOLO5Face to YOLO8Face and YOLO11Face

Computer vision model to detect face mask using webcam as a source. Created with the help of Ultralytics YOLO v8

Repository of Computer Vision projects based on CNNs, Vision Transformers, and YOLO11, implemented with TensorFlow, PyTorch, Hugging Face, and Ultralytics.

Real-time multi-face emotion detection using YOLOv8 and OpenCV. Detects facial expressions like happy, sad, angry, and more with color-coded bounding boxes and live webcam support. Built with Python, Ultralytics YOLO, and face_recognition.

[FD] Face Detection with DL models : DLib, Haar-Cascade(OpenCV), Mediapipe(Google), MTCNN, RetinaFace(Insightface), SCRFD (Insightface), SSD, YOLOv5 (Ultralytics), YuNet, etc.

AI-powered tool that generates visually compelling thumbnails from videos using motion analysis, YOLOv8 object detection, face cropping, and text overlays. Includes scripts for original frame extraction and side-by-side comparisons. Built with OpenCV, PIL, and Ultralytics in a WSL environment.

This repository provides a step-by-step guide and scripts to install and run Ultralytics YOLO (YOLOv8) on Raspberry Pi (tested on Raspberry Pi 3B+/4). It's optimized for lightweight inference. Whether you're using the Pi for object detection, face recognition, or smart camera projects, this repo helps you set up everything with ease.

In this project I've made a Drive Drowsiness Detector using Python, Pytorch and Yolo Model for Object Detection. Our aim was to build a fine tuned model which can help us to determine whether the driver is feeling drowsy or awake. We have used Ultralytics Yolo(v5) in this and used its base model which is trained on Coco dataset for object detection. After all the computation we were able to detect the face and provide the desired output in the real time by leveraging our webcam.

Face_detection_yolov8_ultralytics

A lightweight face emotion detection project built on Ultralytics YOLOv8.

Privacy-friendly pose skeleton + face mosaic video generator (YOLO/Ultralytics, tiled inference, JSONL cache)

A production-ready script to apply oval face blurring on all videos in a folder using Ultralytics YOLOv8n-face and OpenCV.

Real-time face and body detection system using YOLOv8 and OpenCV. Processes webcam/video input with bounding box annotations. Suitable for surveillance, attendance systems, and crowd analytics. Key Features: Dual-model detection (body + face) Real-time processing Easy customization Requirements: Python 3.8+, OpenCV, Ultralytics

This real-time system uses a YOLOv8 model to detect whether a face is real or fake via webcam. It draws colored bounding boxes with confidence scores and class labels ("REAL" or "FAKE") and displays the FPS. Built with OpenCV, cvzone, and Ultralytics YOLO, it’s fast, efficient, and customizable.

This real-time system uses a YOLOv8 model to detect whether a face is real or fake via webcam. It draws colored bounding boxes with confidence scores and class labels ("REAL" or "FAKE") and displays the FPS. Built with OpenCV, cvzone, and Ultralytics YOLO, it’s fast, efficient, and customizable.

This is an Ultralytics-based abnormal target detection project. Its primary function is to recognize fire, smoke, license plates, and faces, and to send corresponding alarm information and on-site images to a host computer. I provide detailed annotations, multiple models and datasets. You can select different models based on your specific needs.

Face mask detection using Pytorch and ultralytics/yolov5

This repo detects human face with YOLOv8 from ultralytics

No description available

Flutter playground for experimenting with Ultralytics-driven background segmentation and face mask binding.

This repository demonstrates how to implement object detection using the YOLOv8 model with Ultralytics to detect dog faces in images. The project leverages a pre-trained YOLO model to accurately detect and localize dog faces, a task that falls under the category of object detection.

This project tracks a predefined target face in a video, detects where the face appears, and extracts the video clips where the target face is present. The solution using Python, OpenCV, Ultralytics and Deepface libraries.

# FlappyFace - Face-Controlled Flappy Bird Game This is a Python-based Flappy Bird game controlled using face movement detected via webcam and YOLOv8. ## Requirements - Python 3.8+ - Pygame - OpenCV - Ultralytics (YOLOv8)

Python scripts for image classification (MobileNetV2, EfficientNetB7), face/body detection (MTCNN, Haar Cascade), and real-time object detection (YOLOv8). Ideal for ML beginners to detect objects/faces in images or webcam feeds. Requires TensorFlow, OpenCV, MTCNN, Ultralytics.

This project implements a Face Recognition System powered by YOLOv8. It combines face detection and face classification to recognize celebrity identities in real-time from images or videos. The system is trained on a celebrity face dataset and fine-tuned using Ultralytics YOLOv8 classification mode for accurate and efficient recognition.

A fast, interactive real-time object detection web app using YOLOv8 (Ultralytics) and streamlit-webrtc for live webcam streaming. Prototype in Kaggle/Colab, deploy seamlessly to Streamlit Community Cloud or Hugging Face Spaces.

Full-stack exam proctoring system with a React-based frontend and FastAPI microservices, using computer vision via OpenCV, MediaPipe, and Ultralytics YOLO for real-time face tracking, object detection, and rule-based exam monitoring.