Identify people with and without masks in images
Identify and match faces from webcam input
Analyze if an image contains a deepfake face
Recognize faces in a live video stream
happy or some other emotion - facial expression
Swap faces in videos
Analyze face image to predict attractiveness, gender, glasses, and facial hair
3D Passive Face Liveness Detection (Face Anti-Spoofing)
Block out underage faces in real-time video
Gaze detection using Moondream
Face liveness detection and verification
Swap faces in images or videos
Identify emotions from a face photo
YOLOv7 Face Mask is an AI-powered tool designed to identify and detect people wearing face masks in images. Built using the advanced YOLOv7 object detection model, it provides high accuracy and efficiency in detecting faces with or without masks. This solution is ideal for applications requiring face mask compliance verification, public safety monitoring, and more.
• High Accuracy: Detects masks with precision in various lighting conditions and angles.
• Real-Time Processing: Enables fast detection for live video streams or real-time applications.
• Multi-Platform Support: Works on mobile, desktop, and web applications seamlessly.
• Efficient Architecture: Optimized for low-latency performance while maintaining accuracy.
• Bounding Box Detection: Provides coordinates for detected faces and masks.
What is YOLOv7 Face Mask used for?
YOLOv7 Face Mask is primarily used to detect and identify individuals wearing face masks in images or video streams, making it useful for security, healthcare, and public safety applications.
Can YOLOv7 Face Mask work in real-time?
Yes, YOLOv7 Face Mask supports real-time detection and can process live video feeds efficiently.
Is YOLOv7 Face Mask customizable?
Yes, the model can be fine-tuned for specific use cases, such as adjusting detection thresholds or adding custom classes.