Identify people with and without masks in images
Swap faces in images
Detect and visualize facial landmarks from a live video feed
Identify and match faces from webcam input
3D Passive Face Liveness Detection (Face Anti-Spoofing)
Swap faces in videos
Classify facial expressions in images
Find and highlight face landmarks in images
Analyze face image to predict attractiveness, gender, glasses, and facial hair
Swap faces in a video
Detect faces in uploaded images
Swap faces in images and videos
Register, recognize, and delete users using face and voice
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.