Identify people with and without masks in images
Classify faces as male or female in images
Detect faces in an image from a URL
Mark faces in images and videos to show key landmarks
Face Recognition
Compare faces in two images to verify identity
3D Passive Face Liveness Detection (Face Anti-Spoofing)
Apply face swap to videos
Identify faces in photos and label them
Upload and search for faces in a database
Swap faces in images
Classify facial attractiveness and explain predictions
Detect and classify faces as real or fake
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.