Facial_Emotion_Recogniser
Detect facial expressions in images
Replace faces in images or videos
Identify ethnicity group from a picture
Upload an image to segment the face
Verify student ID by comparing face images
Identify emotions from a face photo
Swap faces in photos
Distinguish between cat and dog faces
Face liveness detection and verification
Detect and visualize facial landmarks from a live video feed
age estimation
Identify people with and without masks in images
Facial Emotion Recogniser is an advanced AI-powered tool designed to identify and analyse human emotions through facial expressions. Using cutting-edge technology, it can detect and classify emotions such as happiness, sadness, anger, surprise, and more. This tool is ideal for applications in psychology, marketing, security, and customer service, providing real-time insights into emotional states.
• Accurate Emotion Detection: Recognises emotions with high precision using deep learning algorithms. • Real-Time Analysis: Processes facial expressions instantly, making it suitable for live interactions. • Multiple Emotion Categories: Supports detection of up to 7 basic emotions (happy, sad, angry, surprised, neutral, disgust, and fear). • Cross-Platform Compatibility: Works seamlessly on desktops, mobile devices, and integrated systems. • Customisable Settings: Allows users to fine-tune sensitivity and emotion thresholds. • Data Privacy: Ensures secure processing of facial data with compliance to privacy regulations.
What devices does Facial Emotion Recogniser support?
Facial Emotion Recogniser is compatible with most modern smartphones, tablets, and desktop computers. It can also be integrated into IoT devices and security systems.
How accurate is Facial Emotion Recogniser?
The tool achieves an accuracy rate of 95% or higher under optimal lighting conditions. Accuracy may vary based on image quality and environmental factors.
Is my data secure when using Facial Emotion Recogniser?
Yes, all data processed by Facial Emotion Recogniser is encrypted and anonymised to ensure user privacy and compliance with data protection laws.