app.py

import gradio as gr
import cv2
import numpy as np
from simple_facerec import SimpleFacerec

# Initialize face recognition
sfr = SimpleFacerec()
sfr.load_encoding_images("images/")

def detect_faces(image):
    if image is None:
        return "No image provided"
    
    # Convert from BGR to RGB
    frame = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
    
    # Detect faces
    face_locations, face_names = sfr.detect_known_faces(frame)
    
    # Draw rectangles and names on the image
    for face_loc, name in zip(face_locations, face_names):
        y1, x2, y2, x1 = face_loc[0], face_loc[1], face_loc[2], face_loc[3]
        
        # Draw rectangle
        cv2.rectangle(frame, (x1, y1), (x2, y2), (0, 255, 0), 2)
        # Add name
        cv2.putText(frame, name, (x1, y1 - 10), cv2.FONT_HERSHEY_DUPLEX, 1, (0, 255, 0), 2)
    
    return cv2.cvtColor(frame, cv2.COLOR_RGB2BGR)

# Create Gradio interface
iface = gr.Interface(
    fn=detect_faces,
    inputs=gr.Image(sources=["webcam"], streaming=True),  # New syntax uses "sources"
    outputs=gr.Image(),
    title="Face Recognition System",
    description="Use webcam or upload an image to detect and recognize faces.",
    live=True
)

if __name__ == "__main__":
    iface.launch(share=True)  # Ensure share is set to True