app.py

import gradio as gr
from deepface import DeepFace
import cv2
import numpy as np

def analyze_frame(frame):
    # Convert frame from BGR to RGB format for DeepFace
    frame_rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
    result = DeepFace.analyze(frame_rgb, actions=['gender'], enforce_detection=False)
    if result:
        gender = result[0]['gender']
    else:
        gender = "No face detected"
    return frame, gender

def process_webcam_image(image):
    # Convert the image to a format suitable for DeepFace
    image = cv2.cvtColor(np.array(image), cv2.COLOR_RGB2BGR)
    frame, gender = analyze_frame(image)
    return frame, gender

demo = gr.Interface(
    fn=process_webcam_image, 
    inputs=gr.Image(source="webcam", streaming=True), 
    outputs=[gr.Image(), gr.Textbox()],
    live=True
)

if __name__ == "__main__":
    demo.launch()