chore: Convert image format for DeepFace analysis

app.py

@@ -4,30 +4,27 @@ import cv2
 import numpy as np
 
 def analyze_frame(frame):
-    result = DeepFace.analyze(frame, actions=['gender'], enforce_detection=False)
+    # 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, f"Gender: {gender}"
+    return frame, gender
 
-def video_feed():
-    camera = cv2.VideoCapture(0)
-    while True:
-        ret, frame = camera.read()
-        if not ret:
-            break
-        yield frame
-    camera.release()
+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
 
-with gr.Blocks() as demo:
-    gr.Markdown("# Real-time Gender Detection")
-
-    with gr.Row():
-        video_stream = gr.Video(source=video_feed, streaming=True)
-        result_image = gr.Image()
-
-    video_stream.stream(fn=analyze_frame, inputs=video_stream, outputs=result_image)
+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()
+    demo.launch()