Update app.py

app.py

@@ -2,6 +2,7 @@ import streamlit as st
 import cv2
 import numpy as np
 from deepface import DeepFace
+import time
 
 st.set_page_config(
     page_title="✨ Age & Gender Predictor",
@@ -13,61 +14,139 @@ st.title("✨ Age & Gender Predictor")
 st.write(
     """
     Welcome to the future of facial analysis!  
-    **Upload your photo** and let our cutting-edge AI reveal your age and gender with impressive precision.  
+    **Enable your webcam** and let our cutting-edge AI reveal your age and gender with impressive precision.
     
     **No data is stored**.
     """
 )
 
-uploaded_file = st.file_uploader("Upload an image...", type=["jpg", "jpeg", "png"])
+# Create placeholders for webcam and captured image
+webcam_placeholder = st.empty()
+captured_image_placeholder = st.empty()
 
-if uploaded_file is not None:
-    file_bytes = np.asarray(bytearray(uploaded_file.read()), dtype=np.uint8)
-    image = cv2.imdecode(file_bytes, cv2.IMREAD_COLOR)
+# Create columns for buttons
+col1, col2 = st.columns(2)
+start_button = col1.button("Start Webcam")
+capture_button = col2.button("Capture Image", disabled=True)
+
+# Results area
+results_area = st.container()
+
+# Initialize session state variables if they don't exist
+if 'camera_on' not in st.session_state:
+    st.session_state.camera_on = False
+if 'captured_image' not in st.session_state:
+    st.session_state.captured_image = None
+
+# Function to start webcam
+def start_webcam():
+    st.session_state.camera_on = True
+    st.experimental_rerun()
+
+# Function to capture image
+def capture_image():
+    st.session_state.camera_on = False
+    st.experimental_rerun()
+
+# Set button callbacks
+if start_button:
+    start_webcam()
+if capture_button:
+    capture_image()
+
+# Main webcam logic
+if st.session_state.camera_on:
+    # Update the UI to show the webcam is active
+    capture_button = col2.button("Capture Image", key='capture_active', on_click=capture_image)
+    stop_button = col1.button("Stop Webcam", key='stop_webcam', on_click=lambda: setattr(st.session_state, 'camera_on', False))
+    
+    # Display webcam feed
+    cap = cv2.VideoCapture(0)
+    
+    if not cap.isOpened():
+        st.error("Could not open webcam. Please check your camera connection.")
+    else:
+        # Get a frame
+        ret, frame = cap.read()
+        if ret:
+            # Convert to RGB for display
+            frame_rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
+            # Display the frame
+            webcam_placeholder.image(frame_rgb, channels="RGB", caption="Webcam Feed", use_column_width=True)
+            # Store the current frame
+            st.session_state.captured_image = frame.copy()
+        else:
+            st.error("Failed to capture image from webcam.")
+        
+        # Small delay to allow UI updates
+        time.sleep(0.1)
+        
+        # Release the camera
+        cap.release()
+        
+        # Force a rerun to get another frame (creates a video effect)
+        if st.session_state.camera_on:
+            time.sleep(0.1)
+            st.experimental_rerun()
+
+# If we have a captured image, display and analyze it
+elif st.session_state.captured_image is not None:
+    # Re-enable the start webcam button with a new key
+    start_again_button = col1.button("Restart Webcam", key='restart_webcam', on_click=start_webcam)
+    
+    # Get the captured image
+    image = st.session_state.captured_image
     
+    # Convert to RGB for display
     image_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
     
-    st.image(image_rgb, caption="Your Uploaded Image", use_container_width=True)
+    # Show the captured image
+    captured_image_placeholder.image(image_rgb, caption="Captured Image", use_column_width=True)
     
-    with st.spinner("Analyzing your image with advanced AI models..."):
-        try:
-            results = DeepFace.analyze(
-                image,
-                actions=['age', 'gender'],
-                detector_backend='retinaface', 
-                enforce_detection=True,
-                align=True
-            )
-            
-            if isinstance(results, list):
-                results = sorted(results, key=lambda x: x['face_confidence'], reverse=True)
-                main_result = results[0]
-            else:
-                main_result = results
-
-            st.success("Analysis complete! Here's what we found:")
-            st.write("## Detailed Results")
-            
-            age = main_result['age']
-            st.write(f"**Predicted Age:** {age} years")
-            
-            gender = main_result['gender']
-            dominant_gender = gender if isinstance(gender, str) else max(gender, key=gender.get)
-            confidence = gender[dominant_gender] if isinstance(gender, dict) else None
-            
-            if confidence:
-                st.write(f"**Predicted Gender:** {dominant_gender} ({confidence:.2f}% confidence)")
-            else:
-                st.write(f"**Predicted Gender:** {dominant_gender}")
+    # Analyze the image
+    with results_area:
+        with st.spinner("Analyzing your image with advanced AI models..."):
+            try:
+                results = DeepFace.analyze(
+                    image,
+                    actions=['age', 'gender'],
+                    detector_backend='retinaface',
+                    enforce_detection=True,
+                    align=True
+                )
                 
-        except Exception as e:
-            st.error(f"Analysis failed: {str(e)}")
-            st.info(
-                "For best results, please try the following tips:\n"
-                "- Use a well-lit, clear photo\n"
-                "- Ensure your face is fully visible\n"
-                "- Avoid low-resolution images"
-            )
+                if isinstance(results, list):
+                    results = sorted(results, key=lambda x: x.get('face_confidence', 0), reverse=True)
+                    main_result = results[0]
+                else:
+                    main_result = results
+                
+                st.success("Analysis complete! Here's what we found:")
+                st.write("## Detailed Results")
+                
+                age = main_result['age']
+                st.write(f"**Predicted Age:** {age} years")
+                
+                gender = main_result['gender']
+                dominant_gender = gender if isinstance(gender, str) else max(gender, key=gender.get)
+                confidence = gender[dominant_gender] if isinstance(gender, dict) else None
+                
+                if confidence:
+                    st.write(f"**Predicted Gender:** {dominant_gender} ({confidence:.2f}% confidence)")
+                else:
+                    st.write(f"**Predicted Gender:** {dominant_gender}")
+            
+            except Exception as e:
+                st.error(f"Analysis failed: {str(e)}")
+                st.info(
+                    "For best results, please try the following tips:\n"
+                    "- Ensure good lighting conditions\n"
+                    "- Position your face clearly in the frame\n"
+                    "- Move closer to the camera if needed"
+                )
+else:
+    # Initial state, just display start webcam button
+    st.info("Click 'Start Webcam' to begin")
 
 st.markdown("---")
 st.markdown(