Update face1.py

face1.py

@@ -1,77 +1,77 @@
-import streamlit as st
-import cv2
-import numpy as np
-from deepface import DeepFace
-
-st.set_page_config(
-    page_title="✨ Age & Gender Predictor",
-    page_icon=":sparkles:",
-    layout="centered",
-)
-
-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.  
-    
-    **No data is stored**.
-    """
-)
-
-uploaded_file = st.file_uploader("Upload an image...", type=["jpg", "jpeg", "png"])
-
-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)
-    
-    image_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
-    
-    st.image(image_rgb, caption="Your Uploaded Image", use_container_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}")
-                
-        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"
-            )
-
-st.markdown("---")
-st.markdown(
-    """
-    **Powered by DeepFace & RetinaFace**    
-    """
+import streamlit as st
+import cv2
+import numpy as np
+from deepface import DeepFace
+
+st.set_page_config(
+    page_title="✨ Age & Gender Predictor",
+    page_icon=":sparkles:",
+    layout="centered",
+)
+
+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.  
+    
+    **No data is stored**.
+    """
+)
+
+uploaded_file = st.file_uploader("Upload an image...", type=["jpg", "jpeg", "png"])
+
+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)
+    
+    image_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
+    
+    st.image(image_rgb, caption="Your Uploaded Image", use_container_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}")
+                
+        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"
+            )
+
+st.markdown("---")
+st.markdown(
+    """
+    **Powered by DeepFace & RetinaFace**    
+    """
 )