Update app.py

app.py

@@ -1,40 +1,40 @@
 import streamlit as st
+from fer import FER  # Import FER only for image processing
+import cv2
 from PIL import Image
 import numpy as np
-import requests
-from io import BytesIO
-import cv2
-from fer import FER  # Ensure this package is in requirements.txt
 
-# Title and Description
-st.title("Emotion Recognition App")
-st.write("Upload a face image to detect emotions using AI!")
+# Application Title
+st.title("Emotion Recognition for Autism Support")
 
-# File upload section
-uploaded_file = st.file_uploader("Upload a face image", type=["jpg", "jpeg", "png"])
+# Upload Image Section
+uploaded_image = st.file_uploader("Upload an Image with a Face", type=["jpg", "jpeg", "png"])
 
-if uploaded_file is not None:
-    # Display the uploaded image
-    image = Image.open(uploaded_file)
+if uploaded_image:
+    # Load the image
+    image = Image.open(uploaded_image)
     st.image(image, caption="Uploaded Image", use_column_width=True)
+    
+    # Convert PIL Image to NumPy Array
+    img_np = np.array(image)
+
+    # Convert RGB to BGR (required by OpenCV)
+    img_bgr = cv2.cvtColor(img_np, cv2.COLOR_RGB2BGR)
+
+    # Initialize FER detector
+    detector = FER(mtcnn=False)  # Disable MTCNN if not needed
+
+    # Detect emotions
+    st.write("Analyzing emotions...")
+    result = detector.detect_emotions(img_bgr)
+
+    if result:
+        for face in result:
+            emotions = face['emotions']
+            st.write("Detected Emotions:")
+            st.json(emotions)
+    else:
+        st.warning("No faces detected in the image. Please try another image.")
 
-    # Convert image to a numpy array
-    img_array = np.array(image)
-
-    # Process the image for emotion detection
-    st.write("Detecting emotions...")
-    detector = FER(mtcnn=True)  # Initialize the FER+ detector
-
-    try:
-        # Detect emotions
-        result = detector.top_emotion(img_array)
-        if result:
-            emotion, score = result
-            st.write(f"Detected Emotion: **{emotion.capitalize()}** with confidence {score * 100:.2f}%")
-        else:
-            st.write("No clear emotion detected. Please try another image.")
-    except Exception as e:
-        st.error(f"Error processing the image: {e}")
-
-# Footer
-st.write("Emotion recognition powered by FER+")
+    # Provide Friendly Feedback
+    st.write("Emotion recognition will be refined in future updates!")