Update app.py

app.py

@@ -7,7 +7,7 @@ import numpy as np
 # Initialize emotion detector
 emotion_detector = FER()
 
-# Function to process uploaded image
+# Function to process image and detect emotions
 def process_image(image):
     frame = np.array(image)
     frame = cv2.cvtColor(frame, cv2.COLOR_RGB2BGR)  # Convert from PIL to OpenCV format
@@ -42,14 +42,19 @@ def process_image(image):
     return cv2.cvtColor(blurred_frame, cv2.COLOR_BGR2RGB)  # Convert back to RGB for Streamlit
 
 # Streamlit UI
-st.title("Emotion Recognition App")
-st.write("Upload an image to detect emotions.")
+st.title("Real-Time Emotion Recognition")
+st.write("Use the camera or upload an image to detect emotions.")
 
-uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "png", "jpeg"])
+# Camera Input
+camera_image = st.camera_input("Take a picture")
+
+# File Upload
+uploaded_file = st.file_uploader("Or upload an image...", type=["jpg", "png", "jpeg"])
+
+# Process image if uploaded or captured via camera
+if camera_image or uploaded_file:
+    image = Image.open(camera_image if camera_image else uploaded_file)
+    st.image(image, caption="Captured Image", use_column_width=True)
 
-if uploaded_file is not None:
-    image = Image.open(uploaded_file)
-    st.image(image, caption="Uploaded Image", use_column_width=True)
-    
     processed_image = process_image(image)
     st.image(processed_image, caption="Processed Image with Emotions", use_column_width=True)