Update app.py

app.py

@@ -60,10 +60,14 @@ st.markdown("""
 
 # Title and description
 st.markdown('<div class="title">Emotion Detection</div>', unsafe_allow_html=True)
-st.markdown('<div class="description">Upload an image to detect emotions</div>', unsafe_allow_html=True)
+st.markdown('<div class="description">Upload an image or provide an image URL to detect emotions</div>', unsafe_allow_html=True)
+
+# Input field for image URL
+st.markdown('<div class="header">Enter Image URL</div>', unsafe_allow_html=True)
+image_url = st.text_input("Image URL")
 
 # File uploader for images
-st.markdown('<div class="header">Upload Image</div>', unsafe_allow_html=True)
+st.markdown('<div class="header">Or Upload Image</div>', unsafe_allow_html=True)
 image_file = st.file_uploader("Choose an image", type=["png", 'jpg'])
 
 # Sidebar to show previous predictions
@@ -74,10 +78,25 @@ st.sidebar.header("Previous Predictions")
 for pred in st.session_state.predictions:
     st.sidebar.image(pred['image'], caption=pred['emotion'], use_column_width=True)
 
-# Display the uploaded image and predict emotions
-if image_file is not None:
+# Function to load image from URL
+def load_image_from_url(url):
+    try:
+        response = requests.get(url)
+        img = Image.open(BytesIO(response.content))
+        return img
+    except Exception as e:
+        st.error(f"Error loading image: {e}")
+        return None
+
+# Display the image and predict emotions
+image = None
+if image_url:
+    image = load_image_from_url(image_url)
+elif image_file is not None:
     image = Image.open(image_file)
-    st.image(image, caption="Uploaded Image", use_column_width=True)
+
+if image:
+    st.image(image, caption="Selected Image", use_column_width=True)
 
     with st.spinner('Processing...'):
         st.markdown('<div class="spinner-text">Processing...</div>', unsafe_allow_html=True)