Update app.py

app.py

@@ -10,10 +10,10 @@ from groq import Groq
 # Load environment variables
 load_dotenv()
 
-# Set up the Streamlit page
+# Page settings
 st.set_page_config(page_title="🌿 Leaf Disease Detector", layout="wide")
 st.markdown("<h1 style='text-align: center;'>🌿 Plant Leaf Disease Detection</h1>", unsafe_allow_html=True)
-st.markdown("<p style='text-align: center;'>Upload a leaf image to detect plant diseases and receive treatment advice.</p>", unsafe_allow_html=True)
+st.markdown("<p style='text-align: center;'>Upload a leaf image to detect plant diseases and get treatment guidance.</p>", unsafe_allow_html=True)
 st.markdown("---")
 
 # Initialize Groq client
@@ -24,7 +24,7 @@ except Exception as e:
     st.error(f"Failed to initialize Groq client: {str(e)}")
     client = None
 
-# Define a simple CNN model (dummy for demonstration)
+# Dummy CNN model
 class PlantDiseaseModel(nn.Module):
     def __init__(self, num_classes=28):
         super(PlantDiseaseModel, self).__init__()
@@ -52,7 +52,7 @@ def load_model():
 
 model = load_model()
 
-# Preprocessing image
+# Preprocessing
 def preprocess_image(image):
     transform = transforms.Compose([
         transforms.Resize((256, 256)),
@@ -75,7 +75,7 @@ disease_classes = [
     "Tomato Target Spot", "Tomato Yellow Leaf Curl Virus", "Tomato Mosaic Virus"
 ]
 
-# Predict disease
+# Predict class
 def classify_disease(image):
     try:
         img_tensor = preprocess_image(image)
@@ -88,7 +88,7 @@ def classify_disease(image):
         st.error(f"Error during classification: {str(e)}")
         return "Unknown"
 
-# Get disease info
+# Fetch disease info
 def get_disease_info(disease_name):
     if not client:
         return {
@@ -117,11 +117,16 @@ def get_disease_info(disease_name):
             "description": "Unable to fetch disease info. Please try again later.",
         }
 
-# Main App
+# Main app
 def main():
-    uploaded_file = st.file_uploader("📷 Upload a leaf image", type=["jpg", "jpeg", "png"])
+    uploaded_file = st.file_uploader("📷 Upload a leaf image", type=["jpeg", "png", "jpg"])
 
     if uploaded_file:
+        filename = uploaded_file.name.lower()
+        if not (filename.endswith(".jpg") or filename.endswith(".jpeg") or filename.endswith(".png")):
+            st.error("Only JPG, JPEG, and PNG files are allowed.")
+            st.stop()
+
         try:
             image = Image.open(uploaded_file).convert("RGB")
             st.image(image, caption="Uploaded Leaf Image", width=400)
@@ -136,12 +141,12 @@ def main():
 
                     col1, col2 = st.columns([1, 2])
                     with col1:
-                        status = "Healthy ✅" if disease_name.lower() == "healthy" else "Diseased ⚠️"
+                        status = "✅ Healthy" if disease_name.lower() == "healthy" else "⚠️ Diseased"
                         st.markdown(f"**Status:** {status}")
                         st.markdown(f"**Detected Disease:** `{disease_name}`")
 
                     with col2:
-                        st.markdown("**📋 Details:**")
+                        st.markdown("**📋 Disease Info:**")
                         st.markdown(info["description"])
         except Exception as e:
             st.error(f"Error processing image: {str(e)}")