Update app.py

app.py

@@ -29,6 +29,16 @@ TIPS = {
     'cardboard': 'Recycle cardboard to reduce waste.'
 }
 
+# AI Eco Insights
+AI_MESSAGES = {
+    'plastic': "🤖 AI Insight: This appears to be plastic waste. Recycling plastic helps reduce pollution and protects oceans.",
+    'paper': "🤖 AI Insight: Paper waste detected. Recycling paper saves trees and reduces landfill burden.",
+    'metal': "🤖 AI Insight: Metal detected. Metal recycling conserves raw materials and energy.",
+    'glass': "🤖 AI Insight: Glass waste identified. Glass is highly recyclable and reusable.",
+    'trash': "🤖 AI Insight: General waste detected. Proper disposal minimizes environmental damage.",
+    'cardboard': "🤖 AI Insight: Cardboard detected. Recycling cardboard supports sustainable packaging."
+}
+
 # -----------------------------
 # PAGE SETTINGS
 # -----------------------------
@@ -41,9 +51,6 @@ st.set_page_config(
 # VALIDATE DATASET STRUCTURE
 # -----------------------------
 def validate_dataset():
-    """
-    Ensure dataset folder contains 6 required class subfolders
-    """
     if not os.path.exists(DATASET_DIR):
         st.error(f"❌ Dataset folder '{DATASET_DIR}' not found.")
         st.stop()
@@ -87,7 +94,7 @@ def train_and_save_model():
         DATASET_DIR,
         target_size=IMG_SIZE,
         batch_size=BATCH_SIZE,
-        classes=CLASSES,  # FORCE CORRECT CLASSES
+        classes=CLASSES,
         class_mode='categorical',
         subset='training',
         shuffle=True
@@ -262,19 +269,31 @@ if uploaded_file is not None:
         with st.spinner("🔍 Analyzing waste type..."):
             predicted_class, confidence, probabilities = predict_waste(image)
 
+        # Prediction Scores
         st.subheader("📊 Prediction Scores")
 
         for i, class_name in enumerate(CLASSES):
             st.progress(float(probabilities[i]))
             st.write(f"{class_name.upper()}: {probabilities[i] * 100:.2f}%")
 
+        # Main Output
         st.success(f"✅ Predicted Type: {predicted_class.upper()}")
         st.info(f"🎯 Confidence: {confidence:.2f}%")
         st.write(f"📁 Uploaded File: {uploaded_file.name}")
 
+        # Sustainability Tip
         st.subheader("🌱 Sustainability Suggestion")
         st.write(TIPS.get(predicted_class, "Dispose responsibly."))
 
+        # AI Environmental Analysis
+        st.subheader("🤖 AI Environmental Analysis")
+        st.success(
+            AI_MESSAGES.get(
+                predicted_class,
+                "AI recommends responsible disposal."
+            )
+        )
+
     except UnidentifiedImageError:
         st.error("❌ Invalid image file. Upload JPG, JPEG, or PNG.")
 
@@ -290,12 +309,13 @@ st.write("""
 Your dataset folder should look like:
 
 dataset-resized/
-├── cardboard/
-├── glass/
-├── metal/
-├── paper/
-├── plastic/
-└── trash/
+└── dataset-resized/
+    ├── cardboard/
+    ├── glass/
+    ├── metal/
+    ├── paper/
+    ├── plastic/
+    └── trash/
 """)
 
 # -----------------------------