cookedd

.gitignore

@@ -38,4 +38,5 @@ unified_dataset
 datasets
 runs
 best_saved_model
-history_archive
+history_archive
+palm_history.db

demo_app.py

@@ -98,6 +98,21 @@ overlay_colors = {
 }
 
 # Helper to reset results when files change or engine switches
+def get_color(class_name):
+    """Robust color lookup for consistent across models."""
+    # Normalize: "Under-ripe" -> "underripe", "Empty Bunch" -> "emptybunch"
+    norm_name = class_name.lower().replace("-", "").replace("_", "").replace(" ", "")
+    
+    # Map normalized names to your MPOB standard colors
+    color_map = {k.lower().replace("_", ""): v for k, v in overlay_colors.items()}
+    
+    if norm_name in color_map:
+        return color_map[norm_name]
+        
+    # Fallback: Generate a consistent unique color for benchmark-only classes
+    import hashlib
+    return f"#{hashlib.md5(class_name.encode()).hexdigest()[:6]}"
+
 def reset_single_results():
     st.session_state.last_detection = None
 
@@ -212,7 +227,9 @@ def display_interactive_results(image, detections, key=None):
         x1, y1, x2, y2 = det['box']
         # Plotly y-axis is inverted relative to PIL, so we flip y
         y_top, y_bottom = img_height - y1, img_height - y2
-        color = overlay_colors.get(det['class'], "#9ca3af") # Fallback to neutral gray
+        
+        color = get_color(det['class'])
+        is_bench = (st.session_state.get('engine_choice') == "Sawit-TBS (Benchmark)")
 
         # The 'Hover' shape
         bunch_id = det.get('bunch_id', i+1)
@@ -221,9 +238,9 @@ def display_interactive_results(image, detections, key=None):
             y=[y_top, y_top, y_bottom, y_bottom, y_top],
             fill="toself",
             fillcolor=color,
-            opacity=0.3, # Semi-transparent until hover
+            opacity=0.5 if is_bench else 0.3, # Stronger highlight for benchmark
             mode='lines',
-            line=dict(color=color, width=3),
+            line=dict(color=color, width=5 if is_bench else 3, dash='dot' if is_bench else 'solid'),
             name=f"ID: #{bunch_id}", # Unified ID Tag
             text=f"<b>ID: #{bunch_id}</b><br>Grade: {det['class']}<br>Score: {det['confidence']:.2f}<br>Alert: {det['is_health_alert']}",
             hoverinfo="text"
@@ -257,10 +274,11 @@ def annotate_image(image, detections):
         cls = det['class']
         conf = det['confidence']
         bunch_id = det.get('bunch_id', '?')
-        color = overlay_colors.get(cls, '#9ca3af') # Fallback to neutral gray
+        color = get_color(cls)
+        is_bench = (st.session_state.get('engine_choice') == "Sawit-TBS (Benchmark)")
         
         # 2. Draw Heavy-Duty Bounding Box
-        line_width = max(4, image.width // 150)
+        line_width = max(6 if is_bench else 4, image.width // (80 if is_bench else 150))
         draw.rectangle(box, outline=color, width=line_width)
 
         # 3. Draw 'Plated Label' (Background Shaded)
@@ -432,6 +450,9 @@ with tab1:
             data = st.session_state.last_detection
             st.divider()
             
+            if model_type == "benchmark":
+                st.info("💡 **Benchmark Mode**: Labels and colors are determined by the external model's architecture. Some labels may not match standard MPOB categories.")
+
             st.write("### 📈 Manager's Dashboard")
             m_col1, m_col2, m_col3, m_col4 = st.columns(4)
             with m_col1: