Update app.py

app.py

@@ -99,6 +99,7 @@ def extract_region_from_editor(editor_data):
 
 def calculate_blue_intensity(image_np, masks):
     """Calculate blue intensity for each cell"""
+    # Ensure image is in correct format
     if len(image_np.shape) == 2:
         # Convert grayscale to RGB
         image_np = cv2.cvtColor(image_np, cv2.COLOR_GRAY2RGB)
@@ -110,6 +111,10 @@ def calculate_blue_intensity(image_np, masks):
     cell_blue_intensities = {}
     unique_cells = np.unique(masks)
     
+    print(f"DEBUG: Found {len(unique_cells)} unique mask values: {unique_cells}")
+    print(f"DEBUG: Image shape: {image_np.shape}, dtype: {image_np.dtype}")
+    print(f"DEBUG: Masks shape: {masks.shape}, dtype: {masks.dtype}")
+    
     for cell_id in unique_cells:
         if cell_id == 0:  # Skip background
             continue
@@ -118,18 +123,24 @@ def calculate_blue_intensity(image_np, masks):
         cell_pixels = image_np[cell_mask]
         
         if len(cell_pixels) > 0:
-            # Calculate mean blue intensity (blue channel)
-            blue_intensity = np.mean(cell_pixels[:, 2])  # Blue channel is index 2
+            # Calculate mean blue intensity (blue channel is index 2)
+            blue_intensity = np.mean(cell_pixels[:, 2])  # Blue channel
             cell_blue_intensities[cell_id] = blue_intensity
+            print(f"DEBUG: Cell {cell_id}: {len(cell_pixels)} pixels, blue intensity: {blue_intensity:.2f}")
     
+    print(f"DEBUG: Total cells with blue intensity: {len(cell_blue_intensities)}")
     return cell_blue_intensities
 
 def create_viability_overlay(image_np, masks, blue_threshold):
     """Create overlay showing live/dead cells based on blue threshold"""
     
     if masks is None or image_np is None:
+        print("DEBUG: masks or image_np is None")
         return None, 0, 0
     
+    print(f"DEBUG: create_viability_overlay called with threshold: {blue_threshold}")
+    print(f"DEBUG: Image shape: {image_np.shape}, Masks shape: {masks.shape}")
+    
     # Ensure image is RGB
     if len(image_np.shape) == 2:
         image_np = cv2.cvtColor(image_np, cv2.COLOR_GRAY2RGB)
@@ -139,6 +150,8 @@ def create_viability_overlay(image_np, masks, blue_threshold):
     # Calculate blue intensities
     cell_blue_intensities = calculate_blue_intensity(image_np, masks)
     
+    print(f"DEBUG: Got {len(cell_blue_intensities)} cells with blue intensities")
+    
     # Create overlay - start with original image
     overlay = image_np.copy().astype(np.float32)
     
@@ -149,14 +162,20 @@ def create_viability_overlay(image_np, masks, blue_threshold):
     for cell_id, blue_intensity in cell_blue_intensities.items():
         cell_mask = masks == cell_id
         
+        print(f"DEBUG: Processing cell {cell_id}, blue intensity: {blue_intensity:.2f}, threshold: {blue_threshold}")
+        
         if blue_intensity > blue_threshold:
             # Dead cell - color in red
             overlay[cell_mask] = [255, 0, 0]  # Red
             dead_count += 1
+            print(f"DEBUG: Cell {cell_id} classified as DEAD")
         else:
             # Live cell - color in green
             overlay[cell_mask] = [0, 255, 0]  # Green
             live_count += 1
+            print(f"DEBUG: Cell {cell_id} classified as LIVE")
+    
+    print(f"DEBUG: Final counts - Live: {live_count}, Dead: {dead_count}")
     
     # Blend with original image
     alpha = 0.6  # Increased alpha for better visibility