with enhanced_eye_crop

app.py

@@ -59,10 +59,17 @@ def detect_eyes_roboflow(image_path, raw_image):
         print(f"Error in Roboflow eye detection: {e}")
         return [], str(e)
 
+# In app.py, replace the existing function with this one
+
 def get_largest_iris_prediction(eye_crop):
     "Calls Roboflow to find the largest iris using a temporary file for reliability."
+    
+    # --- NEW: Enhance the eye crop before saving it ---
+    enhanced_eye_crop = enhance_image_unsharp_mask(eye_crop)
+
     with tempfile.NamedTemporaryFile(delete=False, suffix=".jpg") as tmp:
-        cv2.imwrite(tmp.name, eye_crop)
+        # Save the ENHANCED version, not the original
+        cv2.imwrite(tmp.name, enhanced_eye_crop)
         temp_iris_path = tmp.name
 
     try:
@@ -144,7 +151,7 @@ async def full_detection_pipeline(image: UploadFile = File(...)):
         sorted_boxes = [cv2.boundingRect(cv2.cvtColor(c, cv2.COLOR_BGR2GRAY)) for c in eye_crops]
         print(f"--- 6. Sorted eye coordinates (x,y,w,h): {sorted_boxes} ---")
         
-        # --- THE CRITICAL FIX ---
+        # --- THE CRITICAL FIX for SWAPPED LABELS ---
         if was_mirrored:
             print("--- 7. Image was mirrored, reversing eye order for correct labeling. ---")
             eye_crops.reverse()
@@ -154,6 +161,7 @@ async def full_detection_pipeline(image: UploadFile = File(...)):
         flags = {}
         eye_images_b64 = {}
         for i, eye_crop in enumerate(eye_crops):
+            # Because of the sort and potential reverse, i=0 is ALWAYS the person's right eye
             side = "right" if i == 0 else "left"
             print(f"--- 9. Processing loop index {i}, assigning to: {side} eye. ---")