this is it

app.py

@@ -96,6 +96,8 @@ def run_leukocoria_prediction(iris_crop):
 # --- 3. FastAPI Application ---
 app = FastAPI()
 
+# In app.py, replace the existing function with this one for testing
+
 @app.post("/detect/")
 async def full_detection_pipeline(image: UploadFile = File(...)):
     with tempfile.NamedTemporaryFile(delete=False, suffix=".jpg") as tmp:
@@ -111,10 +113,10 @@ async def full_detection_pipeline(image: UploadFile = File(...)):
         if not detect_faces_roboflow(temp_image_path):
             return JSONResponse(status_code=400, content={"error": "No face detected."})
 
-        # --- This is the final corrected logic with logging ---
+        # --- This is the test logic with eye_crops.reverse() removed ---
         
         image_to_process = raw_image
-        was_mirrored = False # Add a flag to track if we flipped the image
+        was_mirrored = False
         
         print("--- 1. Attempting detection on original image... ---")
         eye_crops, error_msg = detect_eyes_roboflow(temp_image_path, image_to_process)
@@ -124,7 +126,7 @@ async def full_detection_pipeline(image: UploadFile = File(...)):
             print("--- 3. Original failed. Attempting detection on mirrored image... ---")
             mirrored_image = cv2.flip(raw_image, 1)
             image_to_process = mirrored_image
-            was_mirrored = True # Set the flag to true
+            was_mirrored = True
             
             with tempfile.NamedTemporaryFile(delete=False, suffix=".jpg") as tmp_mirrored:
                 cv2.imwrite(tmp_mirrored.name, mirrored_image)
@@ -141,7 +143,6 @@ async def full_detection_pipeline(image: UploadFile = File(...)):
                 content={"error": "Could not detect exactly two eyes. Please try another photo."}
             )
 
-        # Get the bounding box coordinates before sorting
         initial_boxes = [cv2.boundingRect(cv2.cvtColor(c, cv2.COLOR_BGR2GRAY)) for c in eye_crops]
         print(f"--- 5. Initial eye coordinates (x,y,w,h): {initial_boxes} ---")
 
@@ -151,17 +152,14 @@ 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 for SWAPPED LABELS ---
+        # --- THE CHANGE ---
+        # The eye_crops.reverse() line has been removed for this test.
         if was_mirrored:
-            print("--- 7. Image was mirrored, reversing eye order for correct labeling. ---")
-            eye_crops.reverse()
-            reversed_boxes = [cv2.boundingRect(cv2.cvtColor(c, cv2.COLOR_BGR2GRAY)) for c in eye_crops]
-            print(f"--- 8. Reversed eye coordinates (x,y,w,h): {reversed_boxes} ---")
+            print("--- 7. Image was mirrored. (Reverse logic is currently disabled for testing) ---")
 
         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. ---")
             
@@ -177,7 +175,7 @@ async def full_detection_pipeline(image: UploadFile = File(...)):
                 has_leuko, confidence = run_leukocoria_prediction(iris_crop)
                 flags[side] = has_leuko
             else:
-                flags[side] = "No iris detected"
+                flags[side] = None
         
         print("--- 10. Final generated flags:", flags, "---")