Update app/main.py

app/main.py

@@ -1,6 +1,6 @@
 # app/main.py
 import os
-os.environ["TF_CPP_MIN_LOG_LEVEL"] = "2"  # quiet TF/MediaPipe logs
+os.environ["TF_CPP_MIN_LOG_LEVEL"] = "2"  
 from absl import logging as absl_logging
 absl_logging.set_verbosity(absl_logging.ERROR)
 
@@ -136,10 +136,8 @@ def blur_faces_oval(img_bgr: np.ndarray, boxes):
         rh, rw = roi.shape[:2]
 
         k_base = int(KERNEL_FRAC * max(w, h))
-        # clamp to ROI and ensure odd
         k = odd(max(MIN_KERNEL, min(MAX_KERNEL, k_base, rh - (rh % 2 == 0), rw - (rw % 2 == 0))))
         if k < 9:
-            # fallback to pixelation if ROI too small
             small = cv2.resize(roi, (max(1, rw // 10), max(1, rh // 10)), interpolation=cv2.INTER_LINEAR)
             roi_blur = cv2.resize(small, (rw, rh), interpolation=cv2.INTER_NEAREST)
         else:
@@ -177,13 +175,11 @@ async def upload_image(request: Request, file: UploadFile = File(...)):
             "request": request, "error": "Could not decode image.", "result": None
         })
 
-    # Optional downscale for very large images
     H, W = img.shape[:2]
     scale = min(1.0, float(MAX_SIDE) / max(H, W))
     if scale < 1.0:
         img = cv2.resize(img, (int(W * scale), int(H * scale)), interpolation=cv2.INTER_AREA)
 
-    # Detection pipeline
     img_proc = gentle_contrast_boost(img)
     boxes = detect_faces_mediapipe(img_proc)
     faces_count = len(boxes)
@@ -191,7 +187,6 @@ async def upload_image(request: Request, file: UploadFile = File(...)):
     preview = draw_unblurred_preview(img_proc, boxes)
     blurred  = blur_faces_oval(img_proc, boxes)
 
-    # Save to /tmp and serve via /results
     uid = uuid.uuid4().hex
     annot_name = f"{uid}_annot.jpg"
     blur_name  = f"{uid}_blur.jpg"