Update app.py

app.py

@@ -2,6 +2,7 @@ import gradio as gr
 from ultralytics import YOLO
 import numpy as np
 from PIL import Image
+import os
 
 # 1. Load your trained YOLO26n-seg model
 # The system looks for 'comic-panels-and-text-detect.pt' in the same directory
@@ -19,18 +20,23 @@ def predict_comic(input_image):
     if input_image is None:
         return None, "Please upload an image first."
 
-    # Convert PIL Image to numpy array for YOLO processing
-    img_array = np.array(input_image)
+    # 💡 CRITICAL FIX: Save to lossless raw PNG temp file.
+    # This prevents Gradio from altering pixel arrays and enforces native Ultralytics decoding.
+    tmp_path = "tmp_input_raw.png"
+    input_image.save(tmp_path, format="PNG", quality=100)
 
-    # Execute segmentation pipeline using optimized configurations
-    # imgsz=1280 ensures small manga text and detailed panels aren't missed
+    # Execute segmentation pipeline mirroring your exact local CLI parameters
     results = model.predict(
-        source=img_array,
+        source=tmp_path,
         conf=0.25,
         iou=0.70,
         imgsz=1280
     )
 
+    # Safe cleanup of the temporary file
+    if os.path.exists(tmp_path):
+        os.remove(tmp_path)
+
     # Extract prediction elements from the primary image result
     res = results[0]