too light

inference_test.py

@@ -78,8 +78,17 @@ class TextProcessor:
         # Filter out special tokens
         cleaned = self.special_token_pattern.sub('', text)
         
+        
         # Remove consecutive duplicates
-        return cleaned
+        if not cleaned:
+            return ''
+            
+        result = [cleaned[0]]
+        for char in cleaned[1:]:
+            if char != result[-1]:
+                result.append(char)
+        return ''.join(result)
+
 
 
     def decode(self, indices) -> str:
@@ -130,13 +139,13 @@ def preprocess_image(image_path):
     gray = cv2.imread(image_path, cv2.IMREAD_GRAYSCALE)
 
     # Convert grayscale to 3-channel RGB by duplicating the gray channel
-    img = adjust_gamma(cv2.cvtColor(gray, cv2.COLOR_GRAY2RGB),gamma=1.67,alpha=1.67,beta=-6) # perfect tunning
+    img = adjust_gamma(cv2.cvtColor(gray, cv2.COLOR_GRAY2RGB),gamma=1.3,alpha=1.65,beta=-2) # perfect tunning
     mat_in = ncnn.Mat.from_pixels_resize(
         img, ncnn.Mat.PixelType.PIXEL_RGB, img.shape[1], img.shape[0], 224, 224
     )
     
-    mean_vals = [0.5, 0.5, 0.5] * 3
-    norm_vals = [1/255, 1/255, 1/255] * 3
+    mean_vals = [0.5, 0.5, 0.5] * 2
+    norm_vals = [1/255, 1/255, 1/255] * 2
     mat_in.substract_mean_normalize(mean_vals, norm_vals)
     return mat_in