contrast without blur

inference_test.py

@@ -124,29 +124,16 @@ def adjust_gamma(image, gamma=1.0, alpha=1.0, beta=0):
     return adjusted
 
 
-def enhance_text(image_path):
-    # Improve contrast using CLAHE
-    gray = cv2.imread(image_path, cv2.IMREAD_GRAYSCALE)
-    clahe = cv2.createCLAHE(clipLimit=3.0, tileGridSize=(8, 8))
-    contrast = clahe.apply(gray)
-
-    # Apply adaptive thresholding to emphasize text
-    binarized = cv2.adaptiveThreshold(
-        contrast, 255,
-        cv2.ADAPTIVE_THRESH_GAUSSIAN_C,
-        cv2.THRESH_BINARY,
-        blockSize=11,
-        C=2
-    )
-
-    return binarized
 
 def preprocess_image(image_path):
     # Load image in grayscale (1-channel)
-    gray = enhance_text(image_path)
+    gray = cv2.imread(image_path, cv2.IMREAD_GRAYSCALE)
     resampled = bicubic(gray) 
     # Convert grayscale to 3-channel RGB by duplicating the gray channel
-    img = contrast_stretch(adjust_gamma(cv2.cvtColor(resampled, cv2.COLOR_GRAY2RGB),gamma=1.6,alpha=1.75,beta=-15)) # perfect tunning
+    img1 = contrast_stretch(adjust_gamma(cv2.cvtColor(resampled, cv2.COLOR_GRAY2RGB),gamma=1,alpha=1.4,beta=-5)) # perfect tunning
+    
+    img = cv2.fastNlMeansDenoising(img1, None, 20, 10, 20)
+    
     plt.imshow(img)
     plt.axis("off")
     plt.savefig("/tmp/output.png", bbox_inches="tight", pad_inches=0)