fix

app.py

@@ -6,19 +6,28 @@ from PIL import Image
 import pytesseract
 
 def enhance(img):
-    gaussian_thresh = cv2.adaptiveThreshold(
-    img, 
-    maxValue=255, 
-    adaptiveMethod=cv2.ADAPTIVE_THRESH_GAUSSIAN_C, 
-    thresholdType=cv2.THRESH_BINARY, 
-    blockSize=11, 
-    C=2)
-    return gaussian_thresh
+    # Apply GaussianBlur to reduce noise
+    blurred = cv2.GaussianBlur(img, (5, 5), 0)
+
+    # Apply adaptive thresholding to enhance text
+    thresh = cv2.adaptiveThreshold(
+        blurred, 
+        255, 
+        cv2.ADAPTIVE_THRESH_GAUSSIAN_C, 
+        cv2.THRESH_BINARY, 
+        11, 
+        2
+    )
+
+    # Perform morphological operations to remove small noise and connect text components
+    kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (3, 3))
+    morph = cv2.morphologyEx(thresh, cv2.MORPH_CLOSE, kernel)
+    return morph
 
 act =  [(150,240), (610,260)]
 
 
-def align_images(ref_gray, input_gray, enh= True):
+def align_images(ref_gray, input_gray, enh= False):
     """
     Aligns the input image to the reference image using homography.
     
@@ -35,9 +44,11 @@ def align_images(ref_gray, input_gray, enh= True):
     if enh:
         ref_gray = enhance(ref_gray)
         input_gray = enhance(input_gray)
+        st.image(ref_gray)
+        st.image(input_gray)
     
     # Detect ORB keypoints and descriptors
-    orb = cv2.ORB_create(nfeatures=500)
+    orb = cv2.ORB_create(nfeatures=1500)
     keypoints1, descriptors1 = orb.detectAndCompute(ref_gray, None)
     keypoints2, descriptors2 = orb.detectAndCompute(input_gray, None)