diff --git a/scripts/deskew_demo.py b/scripts/deskew_demo.py
index 7a05806..ddbc22c 100644
--- a/scripts/deskew_demo.py
+++ b/scripts/deskew_demo.py
@@ -1,4 +1,4 @@
-#sample usage: python3 scripts/deskew_demo.py /path/to/crooked.pdf 0
+# sample usage: python3 scripts/deskew_demo.py /path/to/crooked.pdf 0
 import argparse
 import numpy as np
 import pdf2image
@@ -11,7 +11,7 @@ def parse_args():
     parser = argparse.ArgumentParser()
     parser.add_argument("pdf_path")
     parser.add_argument("page_index", type=int)
-    
+
     args = parser.parse_args()
 
     return args
diff --git a/vidocp/utils/deskew.py b/vidocp/utils/deskew.py
index 70c36ff..0022f1e 100644
--- a/vidocp/utils/deskew.py
+++ b/vidocp/utils/deskew.py
@@ -2,40 +2,42 @@ import numpy as np
 import cv2
 
 
-def detect_angle(im: np.array, max_skew_deg=10, min_nlines=5) -> int:
+def detect_angle(im: np.array, max_skew_deg=10, min_skew_deg=0.1, min_nlines=5) -> int:
     max_skew_rad = np.deg2rad(max_skew_deg)
+    min_skew_rad = np.deg2rad(min_skew_deg)
     width = im.shape[1]
 
     im_gs = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)
     im_gs = cv2.fastNlMeansDenoising(im_gs, h=3)
     im_bw = cv2.threshold(im_gs, 0, 255, cv2.THRESH_BINARY_INV | cv2.THRESH_OTSU)[1]
 
-    lines = cv2.HoughLinesP(
-        im_bw, 1, np.pi / 180, 200, minLineLength=width / 12, maxLineGap=width / 150
-    )
+    lines = cv2.HoughLinesP(im_bw, 1, np.pi / 180, 200, minLineLength=width / 12, maxLineGap=width / 150)
 
     angles = []
     for line in lines:
         x1, y1, x2, y2 = line[0]
-        angles.append(np.arctan2(y2 - y1, x2 - x1))
-    angles = [angle for angle in angles if abs(angle) < max_skew_rad]
+        raw_angle = np.arctan2(y2 - y1, x2 - x1)
+        angles.append(min(raw_angle, np.pi / 2 - raw_angle))
+    angles = [angle for angle in angles if (abs(angle) < max_skew_rad)]
+    nonzero = list(filter(lambda x: x != 0, angles))
 
-    if len(angles) < min_nlines:
-        return 0
+    # empirically found this ad hoc approach to work
+    robust_avg = (np.mean(angles) + np.mean(nonzero) + np.median(nonzero)) / 3
+    # slightly lower alternative:
+    # robust_avg = (np.mean(angles) + np.mean(nonzero) + np.median(angles) + np.median(nonzero)) / 4
 
-    return np.rad2deg(np.median(angles))
+    if robust_avg < min_skew_rad or min(len(angles), len(nonzero)) < min_nlines:
+        return 0.0
+    return np.rad2deg(robust_avg)
 
 
 def rotate_straight(im: np.array, skew_angle: int) -> np.array:
     h, w = im.shape[:2]
     center = (w // 2, h // 2)
-    
+
     M = cv2.getRotationMatrix2D(center, skew_angle, 1.0)
-    
-    rotated = cv2.warpAffine(
-        im, M, (w, h), flags=cv2.INTER_CUBIC, borderMode=cv2.BORDER_REPLICATE
-    )
-    
+
+    rotated = cv2.warpAffine(im, M, (w, h), flags=cv2.INTER_CUBIC, borderMode=cv2.BORDER_REPLICATE)
     return rotated
 
 
@@ -43,6 +45,7 @@ def deskew_image(image: np.array, verbose=False) -> np.array:
     skew_angle = detect_angle(image)
     if verbose:
         print(f"Skew angle: {skew_angle}")
-    deskewed = rotate_straight(image, skew_angle)
-    return deskewed
-    
\ No newline at end of file
+    if skew_angle:
+        deskewed = rotate_straight(image, skew_angle)
+        return deskewed
+    return image