diff --git a/secure_pixelation/__main__.py b/secure_pixelation/__main__.py
index cc4b6cd..b8aadd4 100644
--- a/secure_pixelation/__main__.py
+++ b/secure_pixelation/__main__.py
@@ -4,4 +4,4 @@ from .detect_humans import detect_humans
 def cli():
     print(f"Running secure_pixelation")
 
-    detect_humans("assets/human_detection/humans.png")
+    detect_humans("assets/human_detection/rev1.png")
diff --git a/secure_pixelation/detect_humans.py b/secure_pixelation/detect_humans.py
index f029e92..02a3c7e 100644
--- a/secure_pixelation/detect_humans.py
+++ b/secure_pixelation/detect_humans.py
@@ -159,6 +159,9 @@ def detect_human_parts(human: dict, face_padding: int = 20):
         # indices of the points that seem to be likely correct
         success_points = []
         for i in range(5):
+            if np.sum(original_points[i]) == 0:
+                continue
+
             s_count = 0
             for j in range(5):
                 d = np.abs(optimized_distances[i][j])
@@ -238,18 +241,18 @@ def detect_human_parts(human: dict, face_padding: int = 20):
         for point in clean_points:
             cv2.circle(image, (int(point[0]), int(point[1])), 4, color, -1)
 
-
-        print("\nOriginal points:")
-        print(original_points)
-        print("\nOriginal pairwise distances:")
-        print(linearize_pairwise_distances(original_points, relative_face_matrix))
-        print(f"Optimized rotation vector (axis-angle): {rotation_vector}")
-        print("\nOptimized points after rotation:")
-        print(optimized_points)
-        print("\nOptimized pairwise distances:")
-        print(optimized_distances)
-        print(success_points)
-        print(clean_points)
+        if valid_face:
+            print("\nOriginal points:")
+            print(original_points)
+            print("\nOriginal pairwise distances:")
+            print(linearize_pairwise_distances(original_points, relative_face_matrix))
+            print(f"Optimized rotation vector (axis-angle): {rotation_vector}")
+            print("\nOptimized points after rotation:")
+            print(optimized_points)
+            print("\nOptimized pairwise distances:")
+            print(optimized_distances)
+            print(success_points)
+            print(clean_points)