make all too long errors and warnings one liner. Need to think about …

…precommit error

stitching/cropper.py

@@ -94,11 +94,7 @@ def estimate_largest_interior_rectangle(self, mask):
 
         contours, hierarchy = cv.findContours(mask, cv.RETR_TREE, cv.CHAIN_APPROX_NONE)
         if not hierarchy.shape == (1, 1, 4) or not np.all(hierarchy == -1):
-            raise StitchingError(
-                """Invalid Contour. Run with --no-crop (using the stitch interface),
-                                 crop=false (using the stitcher class) or Cropper(False)
-                                 (using the cropper class)"""
-            )
+            raise StitchingError("Invalid Contour. Run with --no-crop (using the stitch interface), crop=false (using the stitcher class) or Cropper(False) (using the cropper class)")
         contour = contours[0][:, 0, :]
 
         lir = largestinteriorrectangle.lir(mask > 0, contour)

stitching/seam_finder.py

@@ -98,8 +98,7 @@ def blend_seam_masks(
 def colored_img_generator(sizes, colors):
     if len(sizes) + 1 > len(colors):
         warnings.warn(
-            """Without additional colors,
-            there will be seam masks with identical colors""",
+            "Without additional colors, there will be seam masks with identical colors",
             StitchingWarning,
         )
 

stitching/stitcher.py

@@ -280,10 +280,7 @@ class AffineStitcher(Stitcher):
     def initialize_stitcher(self, **kwargs):
         for key, value in kwargs.items():
             if key in self.AFFINE_DEFAULTS and value != self.AFFINE_DEFAULTS[key]:
-                warnings.warn(
-                    f"""You are overwriting an affine default ({key}=
-                    {self.AFFINE_DEFAULTS[key]}) with another value ({value}). Make
-                sure this is intended""",
+                warnings.warn(f"You are overwriting an affine default ({key}={self.AFFINE_DEFAULTS[key]}) with another value ({value}). Make sure this is intended",
                     StitchingWarning,
                 )
         super().initialize_stitcher(**kwargs)

stitching/subsetter.py

@@ -30,11 +30,7 @@ def subset(self, img_names, features, matches):
 
         if len(indices) < len(img_names):
             warnings.warn(
-                """Not all images are included in the final panorama.
-                          If this is not intended, use the 'matches_graph_dot_file'
-                          parameter to analyze your matches. You might want to
-                          lower the 'confidence_threshold' or try another 'detector'
-                          to include all your images.""",
+                "Not all images are included in the final panorama. If this is not intended, use the 'matches_graph_dot_file' parameter to analyze your matches. You might want to lower the 'confidence_threshold' or try another 'detector' to include all your images.",
                 StitchingWarning,
             )
 
@@ -65,13 +61,7 @@ def get_indices_to_keep(self, features, pairwise_matches):
         indices = indices.flatten()
 
         if len(indices) < 2:
-            raise StitchingError(
-                """No match exceeds the given confidence threshold.
-                                 Do your images have enough overlap and common
-                                 features? If yes, you might want to lower the
-                                 'confidence_threshold' or try another
-                                 'detector'."""
-            )
+            raise StitchingError("No match exceeds the given confidence threshold. Do your images have enough overlap and common features? If yes, you might want to lower the 'confidence_threshold' or try another 'detector'.")
 
         return indices