  
          end = 0
          for key in tqdm(sorted(self.alignments.alignments.keys()),
                          desc="Compiling"):
              val = self.alignments.alignments[key]
              if not val:
                  continue
              # We should only be normalizing a single face, so just take
              # the first landmarks found
              landmarks = np.array(val[0]["landmarksXY"]).reshape(68, 2, 1)
 
</s> remove         for key in tqdm(sorted(self.alignments.alignments.keys()),
 </s> add         for key in tqdm(sorted(self.alignments.data.keys()), </s> remove         count = sum(1 for val in self.alignments.alignments.values() if val)
 </s> add         count = sum(1 for val in self.alignments.data.values() if val) </s> remove     umeyama_landmarks = cv2.transform(landmarks, mat_umeyama, landmarks.shape)
 </s> add     umeyama_landmarks = cv2.transform(  # pylint: disable=no-member
        landmarks,
        mat_umeyama,
        landmarks.shape)
 </s> remove     # cv2 expects points to be in the form np.array([ [[x1, y1]], [[x2, y2]], ... ]), we'll expand the dim
    landmarks = numpy.expand_dims(landmarks, axis=1)
 </s> add     # cv2 expects points to be in the form
    # np.array([ [[x1, y1]], [[x2, y2]], ... ]), we'll expand the dim
    landmarks = np.expand_dims(landmarks, axis=1)
 </s> remove 
        except Exception as err:
            print("{} not read!".format(self.location))
            print(str(err))
            data = dict()
 </s> add         except IOError as err:
            print("Error: {} not read: {}".format(self.file, err.strerror))
            exit(1)
            val = self.alignments.data[key]
  
          end = 0
          for key in tqdm(sorted(self.alignments.alignments.keys()),
                          desc="Compiling"):
            val = self.alignments.data[key]
              if not val:
                  continue
              # We should only be normalizing a single face, so just take
              # the first landmarks found
              landmarks = np.array(val[0]["landmarksXY"]).reshape(68, 2, 1)
keep keep keep keep replace keep keep keep keep keep
 Fix convert-adjust (#531)

* Add dimensions to alignments + refactor

* Add frame_dims + funcs to DetectFaces. Add alignments lib

* Convert Adjust working

* Refactor and tidy up 
tools/lib_alignments/jobs.py