                      # The try-catch block is to handle the first face that gets
                      # processed, as the first value is None.
                      try:
                          score = self.get_avg_score_faces(f1encs, references)
                      except TypeError:
                          score = float("inf")
                      except ZeroDivisionError:
                          score = float("inf")
                      if score < current_best[1]:
                          current_best[0], current_best[1] = key, score
  
                  if current_best[1] < min_threshold:
 
</s> remove                     reference_groups[current_best[0]].append(f1encs[0])
 </s> add                     reference_groups[current_best[0]].append(f1encs) </s> remove                 if f1encs and f2encs:
                    score = face_recognition.face_distance(f1encs[0],
                                                           f2encs)[0]
                else:
                    score = float("inf")

 </s> add                 score = self.vgg_face.find_cosine_similiarity(f1encs, f2encs) </s> remove             score = face_recognition.face_distance(f1encs, f2encs)[0]
 </s> add             score = self.vgg_face.find_cosine_similiarity(f1encs, f2encs) </s> remove     @staticmethod
    def get_avg_score_faces(f1encs, references):
 </s> add     def get_avg_score_faces(self, f1encs, references): </s> remove                     reference_groups[len(reference_groups)] = img_list[i][1]
 </s> add                     reference_groups[len(reference_groups)] = [img_list[i][1]]
                    except (TypeError, ValueError, ZeroDivisionError):
                      # The try-catch block is to handle the first face that gets
                      # processed, as the first value is None.
                      try:
                          score = self.get_avg_score_faces(f1encs, references)
                    except (TypeError, ValueError, ZeroDivisionError):
                    except (TypeError, ValueError, ZeroDivisionError):
                    except (TypeError, ValueError, ZeroDivisionError):
                          score = float("inf")
                      if score < current_best[1]:
                          current_best[0], current_best[1] = key, score
  
                  if current_best[1] < min_threshold:
keep keep keep keep replace replace replace keep keep keep keep keep
 Remove dlib (#725)

* Sort to vgg_face. Remove Face Recognition requirements

* Remove dlib components from setup.py

* Remove dlib from Windows Installer script

* Remove dlib and cmake from requirements.txt

* Update INSTALL.md to remove all dlib requirements

* Remove dlib and cmake from dockerfiles

* Windows installer. Output cli to details Window. Setup.py bugfix

* Skip FaceFilter if invalid paths passed in 
tools/sort.py