              j_min_score = i + 1
              for j in range(i + 1, len(img_list)):
                  f1encs = img_list[i][1]
                  f2encs = img_list[j][1]
                  if f1encs and f2encs:
                      score = face_recognition.face_distance(f1encs[0],
                                                             f2encs)[0]
                  else:
                      score = float("inf")
  
                  if score < min_score:
                      min_score = score
                      j_min_score = j
              (img_list[i + 1],
               img_list[j_min_score]) = (img_list[j_min_score],
 
</s> remove                     reference_groups[current_best[0]].append(f1encs[0])
 </s> add                     reference_groups[current_best[0]].append(f1encs) </s> remove                     except TypeError:
                        score = float("inf")
                    except ZeroDivisionError:
 </s> add                     except (TypeError, ValueError, ZeroDivisionError): </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         global INSTALL_FAILED
 </s> add         global INSTALL_FAILED  # pylint:disable=global-statement
                score = self.vgg_face.find_cosine_similiarity(f1encs, f2encs)
              j_min_score = i + 1
              for j in range(i + 1, len(img_list)):
                  f1encs = img_list[i][1]
                  f2encs = img_list[j][1]
                score = self.vgg_face.find_cosine_similiarity(f1encs, f2encs)
                score = self.vgg_face.find_cosine_similiarity(f1encs, f2encs)
                score = self.vgg_face.find_cosine_similiarity(f1encs, f2encs)
                score = self.vgg_face.find_cosine_similiarity(f1encs, f2encs)
                score = self.vgg_face.find_cosine_similiarity(f1encs, f2encs)
                score = self.vgg_face.find_cosine_similiarity(f1encs, f2encs)
                  if score < min_score:
                      min_score = score
                      j_min_score = j
              (img_list[i + 1],
               img_list[j_min_score]) = (img_list[j_min_score],
keep keep keep keep replace replace replace 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