                                "min_max": (0.01, 0.99),
                                "rounding": 2,
                                "type": float,
                                "dest": "ref_threshold",
                                "default": 0.6,
                                "help": "Threshold for positive face recognition. For use with "
                                        "nfilter or filter. Lower values are stricter."})
          argument_list.append({"opts": ("-n", "--nfilter"),
                                "action": FilesFullPaths,
                                "filetypes": "image",
 
</s> remove                                       "nfilter or filter. Lower values are stricter."})
 </s> add                                       "nfilter or filter. Lower values are stricter. NB: Using "
                                      "face filter will significantly decrease extraction speed."}) </s> remove                               "help": "Reference image for the persons you do "
                                      "not want to process. Should be a front "
                                      "portrait. Multiple images can be added "
                                      "space separated"})
 </s> add                               "help": "Reference image for the persons you do not want to "
                                      "process. Should be a front portrait with a single person "
                                      "in the image. Multiple images can be added space "
                                      "separated. NB: Using face filter will significantly "
                                      "decrease extraction speed."}) </s> remove                               "help": "Reference images for the person you "
                                      "want to process. Should be a front "
                                      "portrait. Multiple images can be added "
                                      "space separated"})
 </s> add                               "help": "Reference images for the person you want to process. "
                                      "Should be a front portrait with a single person in the "
                                      "image. Multiple images can be added space separated. NB: "
                                      "Using face filter will significantly decrease extraction "
                                      "speed."}) </s> remove         """ Check Face
            we could use detected landmarks, but I did not manage to do so.
            TODO The copy/paste below should help """
 </s> add         """ Check the extracted Face """

                              "default": 0.4,
                                "min_max": (0.01, 0.99),
                                "rounding": 2,
                                "type": float,
                                "dest": "ref_threshold",
                              "default": 0.4,
                                "help": "Threshold for positive face recognition. For use with "
                                        "nfilter or filter. Lower values are stricter."})
          argument_list.append({"opts": ("-n", "--nfilter"),
                                "action": FilesFullPaths,
                                "filetypes": "image",
keep keep keep keep replace keep keep keep keep keep
 Face filter vgg face (#724)

* Implement extraction pipeline

* Face filter to vgg_face. Resume partial model downloads

* On-the-fly conversion to extraction pipeline

* Move git model ids from get_model to model definition 
lib/cli.py