  
  class Detect(Detector):
      """ CV2 DNN detector for face recognition """
      def __init__(self, **kwargs):
          model_filename = ["resnet_ssd_v1.caffemodel", "resnet_ssd_v1.prototxt"]
          super().__init__(git_model_id=git_model_id, model_filename=model_filename, **kwargs)
          self.parent_is_pool = True
          self.target = (300, 300)  # Doesn't use VRAM
          self.vram = 0
 
</s> remove         super().__init__(model_filename=model_filename, **kwargs)
 </s> add         super().__init__(git_model_id=git_model_id, model_filename=model_filename, **kwargs) </s> remove         super().__init__(model_filename=model_filename, **kwargs)
 </s> add         super().__init__(git_model_id=git_model_id, model_filename=model_filename, **kwargs) </s> remove         super().__init__(model_filename=model_filename, **kwargs)
 </s> add         super().__init__(git_model_id=git_model_id, model_filename=model_filename, **kwargs)
        git_model_id = 4
  
  class Detect(Detector):
      """ CV2 DNN detector for face recognition """
      def __init__(self, **kwargs):
        git_model_id = 4
          model_filename = ["resnet_ssd_v1.caffemodel", "resnet_ssd_v1.prototxt"]
          super().__init__(git_model_id=git_model_id, model_filename=model_filename, **kwargs)
          self.parent_is_pool = True
          self.target = (300, 300)  # Doesn't use VRAM
          self.vram = 0
keep keep keep add 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 
plugins/extract/detect/cv2_dnn.py