Hi all, not sure if this is the correct place to ask this but hopefully someone can shine a light on this.
I started off by creating a classifier with Pytorch based on resnet50.
Following this, I created a separate object detection model using detectron2 using "COCO-Detection/faster_rcnn_R_101_FPN_3x.yaml" as my pretrained model.
I want to know if there is a way to use the previous classification model I have already created as the base for my object detection model. Am I just thinking about this wrong? Is there a better way to do what I am trying to do?
Further context: there are multiple classified images for classes but only one of the classes has segmented data available (with the masks and bbox). Eventually, I would like to be in a position where all classes can be detected by a camera in real-time with bounding boxes however the data is not there currently. Please let me know if any other approaches should be considered/investigated.