I’d like to add some features to fasterrcnn_resnet50_fpn, for example feature[91]=‘chicken’ and feature[92]=‘frog’, but keep the existing 91 features. Is this possible via transfer learning? All the examples I’ve seen use the pre-trained fasterrcnn_resnet50_fpn, but then train it to only detect a handful of new features, ignoring the existing 91.
If this is possible, could I please get the broad strokes, or some links of how to go about it?
Thanks.