Hi, Thank you for producing this repository. It is very impressive that you are able to achieve these results with such small sample size.
I'd like to train a similar model on my dataset, which includes only three classes, but the object I want to detect is very difficult to see (it's very small and moves quickly and sporadically). I need to use multiple annotated videos for each class, but in the Davis dataset there is only one video for each class. How could I use multiple videos for each class instead?
Also, since the object I'm looking for is very small and hard to see, could I provide some videos where there is no object at all (the segmentation mask would be blank). I'm not clear on how I would do this given the current configuration.
Hi, Thank you for producing this repository. It is very impressive that you are able to achieve these results with such small sample size. I'd like to train a similar model on my dataset, which includes only three classes, but the object I want to detect is very difficult to see (it's very small and moves quickly and sporadically). I need to use multiple annotated videos for each class, but in the Davis dataset there is only one video for each class. How could I use multiple videos for each class instead? Also, since the object I'm looking for is very small and hard to see, could I provide some videos where there is no object at all (the segmentation mask would be blank). I'm not clear on how I would do this given the current configuration.