Try using U-net segmentation.
Awesome! Did you guys manage to get this working?
Also, do you have any thoughts on applying this to a new dataset and roughly how much training data you’d need to annotate?
Any update on Mask R-CNN code?
I found AffordanceNet code can do multiclass instance segmentation, but they only used VGG16.
Hey, did you implement the Mask R-CNN in PyTorch? Is there a good PyTorch implementation for it on github?
We are actually trying to use the following repository https://github.com/matterport/Mask_RCNN
What do you think about?
Any progress to implement it here?
I have been using that. I really like the notebooks and the examples using simple shapes as this allows you to experiment with small data. It definitely works. There is an existing port to pytorch but it is not working for training. Also they have not converted the notebooks and shapes; and have moved a lot of stuff around. I am still trying to understand all the different parts of maskRCNN but using both these projects to help me do that.