Open ahundt opened 7 years ago
Hey! Yes, I would be happy to Collab, thanks for bringing these to my attention, I'm not quite familiar with this repo, by Upstream you mean that it will be merged into Keras sometime soon?
I will look into this / your comments, let me know if there is one specific one that's hot-burning I can look at for you also.
See I realized that in terms of the model, my previous implementation of the SegNet with further complexity can do wonders.
However, at the meantime, I'm implementing Mask R-CNN, but I want to replicate the result this time around 😄 (hopefully)
I'm running into 2 problems, 1. I can't fit the model into memory 😄 (I think switching backend to TF all the sudden is causing some trouble) and 2ndly, I don't know how to create this custom ROI-Align thingy from the paper, which is aligning 2 tasks Pixel-wise loss.
All in all, if that works out :), I can guarantee better results for same tasks.
PS: I just looked at (https://github.com/farizrahman4u/keras-contrib/issues/63)
OH and also, the paper has a little tiny mistake on the Diagram, keep that in mind for calculating the Param m, which the growth rate.
keras-contrib is where new functionality now goes for Keras until it is ready for prime time: https://github.com/fchollet/keras/blob/master/CONTRIBUTING.md#pull-requests
Kept replies numbered below so we can refer back to them, the best version of the DenseNetFCN model code is in ahundt/keras-contrib with the densenet-atrous branch, and Keras-FCN.
The most hot burning of any item is (4), since I've got evidence it works in Keras-FCN with ResNets, but this is not DenseNetFCN specific. I'd say second most burning which is specific for the tiramisu DenseNetFCN network might be (6a) + (1) which are both easy steps.
A lot of good stuff here, i will get to it tonight : )
Hello, Excuse me, I want to know about the file "fc-densenet-model.py", Does it work or not??
Thanks :)
Might you be interested in a pull request of this code to the official keras-contrib repository which is the upstream source for Keras, and has a DensenetFCN implementation?
These keras-contrib issues are also relevant to this repository:
Keras-FCN, which I was planning to adapt for a merge into keras-contrib also has a SegDataGenerator implementation with some of the features you are looking for in your comments, plus additional models and experimental support for coco.
I figured it might be worth collaborating because it appears we are working on the same thing (training DenseNetFCN), and both running into the same accuracy limitations even with independent implementations.