Hey Marcus, I agree that we should focus on one topic only, I am more interested in Segmentation Models.
I started implementing SegNet(https://github.com/mlpack/models/issues/54) but as UpSampling Layer is not implemented in mlpack I got stuck. As you can see in the discussion said that they will implement of the layer is in progress and I think soon we will know the status. Also, I did some more reading regarding Segmentation Models, I think reading survey papers on this topic would be a better option as by that we can analyze the speed and requirements of the model and then can implement those which provides better timings. What do you think? I read this article( https://medium.com/@arthur_ouaknine/review-of-deep-learning-algorithms-for-image-semantic-segmentation-509a600f7b57 ) [image: image.png] I think it would be better to decide the models now, once decided we can start focusing on Model Implementation & Visualization. Regards. Gopi M Tatiraju On Sun, Mar 1, 2020 at 11:54 PM Marcus Edel <[email protected]> wrote: > Hello Gopi, > > Regarding the proposal are there any specific models you have in mind? > > As mentioned on the issue itself, I would start with a model that provides > fast > timings for the CPU and GPU as well, mobilenet or squeezenet are two > examples. > Personally, I would focus on a single topic, so either object detection or > segmentation, rather have one polished model instead of two that are okay. > > About the visualize part, the cool thing about the models repo is, we > don't have > to care so much about dependencies, so if you think OpenCV is the best > option, > fine with me. > > Thanks, > Marcus > > On 28. Feb 2020, at 15:25, Gopi Manohar Tatiraju <[email protected]> > wrote: > > Hey, > Regarding adding more models in Mlpack, you are already familiar with my > basic idea. I have already started working on it and by now I have a good > idea about the functionality and architecture of Mlpack library. > > https://github.com/mlpack/models/issues/54 > > Regarding the proposal are there any specific models you have in mind? I > am thinking about models on Image Segmentation and Detection. > > Atleast two models which can be implemented directly without adding any > new layer in Mlpack and remaining by adding new layers throughout the > library so that they can be used for future implementations as well > increasing the functionality of the library. This will also asure that we > will be implementing atleast 2 models as creating the architecture only > using Mlpack's already implemented functionality will be a bit easier than > to implement models and layers. > > Also I think we need a separate module to visualize these algorithms, we > can do that using OpenCV. This will be very helpful as image processing is > only as useful if we can visualize it. > > What are your views? > > Project: > https://github.com/mlpack/mlpack/wiki/SummerOfCodeIdeas#application-of-ann-algorithms-implemented-in-mlpack > Mentors: Marcus Edel, Sumedh Ghaisas, Shikhar Jaiswal > Reagrds > > Gopi M Tatiraju > [email protected] > https://github.com/heisenbuug > _______________________________________________ > mlpack mailing list > [email protected] > http://knife.lugatgt.org/cgi-bin/mailman/listinfo/mlpack > > >
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