Hi Vishwas! I just wanted to say if you decide to go ahead with implementing Inception V3 for the mlpack/models repository, you may find the following PR useful:
Inception V3 Layer <https://github.com/mlpack/mlpack/pull/2848> In this PR, I've implemented various blocks ( except Auxiliary Classifier) in Inception V3 network. All the tests have also been written. Regards Shah Anwaar Khalid On Fri, Mar 26, 2021 at 10:32 PM Vishwas Chepuri < [email protected]> wrote: > Hello everyone! > > I am Vishwas Chepuri, a sophomore at IIT(BHU), Varanasi, India. I have > been getting myself familiar with mlpack for the last couple of months. I > wanted to get some opinions regarding my project proposal and kindly help > me improve it. > > Idea is to implement the following ready to use models, > > 1) VGG16 > > 2) VGG19 > > 3) InceptionV3 > > 4) ResNet50 > > 5) ResNet101 > > For each of the above models, I would like to implement a class following > the class design in the models repo which includes > > the sketch of model with and without FC layers on top of base > architecture, include ImageNet weights for both the models (with and > without FC layers), implement preprocessing function which includes > preprocessing steps with which the above-included weights are trained, > write tests and documentation. > > I have opened a PR #49 (https://github.com/mlpack/models/pull/49) for > VGG16 and VGG19 models, and I am able to get weights using PyTorch-mlpack > Weight Converter ( > https://github.com/kartikdutt18/mlpack-PyTorch-Weight-Translator). > Hopefully, I will complete implementing and including all the > above-mentioned functionalities for these two models before GSOC begins. > > I am excited about this project. Kindly let me know your thoughts on this > idea. Thanks for reading. > > Regards, > > Vishwas Chepuri > > GitHub ID: vstark21 > _______________________________________________ > mlpack mailing list > [email protected] > http://knife.lugatgt.org/cgi-bin/mailman/listinfo/mlpack >
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