[mlpack] GSOC 21

[Vishwas Chepuri]

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
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