Hello Anmolpreet, I like the idea, also are you aware of https://github.com/Netflix/vmaf? <https://github.com/Netflix/vmaf?> I really like what Netflix put together.
Thanks, Marcus > On 13. Mar 2021, at 17:16, Ryan Curtin <[email protected]> wrote: > > Hi Anmolpreet, > > These sound like nice ideas. It seems likely to me that it would be > possible to implement more than one of these in the summer, but also you > should be sure to think about example usages: if we have many different > quality metrics, that is great, but what is maybe more important to > drive users to them is coherent and clear examples demonstrating their > usage. So you may want to ensure that documentation and examples are > part of the plan also. :) > > I hope this is helpful! I'm not deeply involved with #2294, so others > may have other comments too. > > Thanks! > > Ryan > > On Sat, Mar 13, 2021 at 11:55:22PM +0530, Anmolpreet Singh wrote: >> Hello all! >> >> >> >> Being with MLpack community for some time I realized a few ideas which can >> be implemented during period of GSOC 2021. Taking into consideration the >> shorter time this year I want to propose the following idea of >> implementing some useful metrics of ML as a GSOC 2021 summer project. >> >> >> >> The structural similarity index measure (SSIM) is a method for predicting >> the perceived quality of images or measuring the similarity between 2 >> images considering the structural information. It has good applications in >> image compression (checking quality of compressed image), image >> restoration and pattern recognition. I think it will be some interesting >> stuff to add in MLpack, as it is an important part of image processing. >> Also, its need is highlighted from the issue #2294(Addition of essential >> metrics only) which is pending due to issues in implementation. So, it >> will be good if is done in an organized way under guidance of mentors. I >> have also gone through a couple of recent research papers regarding >> improvements in this. >> >> >> >> PSNR is another image quality metric which has wide use in digital image >> processing. I feel that Metrics like these which have tremendous use will >> fit good in MLpack. Also, discussion will bring more metrics into >> consideration. >> >> >> >> In addition, I may also add metrics like Top K accuracy and some other >> needful metrics (suggestions are welcomed) which may help in evaluating >> the performance of various models. Recently, I have done a data science >> project (chat-bot using NLP) and planning to continue my journey with >> this idea. >> >> >> >> Any feedback or suggestion for these ideas will be really helpful for >> further planning this according to the discussion. >> >> Regards, >> >> Anmolpreet Singh >> >> > >> _______________________________________________ >> mlpack mailing list >> [email protected] >> http://knife.lugatgt.org/cgi-bin/mailman/listinfo/mlpack > > > -- > Ryan Curtin | "We need some time for some things to happen!" > [email protected] | - Bells > _______________________________________________ > mlpack mailing list > [email protected] > http://knife.lugatgt.org/cgi-bin/mailman/listinfo/mlpack
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