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Category: Reddit MachineLearning

[R] FoveaBox object detection code is available

https://github.com/taokong/FoveaBox

FoveaBox is an accurate, flexible and completely anchor-free object detection system for object detection framework, as presented in our paper https://arxiv.org/abs/1904.03797: Different from previous anchor-based methods, FoveaBox directly learns the object existing possibility and the bounding box coordinates without anchor reference. This is achieved by: (a) predicting category-sensitive semantic maps for the object existing possibility, and (b) producing category-agnostic bounding box for each position that potentially contains an object.

submitted by /u/taokongcn
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[P] Pytorch Implementation of Autoregressive Language Model

A step-by-step tutorial on how to implement and adapt Autoregressive language model to Wikipedia text.

A pre-trained BERT, XLNET is publicly available ! But, for NLP beginners, It could be hard to use/adapt after full understanding. For them, I covered whole, end-to-end implementation process for language modeling, using unidirectional/bidirectional LSTM network, we already know.

  • – do not use torchtext library !
  • + include trained model file, training logs

I hope that this repo can be a good solution for people who want to have their own language model 🙂

https://github.com/lyeoni/pretraining-for-language-understanding

submitted by /u/lyeoni
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[P] CLI tool to run DL machines on AWS

I created an open source tool to spin up Deep learning EC2 machines with a single command. The goal is to make it easy to use EC2 machines for development without fiddling with the AWS Console, managing SSH keys.

90-second demo of the tool: https://www.youtube.com/watch?v=lXEeteH3-So

Link to the project: https://github.com/narenst/infinity

It takes less than a minute to set up and use your first Deep Learning machine. I would love to hear your feedback 🙂

submitted by /u/narenst
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[D] Detecting when football players take a shot on goal (3DCNN)

www.youtube.com/watch?v=YQ58Sz23PT0

Join Tim Scarfe, Karol Zak, Tess Ferrandez and Hamid Reza Vaezi joze on a discussion of 3D CNNs for action detection (shots) in football games. We explain our baseline approach (2D CNN), interview Hamid and learn some background of 3DCNNS and then go through our new code (C3D pretrained on Sports1M dataset) in detail explaining the results. We didn’t yet try the I3D but expect it to be even better.

This should be of interest to anyone who is interested in learning the basics of action detection in videos.

submitted by /u/timscarfe
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[P] How I made a meme face using ML

video: https://youtu.be/kwpb4TeZguo

repo: https://github.com/Suji04/Meme_with_ML

This is a fun project I made while learning about object detection with haar cascades. Like, everyone, I too like the thug life memes. But to make a meme face of your friend you have to add the pixelated glasses on your own. I wrote a python program that automatically finds the eyes and places the pixelated glasses on them. I first tried with a haar cascade that can find the eyes but that didn’t produce good results after placing the glasses. After that, I tried a face detecting haar cascade. My idea was…I don’t have to find the eyes I just have to know where the eyes lie on the face. I divided the face(a rectangle) into 4 parts by 3 horizontal lines. The eyes generally lie on the 2nd part from the top. So the program just places the glasses on the 2nd part of the face. To my surprise, this simple idea produced better results than the former one!

submitted by /u/nerdy_wits
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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.