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https://github.com/alvinwan/emotion-based-dog-filter
Real-time Emotion-Based, Snapchat-esque Dog Filter using Computer Vision
https://github.com/alvinwan/emotion-based-dog-filter
adversarial-examples computer-vision dog-filter face-detection face-recognition machine-learning opencv python3 pytorch
Last synced: about 1 month ago
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Real-time Emotion-Based, Snapchat-esque Dog Filter using Computer Vision
- Host: GitHub
- URL: https://github.com/alvinwan/emotion-based-dog-filter
- Owner: alvinwan
- License: apache-2.0
- Created: 2017-12-14T07:28:12.000Z (almost 7 years ago)
- Default Branch: master
- Last Pushed: 2022-06-21T21:08:41.000Z (over 2 years ago)
- Last Synced: 2023-02-27T17:32:57.776Z (over 1 year ago)
- Topics: adversarial-examples, computer-vision, dog-filter, face-detection, face-recognition, machine-learning, opencv, python3, pytorch
- Language: Python
- Homepage: https://dogfilter.glitch.me
- Size: 82.5 MB
- Stars: 8
- Watchers: 1
- Forks: 6
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# [How To Apply Computer Vision to Build an Emotion-Based Dog Filter in Python 3](https://www.digitalocean.com/community/tutorials/how-to-apply-computer-vision-to-build-an-emotion-based-dog-filter-in-python-3)
**Want an in-person tutorial with step-by-step walkthroughs and explanations? See the corresponding AirBnb experience for both beginner and experienced coders alike, at ["Build a Dog Filter with Computer Vision"](http://abnb.me/GFEpWpfUlO)**
This repository includes all source code for the [tutorial on DigitalOcean](https://www.digitalocean.com/community/tutorials/how-to-apply-computer-vision-to-build-an-emotion-based-dog-filter-in-python-3) with the same title, including:
- A real-time filter that adds dog masks to faces on a live feed.
- A dog filter that responds to your emotions. (Couldn't find a pug mask, so I used a cat.) A generic dog for smiling "happy", a dalmation for frowning "sad", and a cat for dropped jaws "surprise".
- Utilities used for portions of the tutorial, such as plotting and advesarial example generation.
- Simple convolutional neural network written in [PyTorch](http://pytorch.org), with pretrained model.
- Ordinary least squares and ridge regression models using randomized features.
created by [Alvin Wan](http://alvinwan.com), December 2017
# Getting Started
> You can setup the repository using Python or view the web demo at [dogfilter.alvinwan.com](https://dogfilter.alvinwan.com)
For complete step-by-step instructions, see the [tutorial on DigitalOcean](https://www.digitalocean.com/community/tutorials/how-to-apply-computer-vision-to-build-an-emotion-based-dog-filter-in-python-3). This codebase was developed and tested using `Python 3.6`. If you're familiar with Python, then see the below to skip the tutorial and get started quickly:
> (Optional) [Setup a Python virtual environment](https://www.digitalocean.com/community/tutorials/common-python-tools-using-virtualenv-installing-with-pip-and-managing-packages#a-thorough-virtualenv-how-to) with Python 3.6.
1. Install all Python dependencies.
```
pip install -r requirements.txt
```
2. Navigate into `src`.
```
cd src
```
3. Launch the script for an emotion-based dog filter:
```
python step_8_dog_emotion_mask.py
```
# How it Works
See the below resources for explanations of related concepts:
- ["Understanding Least Squares"](http://alvinwan.com/understanding-least-squares/)
- ["Understanding Neural Networks"](http://alvinwan.com/understanding-neural-networks/)
## Acknowledgements
These models are trained on a Face Emotion Recognition (FER) dataset curated by Pierre-Luc Carrier and Aaron Courville in 2013, as published on [Kaggle](https://www.kaggle.com/c/challenges-in-representation-learning-facial-expression-recognition-challenge).