Awesome
Cartoonizer
Convert images and videos into a cartoon!
The webapp is deployed here - https://cartoonize-lkqov62dia-de.a.run.app
<div style="text-align:center"><img height="100" alt="Powered by Algorithmia" style="border-width:0" src="static/sample_images/algorithmia.jpeg" /></div>You can find a writeup on this webapp's architecture here!
Contents
Prerequisites for Google Cloud and Algorithmia
These are important steps if you want to leverage Google buckets, signed URLs and Algorithmia's platform. Skip this if you want to run locally / colab.
Cloud Run authentication
To use any functionalities pertaining to Google Cloud, you'll need a global authentication file (JSON). You can obtain this JSON by following the steps given here - Getting started with authentication
After you get the JSON file, rename it to token.json
(so that it's compatible with the codebase).
Set the environment variable in your terminal -
export GOOGLE_APPLICATION_CREDENTIALS="/path/to/token.json"
Notes:
- You can set it permanently by adding this line to
~/.bashrc
. Dockerfile
already includes the setting of this particular environment variable. :)
Algorithmia
We used the Serveless AI Layer product of Algorithmia for inference on videos. To learn more on how to deploy your model in Algorithmia, check here - https://algorithmia.com/developers
Installation
Application tested on:
- python 3.7
- tensorflow 2.1.0
- tf_slim 1.1.0
- ffmpeg 3.4.8
- Cuda version 10.1
- OS: Linux (Ubuntu 18.04)
Using Docker
The easiest way to get the webapp running is by using the Dockerfile:
cd
into the root directory and build the image
docker build -t cartoonize .
Note: Set the appropriate values in config.yaml
before building the image.
- Run the container by exposing the appropriate ports
docker run -p 8080:8080 cartoonize
Using virtualenv
- Make a virtual environment using
virutalenv
and activate it
virtualenv -p python3 cartoonize
source cartoonize/bin/activate
- Install python dependencies
pip install -r requirements.txt
- Run the webapp. Be sure to set the appropriate values in
config.yaml
file before running the application.
python app.py
Using Google Colab
- Clone the repository using either of the below mentioned way:
-
Using Command:
- Create a new Notebook in Colab and in the cell execute the below command.
! git clone https://github.com/experience-ml/cartoonize.git
Note: Don't forget to add
!
at the beginning of the command -
From Colab User Interface
-
Open Colab
└── File
└── Open Notebook
└── Github
└── paste the Url of the repository
Note : Before running the application change the runtime to GPU for processing videos but you for images CPU shall also work just fine.
Runtime
└── Change runtime type
└── Select GPU
-
After cloning the repository navigate to the
/cartoonize
using below command in the notebook cell:%cd cartoonize
-
Run the below commands in the notebook cell to install the requirements.
!pip install -r requirements.txt
-
In config.yaml file set:
colab-mode: true
-
Launch the flask app on ngrok
!python app.py
Note : Sample Google Colab Notebook for reference
Sample Image and Video
Emma Watson Cartoonized
<img alt="Emma Watson Cartoonized" style="border-width:0" src="static/sample_images/twitter_image.png" />Youtube Video of Avenger's Bar Scene Cartoonized
License
-
Copyright © Cartoonizer (Demo webapp)
-
Authors: Niraj Pandkar and Tejas Mahajan.
-
Licensed under the CC BY-NC-SA 4.0
-
Commercial application is prohibited by license
-
-
Copyright (C) Xinrui Wang, Jinze Yu. (White box cartoonization)
- All rights reserved.
- Licensed under the CC BY-NC-SA 4.0
- Also, Commercial application is prohibited license (https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode).