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Cartoonized digital images using 4 pre trained CartoonGAN models and tensorflow improving model performance adopting image masking with openCV and nearest neighbor interpolation algorithm

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Emoate

Website that converts user-uploaded images into cartoon forms using 4 pre trained CartoonGAN models and improving model performance through image masking and nearest neighbor interpolation.

Setup

The first thing to do is to clone the repository:

$ git clone https://github.com/leslie33kim/emoate.git
$ cd pragmatic

Create a virtual environment to install dependencies in and activate it:

$ virtualenv2 --no-site-packages env
$ source env/bin/activate

Then install the dependencies:

(env)$ pip install -r requirements.txt

Note the (env) in front of the prompt. This indicates that this terminal session operates in a virtual environment set up by virtualenv2.

Once pip has finished downloading the dependencies:

(env)$ cd project
(env)$ python manage.py runserver

And navigate to http://127.0.0.1:8000/emoate/.

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Cartoonized digital images using 4 pre trained CartoonGAN models and tensorflow improving model performance adopting image masking with openCV and nearest neighbor interpolation algorithm

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