Art-Style-Transfer-Video

Art style transfer for both images and video written in Tensorflow 2. Preview and save your outputs.

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Art-Style-Transfer-Video

Art style transfer for images and video. Save and resize your outputs. Example artworks included.

Setup

Use your choice of Python 3.7+ virtual environment or conda environment. Then run:

pip install -r requirements.txt

Examples

Find example images to transfer art styles from in art.

Video

python video.py

Note the following arguments, which are all optional:

usage: video.py [-h] [--i I] [--s S] [--u U] [--r R] [--w W] [--f F]

optional arguments:
  -h, --help            show this help message and exit
  --i I, ---img_name I  Image name of the artwork to transfer the style from
                        in the art folder.
  --s S, --src S        Input source. Defaults to 0 for web cam.
  --u U, --url U        URL to the tf hub model.
  --r R, --resolution R
                        Resolution of the smallest dimension of the input.
  --w W, --write W      Whether or not to write the output.
  --f F, --frame_skip F
                        Number of frames to skip between processing.
                        

Image

python img.py [path to input image]

Pass any image preprocessing logic (i.e. blurring) into the preprocess argument as a function. Note that the preprocessing function should return a numpy.ndarray.

Note the following arguments, which are all optional except for src:

usage: img.py [-h] [--i I] [--u U] [--r R] [--w W] src

positional arguments:
  src                   Input image

optional arguments:
  -h, --help            show this help message and exit
  --i I, ---img_name I  Image name of the artwork to transfer the style from
                        in the art folder.
  --u U, --url U        URL to the tf hub model.
  --r R, --resolution R
                        Resolution of the smallest dimension of the input.
  --w W, --write W      Whether or not to write the output.