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Add ipynb file for running pretrained networks on Google Colabs #20

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Add ipynb file for running pretrained networks on Google Colabs #20

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Added Google Colab file
MalachiMassey Jan 23, 2021
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Added Google Colabs mention to README.md
MalachiMassey Jan 23, 2021
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4 changes: 4 additions & 0 deletions README.md
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Expand Up @@ -77,6 +77,10 @@ The results are placed in `results/<RUNNING_ID>/*.png`. You can change the locat

You can import the networks in your own Python code using `pickle.load()`. For this to work, you need to include the `dnnlib` source directory in `PYTHONPATH` and create a default TensorFlow session by calling `dnnlib.tflib.init_tf()`. See [run_generator.py](./run_generator.py) and [pretrained_networks.py](./pretrained_networks.py) for examples.

## Running on Google Colabs

stylegan2.ipynb can be used to run pre-trained networks on [Google Colabs](https://colab.research.google.com).

## Preparing datasets

Datasets are stored as multi-resolution TFRecords, similar to the [original StyleGAN](https://github.com/NVlabs/stylegan). Each dataset consists of multiple `*.tfrecords` files stored under a common directory, e.g., `~/datasets/ffhq/ffhq-r*.tfrecords`. In the following sections, the datasets are referenced using a combination of `--dataset` and `--data-dir` arguments, e.g., `--dataset=ffhq --data-dir=~/datasets`.
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