pt-singan-single-image-gan Inofficial implementation of the paper "SinGAN: Learning a Generative Model from a Single Natural Image " as a project for the Deep Generative Models lecture at TU Darmstadt SS2020.
In order to execute the web application on your local computer, you need to do the following.
Install all packages from the requirements.txt.
Install the RabbitMQ message broker from their website .
Run the RabbitMQ Service, then open a terminal and configure RabbitMQ by entering the following four commands:
rabbitmqctl.bat add_user singan singanrabbitmqctl.bat add_vhost singan_hostrabbitmqctl.bat set_user_tags singan singan_tagrabbitmqctl.bat set_permissions -p singan_host singan ".*" ".*" ".*"
In the project's root directory, go into the folder web, open a terminal here and run python manage.py runserver
to run the Django server.
In the same folder (web) open another terminal and execute the Celery worker process by entering
celery -A web worker --pool=solo -l info
Finally, in your browser, open http://127.0.0.1:8000/ .
How to use without the UI For each of the SinGAN applications, we created an easy-to-use python script that can be run directly from the console by specifying the necessary parameters. All of these scripts have in common that they require either just the run_name of a pretrained SinGAN model or the --not_pretrained flag together with the training image path, the number of scales N and the number of steps per scale. For instance, the following additional command line arguments would train a SinGAN model on the green fern plant image with 8 scales and 2000 steps per scale:
python application.py [...] --not_pretrained --img 5026-green-fern-plant-during-daytime.jpg --N 8 --steps_per_scale 2000 If the --not_pretrained flag is not given but a trained model with the identifier run_name exists, this is used instead.
python sample.py --run_name <String> -- height <int> --width <int> python scale_injections.py --run_name <String> python scale_injections.py --run_name <String> --super_scales <int> Note : You have to additionally provide a training image via --img if you want to train a new model. The paint images are expected to be found in the data/paint subdirectory.
python paint2image.py --run_name <String> --paint 5026_1.jpg python animate.py --run_name <String> --frames <int> --fps <int> --alpha 0.1 --beta 0.9 --start_at_scale <int>
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