training on a custom dataset

[surfingnirvana]

Is it possible to train my custom dataset with just a small sample size?

[winfried-ripken]

Sure!
For parametric style transfer you would only need a pair of style and content images like for classical style transfer. Our local parameter prediction task relies on the code for Pix2PixGAN that accepts all kinds of paired image datasets. Let me know if that answered your question!

[surfingnirvana]

If i try to run the parametric style transfer i get an error:

(base) PS C:\neural\wise> python -m parameter_optimization.parametric_styletransfer --effect xdog --content experiments/source/portrait.png --style experiments/target/watercolor_portrait.jpg
Traceback (most recent call last):
File "C:\ProgramData\Anaconda3\lib\runpy.py", line 197, in _run_module_as_main
return _run_code(code, main_globals, None,
File "C:\ProgramData\Anaconda3\lib\runpy.py", line 87, in _run_code
exec(code, run_globals)
File "C:\neural\wise\parameter_optimization\parametric_styletransfer.py", line 109, in
strotss_process(args.content, args.style, effect=effect, preset=preset, cpu=args.cpu)
File "C:\neural\wise\parameter_optimization\parametric_styletransfer.py", line 92, in strotss_process
result = execute_style_transfer(s, t, resize_dim, device="cpu" if cpu else "cuda:0")
NameError: name 'execute_style_transfer' is not defined