/StyleTransferWithCatalyst

This repository shows style transfer in realtime experiment with catalyst deep learning framework

Primary LanguagePythonApache License 2.0Apache-2.0

Style transfer with catalyst

Catalyst logo

This repository shows experiment in realtime style transfer with catalyst deep learning framework. The experiment is based on article Perceptual Losses for Real-Time Style Transfer and Super-Resolution

Examples


Usage

  1. Install dependencies: pip3 install torch==1.6.0 catalyst==20.8.2 numpy tensorflow==2.0.0 tensorboard

    Attention: Catalyst don't have guaranteed backward compatibility, please use only specified version.

  2. Configure experiment:
    Fill all fields marked by "{SPECIFY}" tag in config.yml

  3. Run training:
    catalyst-dl run --config config.yml --verbose
    Well recommendation is to install https://github.com/NVIDIA/apex and use more than one GPU. Catalyst provides multi-GPU and distributed training "out-the-box"

  4. Inference:
    See infer_catalyst.py to find details.

  5. Ready models:
    You can find weights for 512x512 ImageTransformer in ./models