# AdaIN-pytorch
**Repository Path**: shzgamelife/AdaIN-pytorch
## Basic Information
- **Project Name**: AdaIN-pytorch
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: GPL-3.0
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No
## Statistics
- **Stars**: 0
- **Forks**: 0
- **Created**: 2022-01-20
- **Last Updated**: 2022-01-20
## Categories & Tags
**Categories**: Uncategorized
**Tags**: 计算机视觉
## README
# AdaIN-pytorch
PyTorch implementation of "Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization" by Xun Huang, Serge Belongie. [arxiv](https://arxiv.org/abs/1703.06868).
## 0. References
- [irasin/Pytorch_AdaIN](https://github.com/irasin/Pytorch_AdaIN/)
## 1. Set up and train model
### 1.1 install requirements
`pip install -r requitements.txt`
### 1.2 get the datasets and unzip them to desired location
- COCO: https://cocodataset.org/#download
- WikiArt: https://www.kaggle.com/c/painter-by-numbers/data
### 1.3 Train model
- to start training:
`python main.py train path/to/coco path/to/wikiart [OPTIONS]`
- to change training parameters and options:
`python main.py train --help`
## 2. Style Transfer using pre-trained model
- to run inference:
`python main.py infer [OPTIONS]`
- info on supported options:
`python main.py infer --help`
## 3. Some Results
- All images were resized to 1024x1024 for inference. The 1024x1024 outputs are interpolated to the original size using bilinear interpolation.
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