计算机毕业设计：基于深度学习的图像风格转换系统(Pytoch)，保证可靠运行，附赠计算机答辩PPT模板

# Fast Neural Style Transfer in PyTorch <p align="center"> <img src="assets/zurich.jpg" width="900"\> </p> PyTorch implementation of [Fast Neural Style Transfer](https://cs.stanford.edu/people/jcjohns/eccv16/) ([official Lua implementation](https://github.com/jcjohnson/fast-neural-style)). I have made some trained models available [here](https://drive.google.com/drive/folders/1aRD6zakhcDImN2Y54qAT6f4801iLcCLB?usp=sharing). ## Train ``` python3 train.py --dataset_path <path-to-dataset> \ --style_image <path-to-style-image> \ --epochs 1 \ --batch_size 4 \ --image_size 256 ``` <p align="center"> <img src="assets/celeba_mosaic.gif" width="400"\> </p> <p align="center"> Figure: Training progress over the first 10,000 batches. </p> ## Test on Video ``` python3 test_on_video.py --video_path <path-to-video> \ --checkpoint_model <path-to-checkpoint> \ ``` <p align="center"> <img src="assets/stylized-celtics.gif" width="400"\> </p> ## Test on Image ``` python3 test_on_image.py --image_path <path-to-image> \ --checkpoint_model <path-to-checkpoint> \ ```