---
# System prepended metadata

title: Style Transfer
tags: [Demi]

---

---
tags: Demi
---
# Style Transfer
---
# fast-style-transfer
https://github.com/lengstrom/fast-style-transfer
## Steps
1. 下載 anaconda
2. 開環境
``` shell=
conda create -n tf-gpu tensorflow-gpu=2.1.0
conda activate tf-gpu
conda install jupyterlab
jupyter lab
```
``` python= 
!pip install moviepy==1.0.2
```

3. fast
``` shell
git clone https://github.com/lengstrom/fast-style-transfer.git
cd fast-style-transfer-master
```
4. 下載訓練好的 models
https://drive.google.com/drive/folders/0B9jhaT37ydSyRk9UX0wwX3BpMzQ?resourcekey=0-Z9LcNHC-BTB4feKwm4loXw
## 改圖而已
``` shell=
mkdir checkpoint # 放 style 的 models*.ckpt
mkdir demi/imgs # 放要改的原圖
mkdir demi/results # 放結果圖
python3.7 evaluate.py --checkpoint checkpoint/scream.ckpt --in-path demi/imgs --out-path demi/results/
```
run.sh
``` shell=
python3.7 evaluate.py --checkpoint checkpoint/la_muse.ckpt --in-path demi/imgs --out-path demi/results/la_muse/
python3.7 evaluate.py --checkpoint checkpoint/rain_princess.ckpt --in-path demi/imgs --out-path demi/results/rain_princess/
python3.7 evaluate.py --checkpoint checkpoint/scream.ckpt --in-path demi/imgs --out-path demi/results/scream/
python3.7 evaluate.py --checkpoint checkpoint/udnie.ckpt --in-path demi/imgs --out-path demi/results/udnie/
python3.7 evaluate.py --checkpoint checkpoint/wave.ckpt --in-path demi/imgs --out-path demi/results/wave/
python3.7 evaluate.py --checkpoint checkpoint/wreck.ckpt --in-path demi/imgs --out-path demi/results/wreck/
```
/bin/sh run.sh
## Train Model
``` shell=
/bin/sh setup.sh
```
---
# Neural style transfer 
https://keras.io/examples/generative/neural_style_transfer/?fbclid=IwAR03SQ3F-cbOzzcfyR4DrS1CgeBACr3lnv2eTrm9WlyfRi0dK82WFkjzUjc