Ben-Louis / Deep Image Analogy Pytorch
Licence: mit
A python implementation of Deep-Image-Analogy based on pytorch.
Stars: ✭ 140
Programming Languages
python
139335 projects - #7 most used programming language
Labels
Projects that are alternatives of or similar to Deep Image Analogy Pytorch
Style Transfer.js
👨🎨️ Generate novel artistic images in Node.js
Stars: ✭ 78 (-44.29%)
Mutual labels: style-transfer
Pytorch Neural Style Transfer
Reconstruction of the original paper on neural style transfer (Gatys et al.). I've additionally included reconstruction scripts which allow you to reconstruct only the content or the style of the image - for better understanding of how NST works.
Stars: ✭ 106 (-24.29%)
Mutual labels: style-transfer
Style Transfer
A Keras Implementation of "A Neural Algorithm of Artistic Style"
Stars: ✭ 115 (-17.86%)
Mutual labels: style-transfer
Frostnet
FrostNet: Towards Quantization-Aware Network Architecture Search
Stars: ✭ 85 (-39.29%)
Mutual labels: style-transfer
Fast Style Transfer
TensorFlow CNN for fast style transfer ⚡🖥🎨🖼
Stars: ✭ 10,240 (+7214.29%)
Mutual labels: style-transfer
Aams
Attention-aware Multi-stroke Style Transfer (CVPR2019)
Stars: ✭ 68 (-51.43%)
Mutual labels: style-transfer
Chainer Fast Neuralstyle Models
Models for the chainer fast neuralstyle
Stars: ✭ 132 (-5.71%)
Mutual labels: style-transfer
Style transfer
Data-parallel image stylization using Caffe.
Stars: ✭ 106 (-24.29%)
Mutual labels: style-transfer
Monoculardepth Inference
Inference pipeline for the CVPR paper entitled "Real-Time Monocular Depth Estimation using Synthetic Data with Domain Adaptation via Image Style Transfer" (http://www.atapour.co.uk/papers/CVPR2018.pdf).
Stars: ✭ 115 (-17.86%)
Mutual labels: style-transfer
Adaptive Style Transfer
Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization
Stars: ✭ 85 (-39.29%)
Mutual labels: style-transfer
Neural Style Transfer Papers
✏️ Neural Style Transfer: A Review
Stars: ✭ 1,372 (+880%)
Mutual labels: style-transfer
Stif Indonesia
Implementation of "Semi-Supervised Low-Resource Style Transfer of Indonesian Informal to Formal Language with Iterative Forward-Translation".
Stars: ✭ 79 (-43.57%)
Mutual labels: style-transfer
Neural Painters Pytorch
PyTorch library for "Neural Painters: A learned differentiable constraint for generating brushstroke paintings"
Stars: ✭ 118 (-15.71%)
Mutual labels: style-transfer
Agis Net
[SIGGRAPH Asia 2019] Artistic Glyph Image Synthesis via One-Stage Few-Shot Learning
Stars: ✭ 77 (-45%)
Mutual labels: style-transfer
Linguistic Style Transfer
Neural network parametrized objective to disentangle and transfer style and content in text
Stars: ✭ 106 (-24.29%)
Mutual labels: style-transfer
Deep Learning With Python
Example projects I completed to understand Deep Learning techniques with Tensorflow. Please note that I do no longer maintain this repository.
Stars: ✭ 134 (-4.29%)
Mutual labels: style-transfer
Neural Style Audio Torch
Torch implementation for audio neural style.
Stars: ✭ 130 (-7.14%)
Mutual labels: style-transfer
Sketch To Art
🖼 Create artwork from your casual sketch with GAN and style transfer
Stars: ✭ 115 (-17.86%)
Mutual labels: style-transfer
Deep-Image-Analogy
This project is a python implementation of Deep Image Analogy.https://arxiv.org/abs/1705.01088.
Some results
Requirements
-
python 3
-
opencv3
If you use anaconda, you can install opencv3 by
conda install opencv -
pytorch
See pytorch for installation
Codes in branch "master" works with pytorch 0.4
Codes in branch "pytorch0.3" works with pytorch 0.3
-
cuda (CPU version is not implemented yet)
Usage (demo)
python main.py --resize_ratio 0.5 --weight 2 --img_A_path data/demo/ava.png --img_BP_path data/demo/mona.png --use_cuda True
Acknowledgments
My project acknowledge the official code Deep-Image-Analogy, pytorch, and another pytorch implementation. Especially, thanks for the authors of this amazing algorithm.
Note that the project description data, including the texts, logos, images, and/or trademarks,
for each open source project belongs to its rightful owner.
If you wish to add or remove any projects, please contact us at [email protected].