PyTorch implementation of "Image-to-Image Translation Using Conditional Adversarial Networks".

Last update: Dec 17, 2022

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Deep Learning pix2pix-pytorch

Overview

pix2pix-pytorch

PyTorch implementation of Image-to-Image Translation Using Conditional Adversarial Networks.

Based on pix2pix by Phillip Isola et al.

The examples from the paper:

Prerequisites

Linux
Python, Numpy, PIL
pytorch 0.4.0
torchvision 0.2.1

Getting Started

Clone this repo:

git clone [email protected]:mrzhu-cool/pix2pix-pytorch.git cd pix2pix-pytorch
Get dataset

unzip dataset/facades.zip
Train the model:

python train.py --dataset facades --cuda
Test the model:

python test.py --dataset facades --cuda

Acknowledgments

This code is a simple implementation of pix2pix. Easier to understand. Note that we use a downsampling-resblocks-upsampling structure instead of the unet structure in this code, therefore the results of this code may inconsistent with the results presented in the paper.

Highly recommend the more sophisticated and organized code pytorch-CycleGAN-and-pix2pix by Jun-Yan Zhu.

Owner

mrzhu

day day up

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