Skip to content

This project uses a conditional generative adversarial network (cGAN) named Pix2Pix for the Image to image translation task.

Notifications You must be signed in to change notification settings

hrithickcodes/pix2pix

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

25 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Google Satelite Image to Streetmap Image translation using Pix2Pix GAN

The Pix2Pix GAN is a general approach for image-to-image translation. It is based on the conditional generative adversarial network, where a target image is generated, that is conditioned on a given input image. The idea of Pix2Pix GAN was proposed in this paper. According to the paper, the model not only learn the mapping from source image to target image, but also learn a loss function to train this mapping.

Network Architecture

The generator is a modified U-net model, it takes an RGB image as input and then tries to map it to another RGB image of the same shape. The discriminator is a PatchGan and which outputs a 30x30 matrix, which is then used to calculate the adversarial loss.

Dataset

The dataset can be downloaded from Kaggle by using this link. After downloading the dataset extract it to the data/dataset folder.

Hyperparameters

source_images = 1096
target_images = 1096
IMAGE_HEIGHT = 256
IMAGE_WIDTH = 256
IMAGE_CHANNEL = 3
DISCRIMINATOR_LEARNING_RATE = 0.0002
GENERATOR_LEARNING_RATE = 0.0002
BATCH_SIZE = 1
EPOCHS = 180
BETA1 = 0.5
BETA2 = 0.999
WEIGHT_INIT_STDDEV = 0.02

Results

Acknowledgment

This playlist helped me a lot.

About

This project uses a conditional generative adversarial network (cGAN) named Pix2Pix for the Image to image translation task.

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published