yuulind/pix2pix-sar2rgb

Pix2Pix SAR To RGB

yuulind/pix2pix-sar2rgb

• This is a Pix2Pix CGAN implementation for translating Synthetic Aperture Radar (SAR) images to Optical (RGB) images.
• For more information on code, please check GitHub Repo
• The demo: yuulind/sar2rgb
• Includes checkpoints from epoch: 180, 265, 295
• Example outputs

Model Details

Model Description

This is custom implementation of pix2pix architecture in PyTorch. The code can found in GitHub Repo

The official lua implementaion: GitHub Repo The official PyTorch implementation GitHub Repo

• Model type: Image to Image Translation
• BASELINE FID SCORE is between 30 and 40
• Baseline score is calculated by randomly sampling two sets from real images and comparing the them.

Number	Name	Model Type	Description	Link to Model File
1	pix2pix_gen_180.pth	Generator	Pix2Pix generator with transpose convolution, 180 epochs. FID score is 185.04	pix2pix_gen_180.pth
2	pix2pix_gen_265.pth	Generator	Pix2Pix generator with transpose convolution, 265 epochs. FID score is 189.81	pix2pix_gen_265.pth
3	pix2pix_gen_295.pth	Generator	Pix2Pix generator with transpose convolution, 295 epochs. FID score is 187.73	pix2pix_gen_295.pth
4	pix2pix_disc_180.pth	Discriminator	Pix2Pix discriminator from epoch 180, with transpose convolution generator.	pix2pix_disc_180.pth
5	pix2pix_disc_265.pth	Discriminator	Pix2Pix discriminator from epoch 265, with transpose convolution generator.	pix2pix_disc_265.pth
6	pix2pix_disc_295.pth	Discriminator	Pix2Pix discriminator from epoch 295, with transpose convolution generator.	pix2pix_disc_295.pth

Loss Graphs

• Discriminator vs Epoch
• Generator Overall Loss vs Epoch
• Generator GAN Loss vs Epoch
• Generator L1 Loss vs Epoch

Model Sources

• Repository: GitHub Repo
• Paper: arxiv:1611.07004
• Official implementation: GitHub Repo

Uses

Converts SAR images to Optical (RGB) images