ID: 5d89f596a0171346e315e542

Summer to Winter GAN

by Deepak Mangla

Automatically converts summer images to winter images with the generative AI.


Contains Dockerfile Ā This model contains Dockerfile.


License: BSD 2

Tags: CycleGAN Summer to Winter

Ā Model stats and performance
Dataset Used View
Framework PyTorch
OS Used Linux
Publication View
Inference time in seconds per sample.

Screenshots


What is it?

Automatically converts Summer images to winter images with the generative AI.

Usage:

Using pip Prerequisites - cuda 10.1 and python 3.6

  • Install all requirements with command pip install -r requirements.txt.
  • Put one or more summer images in 'Input' folder. (Initially sample images are provided for testing purpose).
  • Run python src/run.py -- input Input --output Output .

Using docker Prerequisites - Docker > 19.03

  • Build docker image and run docker container - docker build -t summ2win -f Dockerfile . && docker run -it summ2win
  • Run python src/run.py -- input Input --output Output .

Voila ! Summer images have been converted to Winter images and have been stored in 'Output' directory.

Stats:

CPU - 0.96 GPU - 0.036

Tested on

  • python 3.5
  • ubuntu 16.04
  • cuda 10.1

Author View Profile


Deepak Mangla
Faridabad, India
Level 25 34010 XP

1302 Profile
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AI wizard who thinks with first principles

I am Deep Learning (Computer Vision) Engineer with specialization in enabling AI on the resource-constrained edge devices. I work on quantizations, pruning and efficient designing and deployment of DL networks. Read my article about Winograd - https://blog.usejournal.com/understanding-winograd-fast-convolution-a75458744ff

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