ID: 5d89f44da0171346e315e540

Monet Style GAN

by Deepak Mangla

Automatically converts images to Monet Style paintings with the generative AI.


Contains Dockerfile Ā This model contains Dockerfile.


License: BSD 2

Tags: CycleGAN GAN painting Monet Style

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?

Want to paint like the famed artist Monet? Relax and let AI do this for you !

How to use?

Using pip Prerequisites - cuda 10.1 and python 3.6

  • Install all requirements with command pip install -r requirements.txt.
  • Put one or more 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 Monet -f Dockerfile . && docker run -it Monet
  • Run python src/run.py -- input Input --output Output .

Voila ! Images have been converted to Monet style paintings and images have been stored in 'Output' directory.

Stats:

CPU inference time - 0.96 s. GPU inference time - 0.036 s.

Tested on:

  • python 3.5
  • ubuntu 16.04
  • cuda 10.1

Author View Profile


Deepak Mangla
Faridabad, India
Level 25 34010 XP

1266 Profile
Views

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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