Examples

Run time and cost

This model costs approximately $0.040 to run on Replicate, or 25 runs per $1, but this varies depending on your inputs. It is also open source and you can run it on your own computer with Docker.

This model runs on Nvidia T4 GPU hardware. Predictions typically complete within 3 minutes. The predict time for this model varies significantly based on the inputs.

Readme

Replicate img2img model in the style of Van Gogh

This is an img2img in the style of Van Gogh. It was written in cog format to be push to replicate.com

[Replicate version 3edc1fe] This diffusion model was made from training 58 images of Van Gogh paintings (https://huggingface.co/hazwan/vg-session). It is a mix of portrait and landscape.

This model does not look visually appealing because the original painting is more abstract compared to the Loving Vincent model below which trained on a movie that carefully made in the style of Van Gogh

[Replicate version 76b7599] The diffusion model is from https://huggingface.co/dallinmackay/Van-Gogh-diffusion

cog.yaml specify the dependencies and python libraries

predict.py is to consume input (image and prompt) and run the input through the diffusion model

Cog process

To initialize the directory

cog init

To build locally and do inference to the image balloon.jpg

cog predict -i prompt="vangh, man" -i image=@imgs/man_1.jpg"

Next add credential and push the build to replicate.com

cog login
cog push r8.im/hazxone/img2img-vg

Inference process

Head over to https://replicate.com/hazxone/img2img-vg to try the web demo

For the 3edc1fe model, use ‘vangh’ as the trigger word

For the 76b7599 model, use ‘lvngvncnt’ in the beginning of the prompt.