
This model is based on [CycleGAN](https://arxiv.org/abs/1703.10593) architecture. It takes images, and generates a futuristic neon image for the image provided.Hope this model neonifies your images.
![Demo.jpg](Demo_img.jpeg)

# Dataset

The model is trained on 256x256 high contrasted neon images as style images, and normal images (including people,scenery etc.) as base images.

#### Dataset - https://www.kaggle.com/datasets/aanisha07/futuristic-images

# Model

All details regarding how to use the model, fine-tune it, are added to GitHub.

#### Github - https://github.com/Aanisha/NeonGAN

# Spaces Demo

Check out the spaces demo, and try the model by yourselves.

#### Demo - https://huggingface.co/spaces/huggan/NeonGAN_Demo



Hope you all enjoy it!






{"license": "mit", "tags": ["gan", "unconditional image generation", "huggan", "style-transfer", "cyclegan", "Pytorch", "unconditional-image-generation"]}
gan unconditional image generation huggan style-transfer cyclegan Pytorch unconditional-image-generation arxiv:1703.10593 license:mit has_space region:us
TAGS
#gan #unconditional image generation #huggan #style-transfer #cyclegan #Pytorch #unconditional-image-generation #arxiv-1703.10593 #license-mit #has_space #region-us 


This model is based on CycleGAN architecture. It takes images, and generates a futuristic neon image for the image provided.Hope this model neonifies your images.
!URL

# Dataset

The model is trained on 256x256 high contrasted neon images as style images, and normal images (including people,scenery etc.) as base images.

#### Dataset - URL

# Model

All details regarding how to use the model, fine-tune it, are added to GitHub.

#### Github - URL

# Spaces Demo

Check out the spaces demo, and try the model by yourselves.

#### Demo - URL



Hope you all enjoy it!






# Dataset

The model is trained on 256x256 high contrasted neon images as style images, and normal images (including people,scenery etc.) as base images. #### Dataset - URL # Model

All details regarding how to use the model, fine-tune it, are added to GitHub. #### Github - URL # Spaces Demo

Check out the spaces demo, and try the model by yourselves. #### Demo - URL



Hope you all enjoy it!
TAGS
#gan #unconditional image generation #huggan #style-transfer #cyclegan #Pytorch #unconditional-image-generation #arxiv-1703.10593 #license-mit #has_space #region-us 
 # Dataset

The model is trained on 256x256 high contrasted neon images as style images, and normal images (including people,scenery etc.) as base images. #### Dataset - URL # Model

All details regarding how to use the model, fine-tune it, are added to GitHub. #### Github - URL # Spaces Demo

Check out the spaces demo, and try the model by yourselves. #### Demo - URL



Hope you all enjoy it!
passage: TAGS
#gan #unconditional image generation #huggan #style-transfer #cyclegan #Pytorch #unconditional-image-generation #arxiv-1703.10593 #license-mit #has_space #region-us 
# Dataset

The model is trained on 256x256 high contrasted neon images as style images, and normal images (including people,scenery etc.) as base images.#### Dataset - URL# Model

All details regarding how to use the model, fine-tune it, are added to GitHub.#### Github - URL# Spaces Demo

Check out the spaces demo, and try the model by yourselves.#### Demo - URL



Hope you all enjoy it!