license: creativeml-openrail-m
language:
- en
tags:
- stable-diffusion
- text-to-image
- diffusers
widget:
- text: bagan, by Vincent van gogh, highly detailed, highly illustration
example_title: Example Prompt 1
- text: >-
Establishing shot of a bagan, an epic fantasy, dramatic lighting,
cinematic, extremely high detail, photorealistic, cinematic lighting,
matte painting, artstation, by simon stalenhag, uncharted 4: a thief's end
example_title: Example Prompt 2
- text: >-
hyper realistic water color painting, transparent, myanmar bagan ancient
city, after raining sense, beautiful cloud, ancient pagoda, some trees,
with water splash infront of pagoda, lovely cloud, beautiful golden ratio
composition, neutral color, moody image, lots of grey, golden ratio
composition, grey and moody, more grey, rule of third, --ar 5:3 --q 0.5
--v 5
example_title: Example Prompt 3
base_model: runwayml/stable-diffusion-v1-5
metrics:
- code_eval
library_name: diffusers
pipeline_tag: text-to-image
enchanted-bagan-small
Enchanted-bagan-small is a latent text-to-image diffusion model designed to generate Bagan images based on the text input. The quality of the generated pictures heavily relies on the input prompt.
How to create prompts:
When we create prompt for bagan, we have to consider 6 keywords. Those are Subject, Medium, Style, Art-sharing website, Resolution, and Additional details.
Subject -> What you want to see in the picture is the subject. Not writing enough about the subjects is a common error.
Medium -> The medium is the substance that artists work with. Illustration, oil painting, 3D rendering, and photography are a few examples. The impact of Medium is significant because a single keyword can significantly alter the style.
Style -> The image's artistic style is referred to as the style. Pop art, impressionist, and surrealist are a few examples.
Art-sharing website -> Specialty graphic websites like Deviant Art and Artstation compile a large number of images from various genres. One surefire way to direct the image toward these styles is to use them as a prompt.
Resolution -> Resolution represents how sharp and detailed the image is
Additional Details -> Sweeteners added to an image are additional details. To give the image a more dystopian and sci-fi feel, we will add those elements.
The example prompt for general bagan is: bagan, a creepy and eery Halloween setting, with Jack o lanterns on the street and shadow figures lurking about, dynamic lighting, photorealistic fantasy concept art, stunning visuals, creative, cinematic, ultra detailed, trending on art station, spooky vibe. That prompt gives you the Halloween theme.
Contributors:
Main Contributor: Ye Bhone Lin
Supervisor: Sa Phyo Thu Htet
Contributors: Thant Htoo San, Min Phone Thit
Limitation:
We can't generate a photo of a human.
Other Work:
Note: These other works are not included in this version.
Other Work: In our exploration of image generation, we also have worked into the architectural marvels of Myanmar, featuring iconic landmarks such as Ananda, Shwezigon, Bupaya, Thatbyinnyu, and Mraukoo. Each structure stands as a testament to the rich cultural and historical tapestry of the region, captured through the lens of our innovative text-to-image generator, General Bagan.
Cite As:
@software{enchanted-bagan-small, author = {{Ye Bhone Lin, Sa Phyo Thu Htet}}, title = {enchanted-bagan-small}, url = {https://huggingface.co/Simbolo-Servicio/enchanted-bagan-small}, urldate = {2024-1-25}, date = {2024-1-25} }
References:
Wikipedia (2022). Stable Diffusion. Retrieved From: https://en.wikipedia.org/wiki/Stable_Diffusion
Rombach, R., Blattmann, A., Lorenz, D., Esser, P., & Ommer, B. (2022). High-Resolution Image Synthesis with Latent Diffusion Models. Retrieved From: https://arxiv.org/abs/2112.10752
Naomi Brown (2022). What is Stable Diffusion and How to Use it. Retrieved From: https://www.fotor.com/blog/what-is-stable-diffusion
Mishra, O. (June, 9). Stable Diffusion Explained. Medium. https://medium.com/@onkarmishra/stable-diffusion-explained-1f101284484d