YeBhoneLin10
/

bagan

   - stable-diffusion
   - text-to-image
   - diffusers
+---
+### Introduction:
+Meet General Bagan, a cutting-edge text-to-image generator trained on a diverse dataset of over 200 images. With a keen understanding of textual inputs, it effortlessly translates words into visually stunning representations. From lifelike nature scenes to captivating abstract compositions.
+### Problem Statement:
+When we prompted the stable diffusion model to generate an image of Bagan, it produced an image depicting a pagoda from Thailand. Hence, our decision was to fine-tune the current stable diffusion model using a multitude of Bagan photos in order to attain a clearer outcome.
+### How to create prompt:
+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.
+### Data:
+We used stable diffusion v1.5 model to train with 223 bagan pictures.
+### Contributors:
+Main Contributor: [Ye Bhone Lin](https://github.com/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:
+In our exploration of image generation, we delve 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.
+### 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