from datetime import datetime import streamlit as st import random import time from streamlit_extras.switch_page_button import switch_page def login(): # skip customize user name for debug mode with st.form("user_login"): # st.write('## Enter Your Name to Start the Session') st.write( '### Getting obsessed with tons of different text-to-image generation models available online? Want to find the most suitable one for your taste?') st.write('**GEMRec** is here to help you! Enter your name to try it outπŸ‘‡!') user_id = st.text_input( "Enter your name πŸ‘‡", label_visibility='collapsed', disabled=False, placeholder='You can leave it blank to be anonymous' ) # st.write('You can leave it blank to be anonymous.') st.session_state.show_NSFW = st.toggle(':orange[show potentially mature content]', help='Inevitably, a few images might be NSFW, even if we tried to elimiate NFSW content in our prompts. We calculate a NSFW score to filter them out. Please check only if you are 18+ and want to take a look at the whole GEMRec-18k dataset', value=False, key='mature_content') # Every form must have a submit button. submitted = st.form_submit_button("Start") if submitted: save_user_id(user_id) switch_page("gallery") def save_user_id(user_id): print(user_id) if not user_id: user_id = 'anonymous' + str(random.randint(0, 100000)) st.session_state.user_id = [user_id, datetime.now().strftime("%Y-%m-%d %H:%M:%S")] st.session_state.assigned_rank_mode = random.choice(['Drag and Sort', 'Battle']) def logout(): st.session_state.pop('user_id', None) st.session_state.pop('selected_dict', None) st.session_state.pop('score_weights', None) st.session_state.pop('gallery_state', None) st.session_state.pop('edit_state', None) st.session_state.pop('progress', None) st.session_state.pop('gallery_focus', None) st.session_state.pop('assigned_rank_mode', None) st.session_state.pop('show_NSFW', None) st.session_state.pop('modelVersion_standings', None) def info(): with st.sidebar: st.write('## About') st.write( "This is a web application **for individual users to quickly dig out the most preferable text-to-image models from [civitai](https://civitai.com) for different prompts**. Our research aims to understand personal preference towards generative models and you can contribute by playing with this tool and giving us your feedback! " ) st.write( "After picking images you liked from Gallery and a Ranking Contest, a summary dashboard will be presented **indicating your preferred models with download links ready to be deployed in [Webui](https://github.com/AUTOMATIC1111/stable-diffusion-webui)** !" ) if __name__ == '__main__': # print(st.source_util.get_pages('Home.py')) st.set_page_config(page_title="Login", page_icon="🏠", layout="wide") info() st.write('A Research by [MAPS Lab](https://whongyi.github.io/MAPS-research), [NYU Shanghai](https://shanghai.nyu.edu)') st.title("πŸ™Œ Welcome to GEMRec Gallery!") if 'user_id' not in st.session_state: login() else: st.write(f"You have already logged in as `{st.session_state.user_id[0]}`") st.write(f"Assigned ranking mode: `{st.session_state.assigned_rank_mode}`") st.button('Log out', on_click=logout) st.write('---') st.write('### FAQ') with st.expander(label='**πŸ€” How to use this webapp?**'): st.write('### Check out the demo video below') st.info('Interface shown in this video demo is a bit different from the current webapp because it\'s outdated, but the basic idea is the same.') st.video('https://youtu.be/EjjCoeUSZF0') with st.expander(label='**ℹ️ What is GEMRec project?**'): st.write('### About GEMRec') st.write("**GE**nerative **M**odel **Rec**ommendation (**GEMRec**) is a research project by [MAPS Lab](https://github.com/MAPS-research), NYU Shanghai.") st.write('### Our Task') st.write('Navigate hundreds of text-to-image models through various categories of pre-defined prompts and a graph-based interface. Given a user’s preference and interaction data, we aim to recommend the most preferred generative model for the user.') st.write('### Our Approach') st.write('We propose a two-stage framework, which contains prompt-model retrieval and generative model ranking. :red[Your participation in this web application will help us to improve our framework and to further our research on personalization.]') # st.write('### Key Contributions') # st.write('1. We propose a two-stage framework to approach the Generative Model Recommendation problem. Our framework allows end-users to effectively explore a diverse set of generative models to understand their expressiveness. It also allows system developers to elicit user preferences for items generated from personalized prompts.') # st.write('2. We release GEMRec-18K, a dense prompt-model interaction dataset that consists of 18K images generated by pairing 200 generative models with 90 prompts collected from real-world usages, accompanied by detailed metadata and generation configurations. This dataset builds the cornerstone for exploring Generative Recommendation and can be useful for other tasks related to understanding generative models') # st.write('3. We take the first step in examining evaluation metrics for personalized image generations and identify several limitations in existing metrics. We propose a weighted metric that is more suitable for the task and opens up directions for future improvements in model training and evaluations.') with st.expander(label='**πŸ“‘ Where can I find the paper and dataset?**'): st.write('### Paper') st.write('Arxiv: [Towards Personalized Prompt-Model Retrieval for Generative Recommendation](https://arxiv.org/abs/2308.02205)') st.write('### GEMRec-18K Dataset') st.write('Image dataset: https://huggingface.co/datasets/MAPS-research/GEMRec-PromptBook \n \ Model dataset: https://huggingface.co/datasets/MAPS-research/GEMRec-Roster') st.write('### Code') st.write('Github: https://github.com/maps-research/gemrec')