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import streamlit as st
import numpy as np
import random
import pandas as pd
import glob
import csv
from PIL import Image
from datasets import load_dataset, Dataset, load_from_disk
from huggingface_hub import login
import os
class GalleryApp:
def __init__(self, promptBook):
self.promptBook = promptBook
st.set_page_config(layout="wide")
def gallery(self, items, col_num, info):
cols = st.columns(col_num)
# # sort items by brisque score
# items = items.sort_values(by=['brisque'], ascending=True).reset_index(drop=True)
for idx in range(len(items)):
with cols[idx % col_num]:
image = st.session_state.images[items.iloc[idx]['row_idx'].item()]['image']
st.image(image,
use_column_width=True,
)
for key in info:
st.write(f"**{key}**: {items.iloc[idx][key]}")
def app(self):
st.title('Model Coffer Gallery')
st.write('This is a gallery of images generated by the models in the Model Coffer')
metadata, images = st.columns([1, 3])
# with images:
# prompt_tags = self.promptBook['tag'].unique()
# # sort tags by alphabetical order
# prompt_tags = np.sort(prompt_tags)
#
# selecters = st.columns(3)
# with selecters[0]:
# tag = st.selectbox('Select a tag', prompt_tags)
with metadata:
prompt_tags = self.promptBook['tag'].unique()
# sort tags by alphabetical order
prompt_tags = np.sort(prompt_tags)
tag = st.selectbox('Select a tag', prompt_tags)
items = self.promptBook[self.promptBook['tag'] == tag].reset_index(drop=True)
prompts = [', '.join(x.split(', ')[4:]) for x in items['prompt'].unique()]
prompt = st.selectbox('Select prompt', prompts)
idx = prompts.index(prompt)
prompt_full = ', '.join(items['prompt'].unique()[idx].split(', ')[:4]) + ', ' + prompt
prompt_id = items[items['prompt'] == prompt_full]['prompt_id'].unique()[0]
items = items[items['prompt_id'] == prompt_id].reset_index(drop=True)
st.write('**Prompt ID**')
st.caption(f"{prompt_id}")
st.write('**Prompt**')
st.caption(f"{items['prompt'][0]}")
st.write('**Negative Prompt**')
st.caption(f"{items['negativePrompt'][0]}")
st.write('**Sampler**')
st.caption(f"{items['sampler'][0]}")
st.write('**cfgScale**')
st.caption(f"{items['cfgScale'][0]}")
st.write('**Size**')
st.caption(f"width: {items['size'][0].split('x')[0]}, height: {items['size'][0].split('x')[1]}")
st.write('**Seed**')
st.caption(f"{items['seed'][0]}")
with images:
selecters = st.columns([1, 1, 2])
# with selecters[0]:
with selecters[0]:
sort_by = st.selectbox('Sort by', items.columns[11: -1])
with selecters[1]:
order = st.selectbox('Order', ['Ascending', 'Descending'], index=1 if sort_by == 'clip_score' or sort_by == 'model_download_count' else 0)
if order == 'Ascending':
order = True
else:
order = False
items = items.sort_values(by=[sort_by], ascending=order).reset_index(drop=True)
with selecters[2]:
info = st.multiselect('Show Info',
['brisque_score', 'clip_score', 'model_download_count', 'model_name', 'model_id',
'modelVersion_name', 'modelVersion_id'],
default=sort_by)
# if sort_by not in info:
# info.append(sort_by)
col_num = st.slider('Number of columns', min_value=1, max_value=9, value=4, step=1, key='col_num')
self.gallery(items, col_num, info)
# st.write(items)
if __name__ == '__main__':
login(token=os.environ.get("HF_TOKEN"))
if 'roster' not in st.session_state:
print('loading roster')
# st.session_state.roster = pd.DataFrame(load_dataset('NYUSHPRP/ModelCofferRoster', split='train'))
st.session_state.roster = pd.DataFrame(load_from_disk(os.path.join(os.getcwd(), 'data', 'roster')))
st.session_state.roster = st.session_state.roster[['model_id', 'model_name', 'modelVersion_id', 'modelVersion_name',
'model_download_count']].drop_duplicates().reset_index(drop=True)
# add model download count from roster to promptbook dataframe
if 'promptBook' not in st.session_state:
print('loading promptBook')
st.session_state.promptBook = pd.DataFrame(load_dataset('NYUSHPRP/ModelCofferMetadata', split='train'))
st.session_state.images = load_from_disk(os.path.join(os.getcwd(), 'data', 'promptbook'))
print('images loaded')
# st.session_state.promptBook = pd.DataFrame(load_dataset('NYUSHPRP/ModelCofferPromptBook', split='train'))
st.session_state.promptBook = st.session_state.promptBook.merge(st.session_state.roster[['model_id', 'model_name', 'modelVersion_id', 'modelVersion_name', 'model_download_count']], on=['model_id', 'modelVersion_id'], how='left')
# add column to record current row index
st.session_state.promptBook['row_idx'] = st.session_state.promptBook.index
print('promptBook loaded')
# print(st.session_state.promptBook)
check_roster_error = False
if check_roster_error:
# print all rows with the same model_id and modelVersion_id but different model_download_count in roster
print(st.session_state.roster[st.session_state.roster.duplicated(subset=['model_id', 'modelVersion_id'], keep=False)].sort_values(by=['model_id', 'modelVersion_id']))
app = GalleryApp(promptBook=st.session_state.promptBook)
app.app()
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