import os
import gradio as gr
from datasets import load_dataset
auth_token = os.environ.get("auth_token")
visit_bench_all = load_dataset("mlfoundations/VisIT-Bench", use_auth_token=auth_token)
print('visit_bench_all')
print(visit_bench_all)
print('dataset keys:')
print(visit_bench_all.keys())
dataset_keys = list(visit_bench_all.keys())
assert len(dataset_keys) == 1
dataset_key = dataset_keys[0]
visit_bench = visit_bench_all[dataset_key]
print('first item:')
print(visit_bench[0])
df = visit_bench.to_pandas()
print(f"Got {len(df)} items in dataframe")
df = df.sample(frac=1)
df['image'] = df['image'].apply(lambda x: f'')
cols = list(df.columns)
cols.insert(0, cols.pop(cols.index('image')))
df = df.reindex(columns=cols)
LINES_NUMBER = 20
df.drop(columns=['visual'],inplace=True)
def display_df():
df_images = df.head(LINES_NUMBER)
return df_images
def display_next(dataframe, end):
start = int(end or len(dataframe))
end = int(start) + int(LINES_NUMBER)
global df
if end >= len(df) - 1:
start = 0
end = LINES_NUMBER
df = df.sample(frac=1)
print(f"Shuffle")
df_images = df.iloc[start:end]
assert len(df_images) == LINES_NUMBER
return df_images, end
initial_dataframe = display_df()
# Gradio Blocks
with gr.Blocks() as demo:
style = """
"""
gr.HTML(style) # This line embeds your CSS in the interface
gr.Markdown("