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"""Streamlit demo to visualize AVTime Dataset."""
import os
from os.path import join, exists, dirname, abspath, basename
import numpy as np
import pandas as pd
import streamlit as st
import warnings
warnings.simplefilter(action='ignore')
curr_filepath = abspath(__file__)
repo_path = dirname(dirname(curr_filepath))
def make_grid(cols,rows):
grid = [0]*cols
for i in range(cols):
with st.container():
grid[i] = st.columns(rows)
return grid
def read_spreadsheet(sheet_id, gid, **kwargs):
BASE_URL = 'https://docs.google.com/spreadsheets/d/'
df = pd.read_csv(BASE_URL + sheet_id + f'/export?gid={gid}&format=csv', **kwargs)
# drop all rows which have atleast 1 NaN value
df = df.dropna(axis=0)
return df
SHEET_ID = "1ejT6SWbihrYzfB_npb0WS2UHd8TIxPZkMpqbJ-M_hfw"
GID = "0"
if __name__ == "__main__":
# Add a title
st.set_page_config(layout="wide")
st.title("Clips from AVTime Dataset 🎬")
if "df" not in st.session_state:
# Read spreadsheet
df = read_spreadsheet(sheet_id=SHEET_ID, gid=GID, on_bad_lines='skip')
st.session_state.df = df
else:
df = st.session_state.df
st.markdown(f"**Total number of relevant clips**: {len(df)}", unsafe_allow_html=True)
reload_button = st.button("Reload")
NUM = 9
indices = np.random.randint(0, len(st.session_state.df), NUM)
if reload_button:
indices = np.random.randint(0, len(st.session_state.df), NUM)
# Create a grid of videos
grid = make_grid(3, 3)
per_video_width = 360
per_video_height = 240
for idx, index in enumerate(indices):
sample = st.session_state.df.iloc[index].to_dict()
video_id = sample["video_id"]
stime, etime = sample["start_time"], sample["end_time"]
duration = etime - stime
desc = sample["description"]
i, j = idx // 3, idx % 3
grid[i][j].caption(f"Segment duration: {duration}")
url = f"https://www.youtube.com/embed/{video_id}?start={int(stime)}&end={int(etime)}"
html_code = f"""
<iframe height="{per_video_height}" width="{per_video_width}" src="{url}" frameborder="0" allowfullscreen></iframe>
"""
grid[i][j].markdown(html_code, unsafe_allow_html=True)
grid[i][j].caption(f"{desc}")
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