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import os
import streamlit as st
from models import CLIP, T2T
from tasks import Summary, VideoSearch
from log_generation import download_youtube, extract_video_frames, generate_log
os.system('pip uninstall opencv-python-headless -y')
os.system('pip uninstall opencv-python -y')
os.system('pip install opencv-python')
st.set_page_config(page_title="Socratic Models Demo", page_icon="", layout="wide")
st.title("Socratic Models Demo")
if "vlm" not in st.session_state:
st.session_state.vlm = CLIP()
if "llm" not in st.session_state:
st.session_state.llm = T2T()
col1, col2, _ = st.columns([2, 2, 3])
with col1:
url = st.text_input(
"YouTube Video URL", "https://www.youtube.com/watch?v=tQG6jYy9xto"
)
video_id = url.split("watch?v=")[-1]
with col2:
st.video(url)
if not os.path.exists(f"{video_id}/history.txt"):
st.write("Video not found locally. Downloading may take several minutes. Continue?")
click = st.button("Download")
if not click:
st.stop()
st.success("Downloading...")
download_youtube(url)
st.write("Extracting frames...")
extract_video_frames(
f"{video_id}/{video_id}.mp4", dims=(600, 400), sampling_rate=100
)
st.write("Generating log...")
generate_log(
f"{video_id}/history.txt",
f"{video_id}",
st.session_state.vlm,
st.session_state.llm,
)
refresh = st.button("Click to refresh")
if not refresh:
st.stop()
search = VideoSearch(video_id, st.session_state.vlm)
st.title("Video Search")
query = st.text_input("Search Query", "working at my computer")
images = search.search_engine(query)
with st.expander(label="See results"):
for image in images:
st.image(image)
st.title("Event Summaries")
summ = Summary(video_id, st.session_state.llm)
summaries = summ.generate_summaries()
with st.expander(label="See results"):
for (prompt, result) in summaries:
st.markdown("*Event Log*")
st.write(prompt)
st.markdown("*Summary*")
st.write(result)
st.title("Video Event Log")
with open(f"{video_id}/history.txt", "r") as f:
st.text(f.read())
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