| 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()) | |