| import streamlit as st | |
| from pytube import YouTube | |
| from transformers import pipeline | |
| import tempfile | |
| import os | |
| st.title("Deepfake Video Detection") | |
| video_url = st.text_input("Enter YouTube Video URL:") | |
| if st.button("Submit") and video_url: | |
| with st.spinner("Downloading and analyzing video..."): | |
| try: | |
| yt = YouTube(video_url) | |
| stream = yt.streams.filter(file_extension='mp4', progressive=True).first() | |
| temp_dir = tempfile.mkdtemp() | |
| video_path = os.path.join(temp_dir, "video.mp4") | |
| stream.download(output_path=temp_dir, filename="video.mp4") | |
| model = pipeline("image-classification", model="facebook/deit-base-distilled-patch16-224") | |
| results = model(video_path) | |
| st.success("Analysis Complete") | |
| st.write("Prediction:", results[0]['label']) | |
| st.write("Confidence:", f"{results[0]['score'] * 100:.2f}%") | |
| os.remove(video_path) | |
| os.rmdir(temp_dir) | |
| except Exception as e: | |
| st.error(f"Error: {e}") | |