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import streamlit as st
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import requests
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from PIL import Image
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from io import BytesIO
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from transformers import pipeline
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def extract_thumbnail_url(youtube_url):
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"""Extracts the thumbnail URL from a YouTube video link."""
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video_id = youtube_url.split("v=")[-1].split("&")[0]
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return f"https://img.youtube.com/vi/{video_id}/maxresdefault.jpg"
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def load_image(url):
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"""Loads an image from a URL."""
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response = requests.get(url)
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if response.status_code == 200:
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return Image.open(BytesIO(response.content))
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return None
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def main():
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st.title("🔎 YouTube Fake Video Detector")
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st.write("Enter a YouTube video link to detect if its thumbnail is AI-generated or manipulated.")
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youtube_url = st.text_input("YouTube Video Link")
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if youtube_url:
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thumbnail_url = extract_thumbnail_url(youtube_url)
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st.subheader("Thumbnail Preview:")
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image = load_image(thumbnail_url)
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if image:
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st.image(image, caption="Video Thumbnail", use_column_width=True)
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with st.spinner("Analyzing thumbnail..."):
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model = pipeline("image-classification", model="nateraw/resnet50-oxford-flowers")
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results = model(thumbnail_url)
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st.subheader("Detection Results:")
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for result in results:
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st.write(f"**{result['label']}**: {result['score']*100:.2f}% confidence")
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else:
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st.error("Failed to load thumbnail. Please check the YouTube link.")
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if __name__ == "__main__":
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main()
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