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import streamlit as st |
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import requests |
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from transformers import pipeline |
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from PIL import Image |
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from io import BytesIO |
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import re |
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model = pipeline("image-classification", model="google/vit-base-patch16-224") |
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def get_thumbnail_url(youtube_url): |
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"""Extract YouTube video ID and generate thumbnail URL.""" |
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video_id_match = re.search(r"(?:v=|youtu.be/|shorts/)([a-zA-Z0-9_-]{11})", youtube_url) |
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if video_id_match: |
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video_id = video_id_match.group(1) |
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return f"https://img.youtube.com/vi/{video_id}/maxresdefault.jpg" |
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return None |
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def detect_thumbnail(thumbnail_url): |
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"""Run AI detection on the thumbnail image.""" |
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response = requests.get(thumbnail_url) |
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if response.status_code == 200: |
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image = Image.open(BytesIO(response.content)) |
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results = model(image) |
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return results, image |
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return None, None |
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def main(): |
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st.title("🔍 Video Thumbnail AI Detector") |
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st.write("Enter a YouTube video link to detect content from its thumbnail.") |
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video_url = st.text_input("YouTube Video URL:") |
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if st.button("Analyze Thumbnail") and video_url: |
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thumbnail_url = get_thumbnail_url(video_url) |
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if thumbnail_url: |
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results, image = detect_thumbnail(thumbnail_url) |
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if results and image: |
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st.image(image, caption="Video Thumbnail", use_container_width=True) |
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st.subheader("Detection Results:") |
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for res in results: |
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st.write(f"- **{res['label']}**: {res['score']:.4f}") |
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else: |
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st.error("Failed to retrieve or analyze the thumbnail.") |
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else: |
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st.error("Invalid YouTube URL.") |
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if __name__ == "__main__": |
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main() |
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