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  This is a Streamlit app that allows users to upload a 60-second video and extract the best 20 frames using three methods:
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  1. **Motion-Based Selection**: Frames with the most motion.
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- 2. **Scene Change-Based Selection**: Frames where significant scene changes occur.
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- 3. **Clustering-Based Selection**: Representative frames from different clusters.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  The app first converts the video to 15 FPS and then applies the frame selection methods.
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  This is a Streamlit app that allows users to upload a 60-second video and extract the best 20 frames using three methods:
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  1. **Motion-Based Selection**: Frames with the most motion.
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+ Compute the absolute difference between consecutive frames.
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+ Frames with higher differences indicate more motion.
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+ Select the top 5 frames with the highest motion scores.
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+ 3. **Scene Change-Based Selection**: Frames where significant scene changes occur.
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+ Select frames where significant scene changes occur.
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+ How It Works:
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+ Compare histograms of consecutive frames.
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+ If the histogram difference exceeds a threshold, consider it a scene change.
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+ Select the top 20 frames where scene changes are detected.
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+ 5. **Clustering-Based Selection**: Representative frames from different clusters.
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+ Select diverse and representative frames by grouping similar frames.
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+ How It Works:
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+ Extract features from each frame using a pre-trained model (e.g., VGG16).
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+ Use K-Means clustering to group similar frames into clusters.
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+ Select one representative frame from each cluster.
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  The app first converts the video to 15 FPS and then applies the frame selection methods.
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