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# Complete the remaining slides and save the PowerPoint file # Continue adding slides add_slide("MobileNetV2 for Feature Extraction", "- Pre-trained model optimized for real-time image processing.\n" "- Reduces computational load while maintaining high accuracy.\n" "- Used for feature extraction before classification.") add_slide("Model Training and Evaluation", "- Trained for 50 epochs with Adam optimizer.\n" "- Evaluated using accuracy, precision, recall, and F1-score.\n" "- Confusion matrix used to assess false positives & false negatives.") add_slide("Real-Time Detection Using OpenCV", "- Captures live video and extracts frames.\n" "- Converts BGR to RGB and resizes frames.\n" "- Feeds frames to MobileNetV2 model for classification.") add_slide("Advantages of Our System", "- AI-based real-time detection enhances security.\n" "- Cloud integration enables remote monitoring.\n" "- Lower false alarm rates compared to traditional systems.") add_slide("Future Scope", "- Adding audio analysis for enhanced accuracy.\n" "- Deploying on edge devices like Jetson Nano.\n" "- Cloud-based real-time alerting system.") add_slide("Conclusion", "- Successfully implemented an AI-powered surveillance system.\n" "- Real-time violence detection using MobileNetV2 & OpenCV.\n" "- Potential for large-scale deployment in public spaces.") # Final slide: Thank You add_slide("Thank You!", "Questions?") # Save the PowerPoint file pptx_filename = "/mnt/data/VigilEye_Presentation.pptx" prs.save(pptx_filename) # Provide the download link pptx_filename
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