Untitled

# 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