Calhacks 12.0 Submission

AdSmart is a comprehensive web application that leverages computer vision, audio analysis, and generative AI to provide actionable insights on advertisement performance. Upload your image or video ads and receive instant, data-driven feedback on key metrics that influence audience engagement.

Modern advertisers struggle to quantify what makes an ad effective. Traditional A/B testing is expensive and time-consuming. AdMetrics AI solves this by providing instant, objective analysis of ad creative elements before launch, helping marketers optimize their content for maximum impact.

• Batch Upload Support - Analyze multiple ads simultaneously
• Persistent Media Library - View and re-analyze historical uploads
• Real-time Processing - Instant feedback with progress indicators
• Responsive Design - Works seamlessly on desktop and mobile
• Exportable Results - Download full analysis as JSON

• Streamlit - Rapid web app development with Python
• Custom CSS - Polished, professional UI/UX

• OpenCV (cv2) - Advanced image and video analysis
• PIL/Pillow - Image manipulation and format conversion
• NumPy - Efficient numerical computations

• Google Gemini 2.5 Flash - State-of-the-art multimodal AI for product detection and feature recognition
• Pydantic - Structured data validation and schema enforcement

• FFmpeg - Audio extraction and conversion
• Custom Audio Analysis Pipeline - Peak detection, voice analysis, and music classification

• Python 3.8+ - Core application logic
• python-dotenv - Secure environment variable management
• Tempfile - Safe file handling and cleanup

- Python 3.8 or higher
- FFmpeg (for video/audio processing)
- Google Gemini API Key

1. Clone the Repository

git clone https://github.com/PolnareffTurtle/ad-intelligence
cd ad-intelligence

2. Create Virtual Environment

python -m venv .venv
source .venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install Dependencies

pip install -r requirements.txt

4. Install FFmpeg

   • macOS: brew install ffmpeg
   • Ubuntu/Debian: sudo apt-get install ffmpeg
   • Windows: Download from ffmpeg.org

5. Configure Environment Variables

# Create .env file
touch .env

# Add your Gemini API key (add this to the .env file)
echo "GEMINI_API_KEY=your_gemini_api_key_here" >> .env

6. Run the Application

streamlit run calhacks.py

7. Alternatives to Website

python3 main.py # this runs the image/video processing, shows run time
python3 audio.py # this runs the audio processing

The app will open automatically in your browser at http://localhost:8501

streamlit>=1.28.0
opencv-python>=4.8.0
numpy>=1.24.0
Pillow>=10.0.0
google-generativeai>=0.3.0
pydantic>=2.0.0
python-dotenv>=1.0.0

1. Click "📷 Upload Image Ad" on the homepage
2. Select one or more image files (PNG, JPG, JPEG)
3. Preview your upload and click "🔍 Analyze Ad(s)"
4. Review metrics in the analysis dashboard
5. Download results as JSON for reporting

1. Click "🎥 Upload Video Ad" on the homepage
2. Select a video file (MP4, MOV, AVI)
3. Preview your upload and click "🔍 Analyze Ad(s)"
4. Wait for video and audio processing (may take 30-60 seconds)
5. Review comprehensive metrics across visual and audio dimensions

• Upload multiple images at once for comparative analysis
• View timing metrics for each file processed
• Access all results from the media library

• View all uploaded images via "🖼️ All Images"
• View all uploaded videos via "🎬 All Videos"
• Clear specific media types or entire history via "🗑️ Clear History"

1. Preprocessing - Resize and normalize images for consistent analysis
2. Edge Detection - Canny algorithm for negative space calculation
3. Local Contrast - Kernel-based intensity variance measurement
4. AI Vision - Gemini 2.5 Flash for semantic understanding
5. Metric Normalization - Scale all values to [0, 1] for comparability

1. Frame Extraction - Sample key frames (start, end, and midpoints)
2. Motion Analysis - Laplacian variance for blur detection
3. Scene Detection - Frame differencing for transition identification
4. Audio Extraction - FFmpeg conversion to WAV format
5. Audio Analysis - Peak detection, voice isolation, music classification
6. Temporal Metrics - First 3-second hook and loudness progression

• Gemini 2.5 Flash provides structured JSON responses with thinking budgets
• Pydantic Models ensure type safety and schema validation
• Fallback Handling for graceful degradation when AI is unavailable

• Engagement Prediction Model - ML model trained on historical ad performance
• Competitor Benchmarking - Compare your ads to industry standards
• Platform-Specific Optimization - Instagram vs. YouTube vs. TikTok recommendations
• A/B Test Suggestions - AI-generated variation recommendations
• Real-time Feedback - Live metrics during ad creation
• Team Collaboration - Shared workspaces and commenting
• API Access - Programmatic analysis for CI/CD pipelines
• Advanced Audio NLP - Sentiment and message clarity analysis

Calhacks 12.0 Team

• Kshitij Tomar - Team Member #1
• Yechan Park - Team Member #2
• Theo Dela Cruz - Team Member #3