Automate Your Kitchen with Python & Applied AI — Sena Sahin

Project focused on automating kitchen management and recipe recommendations using Python and AI technologies

Core components include:

• Object detection to identify fridge contents
• Recipe recommendation system based on available ingredients
• Integration with OpenAI’s GPT-3.5 API for recipe suggestions
• Streamlit for creating the user interface

Used pre-trained models (Faster R-CNN with ResNet) for object detection rather than building from scratch

Key challenges addressed:

• Handling messy fridge contents
• Dealing with ingredients stored outside the fridge
• Managing ingredient quantities
• Processing chopped/prepared ingredients
• Edge cases in food detection

Project design considerations:

• Start with version control and small steps
• Focus on baseline functionality first
• Add features incrementally
• Get user feedback early
• Consider simulation for test data

Benefits:

• Reduces food waste
• Helps with meal planning
• Assists in mindful shopping
• Makes cooking more accessible

Technical implementation kept simple by:

• Using pre-trained models
• Leveraging existing APIs
• Building monolithic architecture
• Using Streamlit for quick UI development

Project serves as good portfolio piece:

• Demonstrates practical AI application
• Shows real-world problem solving
• Includes user interaction
• Combines multiple technologies