magnify

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  magnify:main page

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  a chart on the test run label

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  the chat and RDA section

Inspiration

The idea for Magnify came from the frustration of trying to understand the small, complex labels on packaged foods. Women, in particular, face unique health challenges that are often overlooked in the nutrition space. Understanding what’s in the food we eat is essential for good health, yet current food labels are not helping much. So created a tool that would help women with easy-to-understand information about food ingredients, nutritional values, and their impact on health.

What it does

Magnify leverages gemini to scan and analyze food labels, extracting and interpreting key nutritional data. The tool breaks down ingredients and nutrient information, comparing them to the recommended daily allowance (RDA), providing a clear, personalized view of what’s inside the food we eat. This helps women make informed decisions about their nutrition and health, empowering them to improve their diets and overall well-being.

How we built it

python streamlit for the frontend(life saver!) gemini

Challenges I ran into

One of the main challenges was handling the variability in food labels—different brands and countries use different formats and terms. Another challenge was ensuring that the nutritional information was presented in a way that was easily understood, especially when dealing with and ingredient lists with different values. Hit a major time burning phase when I could not get my hands on data which could serve my purpose well(Thanks to my friend who helped me get that info)

Accomplishments that I am proud of

The tool can accurately extract data from images of food labels, interpret the information, and present it in an easy-to-understand format. Particularly proud of integrating the RDA comparison, which provides users with valuable context about their food choices. Additionally, we’re excited to see how this tool can support women in making informed, healthy decisions.

What I learned

Through this project, I learned a lot about OCR and AI to analyze real-world data. I learned about RDA and other regulations with regards to food and nutrition. Using gemini for the the first time to build something with streamlit was fun!

What's next for Magnify

Moving forward, I plan to improve the tool’s ability to handle a wider variety of label formats and languages. I also aim to expand the database of nutritional values, integrating more global food products. Capture picture of food and be able to calculate the total nutrition value.

Built With

• gemini
• python
• streamlit