Recipe Genie Pad

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Inspiration

I am a big foodie myself and often thought of a tool that could identify a dish from a photo and provide recipe suggestions. After discussing the idea with my friends, I realized that many people would find such a tool incredibly useful. As a result, I decided to build the Recipe Genie Pad - a cutting-edge app that uses advanced technology to make cooking and eating more accessible, enjoyable, and sustainable.

What it does

The Recipe Genie Pad is a revolutionary web app that has taken the world of cooking and food to a whole new level! Imagine being able to take a picture of any dish and instantly receiving the name of the food, along with links to YouTube videos and blog articles on how to prepare it. That's what the Recipe Genie Pad does - it's like having a personal chef right at your fingertips!

But that's not all - the Recipe Genie Pad also provides a host of other amazing features. Want to order the dish for delivery? Simply click a button and let the app take care of the rest, automatically searching for the dish on food delivery platforms like Swiggy. And if you're feeling charitable, the app can even help you find local NGOs that accept donations of leftover food - just click a button and let the app do the work for you.

How I built it

I built Recipe Genie Pad using Python and various Python libraries such as Streamlit, Keras, Tensorflow, Selenium, and Beautiful Soup. The image recognition model was trained using a pre-trained model, Inception V3, and fine-tuned on a food image dataset. I integrated the app with Streamlit to create a user-friendly interface and used Selenium to automate the food delivery search feature. I used Domain.com for the domain name.

Challenges I ran into

The Biggest Problem, I faced was managing my time. Working all alone for a hackathon is a lot of work because you need to do Everything from a to z. Another challenge I faced was getting the food recognition algorithm to work accurately and quickly. I had to experiment a little to optimize the algorithm's performance. Additionally, integrating the food delivery and charitable donation features required me to work with external APIs and automate web scraping, which posed various technical challenges. 1 Minutes left and I came to know that hosting on streamlit and linking domain name to github pages is also pretty hard.

Accomplishments that I proud of

I'm proud that I was able to create an app that can identify dishes from photos and suggest relevant recipes. The automated food delivery search feature and the charitable food donation suggestions are also significant accomplishments. Additionally, I was able to make the app user-friendly and accessible to everyone, regardless of their technical skills.

What I learned

While building Recipe Genie Pad, I learned a lot about image recognition technology, neural networks, web development, and automation using Selenium. I also improved my skills in Python programming, particularly with the libraries used in the project.

What's next for Recipe Genie Pad

In the future, I plan to expand Recipe Genie Pad's image recognition capabilities to include more types of food and dishes. I also want to integrate a feature that suggests wine pairings for the recipes suggested by the app. Additionally, I plan to explore ways to make the food delivery search feature more precise and customizable for users.

Built With

• css
• html
• javascript
• keras
• opencv
• pillow
• python
• selenium
• streamlit
• tensorflow