👨‍🎓
Somesh Fengade
  • ME
    • 👋About
    • 📚Personal Projects
      • 🌄AI meditations
      • 🤖GPT-Compare
      • 🌙Learning to see in the dark
      • 💸Lending Club analysis
      • ⏬Moodle Downloader
      • 📚Analyzing the complexity of literary passages.
      • 🧪Unit test analysis
      • 🍕Food Vision
      • 📜Skim Lit project
      • 🚋Driver's attention detection
      • ⏳React Countdown Timer app
  • Achievements
    • 🎓Achievements directory
      • 🐣Kaggle Expert (notebook)
      • ❗Amazon Machine learning competition (top 100)
      • 🐶PetFinder.my - Pawpularity Contest ( top 20%)
      • 🐳Happywhale - Whale and Dolphin Identification (top 20%)
      • 🖊️NBME - Score Clinical Patient Notes ( top 50%)
      • 🕸️Tensorflow Barrier Riff challenge(top 42%)
  • Notes and courses
    • 🍂Foundations of LLMs Lesson 1
    • GPT from scratch
    • Introduction to CUDA Python with Numba
      • Custom CUDA kernels in python with Numba
      • Multidimensional grids and shared memory for cuda python with Numba
Powered by GitBook
On this page
  • Github Link:
  • Libraries used:
  • Live application
  1. ME
  2. Personal Projects

Food Vision

This application was the first application I have developed while working with computer vision with tensorflow

PreviousUnit test analysisNextSkim Lit project

Last updated 3 years ago

The project was to determine the food after analyzing and passing clicked images from the machine learning model. In this I have used various machine learning models the best model was able to detect 250 classes of various food variety

Github Link:

Libraries used:

  • TensorFlow

  • matplotlib

  • streamlit

  • fastai

Live application

📚
🍕
GitHub - someshfengde/Food-vision-streamlit: deploying the machine learning model for doing the predictions on the food images onlineGitHub
https://share.streamlit.io/someshfengde/food-vision-streamlit/main/main.py
Logo
Logo