👨‍🎓
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
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Learning to see in the dark

In this project, we implemented a research paper ( learning to see in the dark ) which mainly converts the night-time images to daytime images.

PreviousGPT-CompareNextLending Club analysis

Last updated 3 years ago

GitHub Link

Live demo link:

Libraries used:

  • Fast-ai

  • Pytorch

  • matplotlib

  • streamlit

  • gdown

The Model was developed on top of UNET architecture. This project can be used to convert night-time images to daytime images in real-time. For the web interface part, we have used Streamlit and it's also deployed on the Streamlit Cloud.

📚
🌙
Logohttps://share.streamlit.io/someshfengde/learning_to_see_in_dark/main/app.py
click to open live demo
LogoGitHub - someshfengde/learning_to_see_in_dark: converting night time images to day imagesGitHub
click to open on github