Computer-Vision-Applications

Overview of real life applications and various projects involving computer vision & deep learning

Check out our YouTube video for an overview of how Computer Vision works:

• https://www.youtube.com/watch?v=ugCHGbzswGE

To Launch all Python Notebook files (.ipynb):

• Click here

• Choose a project and open a file

• You can now look through the code!

• To interact with and run the code, click on the 'Execute on Binder' button on the top right of the screen. (This will take a considerable amount of time to load)

• Once loaded, you can download the file to save your changes

• You can also download the .ipynb files in this repository and upload them in Google Colab here

• Alternatively, if you want to run .ipynb files on your local machine, you can download jupyter notebook by running pip install notebook and then running jupyter notebook. Read more here

To Download & Run the Python files (.py):

• Download the code git clone https://github.com/SJUSATA/Computer-Vision-Applications.git

• Navigate to the directory cd Computer-Vision-Applications

• Follow the instructions in your specific project's folder

Additional Resources

• TedTalk: How we teach computers to understand pictures

• TedTalk: Keep Calm and Learn Deep Learning

• TedTalk: How AI is Making it Easier to Diagnose Disease

• MIT Intro to Deep Learning Lecture

• MIT Convolutional Neural Network Lecture

• How Google Uses CAPTCHA to Train its Self Driving Cars

• Deep Neural Networks Help to Explain Living Brains

• How NASA Built a Self-Driving Car for Its Next Mars Mission

• Interactive 3D Visualization of Convolutional Layers

• GTA 5 Self Driving Car via Computer Vision

• Datasets for Computer Vision & Deep Learning Applications can be found on Kaggle and Google Dataset Search

Featured Projects

Face Mask Detection

Detecting COVID-19 in X-Rays

Social Distancing Detection

Age & Gender Detection

Object Detection

Human Pose Estimation

Pop Art Effect