This repository includes projects done as part of Self-Driving Car Engineer Nanodegree term 1 by Udacity.
Project 1 - Finding Lane Lines on the Road using computer vision
Project 2 - Traffic Sign Classifier using deep learning and TensorFlow
Project 3 - Behavioral Cloning using deep learning and Keras
Project 4 - Advanced Lane Finding using computer vision
Project 5 - Vehicle Detection and Tracking using machine learning and computer vision
There are two ways to get up and running:
Get started here. More info here.
Supported Sytems: Linux (CPU), Mac (CPU), Windows (CPU)
| Pros | Cons |
|---|---|
| More straight-forward to use | AWS or GPU support is not built in (have to do this yourself) |
| More community support | Implementation is local and OS specific |
| More heavily adopted |
Get started here. More info here.
Supported Systems : AWS (CPU, GPU), Linux (CPU), Mac (CPU), Windows (CPU)
| Pros | Cons |
|---|---|
| Configure once for all environments | More challenging to use |
| AWS, GPU support | Less community support |
| Practice with Docker | Have to manage images and containers |
This project requires Python 3.5 and the following Python libraries installed:
- Jupyter
- NumPy
- SciPy
- scikit-learn
- TensorFlow
- Matplotlib
- Pandas (Optional)
Run this command at the terminal prompt to install OpenCV. Useful for image processing:
conda install -c https://conda.anaconda.org/menpo opencv3