02. Setting up your Local Environment

Install Dependencies

The following instructions are meant to be carried out on your computer instead of the VM.
Note: Currently, we will be working with TF version 1.2.1 for the rest of this module and will update to the latest TF version later.

Prerequisites

The RoboND environment requires Python 3.5 64-bit and Anaconda. During the first week of the ND, you went through the installation for Anaconda. You can follow the steps pointed out here in case you want to reinstall the software.

Once you have Anaconda setup with the required Python version, run the following commands via the terminal or command line, to setup your environment:

Note: if you have a recent version of the RoboND environment then these packages should already be installed.

OS X and Linux (Ubuntu)

source activate RoboND
pip install tensorflow==1.2.1
pip install socketIO-client
pip install transforms3d
pip install PyQt5
pip install pyqtgraph

Windows

source activate RoboND 
# if the above throws an error, you can run "activate RoboND" instead
pip install tensorflow==1.2.1
pip install socketIO-client
pip install transforms3d
pip install PyQt5
pip install pyqtgraph

**Note: ** The above steps will help you install the CPU version for Tensorflow only.

Grab the Project Resources and the Simulator Binary

Clone the repository

$ git clone https://github.com/udacity/RoboND-DeepLearning-Project.git

Download the QuadSim binary

To interface your neural net with the QuadSim simulator, you must use a version QuadSim that has been custom tailored for this project. The previous version that you might have used for the Controls lab will not work.

The simulator binary can be downloaded here

Grab the Data

Save the following three files into the data folder of the cloned repository.

Training Data

Validation Data

Sample Evaluation Data