Project instructions Workspaces

Workspace Users :

This workspace is designed to be a simple, easy to use environment in which you can code and run the
Finding Lane Lines project.

Note: If you prefer to run the project in your local setup, navigate to the Project instructions Local Setup lesson.

Intro

In this project, you will be writing code to identify lane lines on the road, first in an image, and later in a video stream (really just a series of images). To complete this project you will use the tools you learned about in the lesson, and build upon them.

Your first goal is to write code including a series of steps (pipeline) that identify and draw the lane lines on a few test images. Once you can successfully identify the lines in an image, you can cut and paste your code into the block provided to run on a video stream.

You will then refine your pipeline with parameter tuning and by averaging and extrapolating the lines.

Finally, you'll make a brief writeup report. The workspace github repository has a writeup_template.md that can be used as a guide.

Have a look at the video clip called "P1_example.mp4" in the repository to see an example of what your final output should look like. Two videos are provided for you to run your code on. These are called "solidWhiteRight.mp4" and solidYellowLeft.mp4".

For tips on workspace use, please review the Workspaces lesson.

Accessing and using the workspace:

Go to the workspace node and the project JUPYTER notebook will automatically load
Complete the project using the instructions in the notebook
The project repo is already in the workspace. To see other files in the repo click on the JUPYTER icon. This will expose the root directory. From there click on the project folder.

Commit to GitHub

Students are highly encouraged to commit their project to a GitHub repo. To do this, you must change the upstream of the current repository and add your credentials. We have supplied a bash script to help you do this. Please open up a terminal, navigate to the project repository, and enter: ./set_git.sh, then follow the prompts. This will set the upstream remote to your own repository and add your email and username to the git configuration. At this time we are not configuring passwords, so you will need to enter your username and password for each push. Since credentials are not persistent, it will be necessary to run this script each time you open, refresh, or reset the workspace.

Things to keep in mind:

If you leave your workspace unattended, it will time out and need to be refreshed. Your most recent work will be restored, but the list of open files or any running shell sessions will not be restored.

Evaluation

Once you have completed your project, use the Project Rubric to review the project. If you have covered all of the points in the rubric, then you are ready to submit! If you see room for improvement in any category in which you do not meet specifications, keep working!

Your project will be evaluated by a Udacity reviewer according to the same Project Rubric. Your project must "meet specifications" in each category in order for your submission to pass.

Ready to submit your project?

Make sure your workspace contains at least :

Jupyter Notebook with your project code
writeup report (md or pdf file)

Click on the Submit Project button and follow the instructions to submit!

Project Support

If you are stuck or having difficulties with the project, don't lose hope! Remember to ask (and answer!) questions on Knowledge tagged with the project name, and reach out to your fellow students in the Finding Lane Lines channel in your Student Hub. We also have a previously recorded project Q&A that you can watch here!

Passed your project? Share the good news!

What you’ve accomplished is no small feat. Give yourself a pat on the back and some well-deserved recognition by sharing your success with your network.

Facebook and LinkedIn

Make sure to use @Udacity and #selfdrivingudacity in your posts!