Autonomous Cars: Deep Learning and Computer Vision in Python (Course Materials)

Getting Started

Install Anaconda for Python 3 for your operating system from

Install OpenCV and Tensorflow
Open an Anaconda Prompt (if you’re on Windows, open it as Administrator by right-clicking on it in your Start menu, selecting “more”, and then “run as administrator.” In the terminal, run:

conda install opencv

Hit ‘y’ to proceed if prompted.

Once it’s done, proceed to run:

pip install --ignore-installed --upgrade tensorflow

You may see some scary-looking errors at this point, but they are safe to ignore.

Get the Course Materials at and unzip them into a path that’s easy to type (for example c:\SelfDrivingMaterials would be appropriate on Windows.)

Get the Slides at if you’d like to have them for later reference.

Try it out
From your Anaconda prompt, cd into the directory you unzipped the course materials into. For example:

cd c:\SelfDrivingMaterials

Now launch a Jupyter Notebook:

jupyter notebook

You should see a listing of the course sections in your web browser. If you have a webcam connected, navigate into section 4, and select “Lecture 4.14 Canny Sobel and Laplace Edge Detection using Webcam.ipynb”

Click in each block of code in order, and hit “shift-enter” to run it. If everything is set up properly, a video window should appear at the end showing you with an edge detection algorithm applied! Hit the “enter” key while this window is active to exit it when you’re done.

If you run into a DLL import error when importing the cv2 package, this is due to a compatibility issue between opencv as installed by conda and your video card. If that happens, shut down the notebook, and back in your Anaconda prompt, type:

conda remove opencv

pip install opencv-python

That should clear it up.

To exit Jupyter, close the notebook’s browser window, then click the “Quit” button from the directory page.

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