In this project, you'll label the pixels of a road in images using a Fully Convolutional Network (FCN).

Make sure you have the following is installed:

• Python 3
• TensorFlow
• NumPy
• SciPy

Download the Kitti Road dataset from here. Extract the dataset in the data folder. This will create the folder data_road with all the training a test images.

Implement the code in the main.py module indicated by the "TODO" comments. The comments indicated with "OPTIONAL" tag are not required to complete.

Run the following command to run the project:

python main.py

Note If running this in Jupyter Notebook system messages, such as those regarding test status, may appear in the terminal rather than the notebook.

1. Ensure you've passed all the unit tests.
2. Ensure you pass all points on the rubric.
3. Submit the following in a zip file.

• helper.py
• main.py
• project_tests.py
• Newest inference images from runs folder (all images from the most recent run)

A well written README file can enhance your project and portfolio. Develop your abilities to create professional README files by completing this free course.