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Main project description

For more information about the system refer the pages:

• System - describing how all parts are working together to train and inference the models
• Cameras - how we created multiple cameras
• Convcam - what the Convcam is and how we use it
• Data Balancing - how are we balancing regression data
• NPCs - our custom NPCs playing in the GTA5 to collect data automatically
• Purpose - a way to let the model “know” where to drive
• Storage and Buffer - how are we managing the training data and why random batches are important
• Unstuck - how to make the car not be stuck anywhere

For more information about the model architectures used refer the pages:

• Xception - the first CNN backbone architecture used
• InceptionResNetv2 - the second, more successful CNN backbone architecture used