Heute schauen wir uns mal die Version 9 von Tesla's Software an, die unter anderem auf neuronale Netze beim Autopiloten setzt.
Based on the new capabilities of Autopilot under version 9, we already knew that the new computer vision neural net had to be significantly updated.
It can now track vehicles and other objects all around the car – meaning that it makes better use of the 8 cameras around the car and not just the front-facing ones.
Now we have a better understanding of just how significant Tesla’s neural net update in version 9 is as TMC member Jimmy_d, a deep learning expert who has access to the software and has been releasing his thoughts on each update, has produced an interesting analysis on version 9.
Jimmy confirmed that Tesla has now deployed a new unified camera network that handles all 8 cameras.
He also listed a few other main changes:Same weight file being used for all cameras (this has pretty interesting implications and previously V8 main/narrow seems to have had separate weights for each camera)
Processed resolution of 3 front cameras and back camera: 1280×960 (full camera resolution)
Processed resolution of pillar and repeater cameras: 640×480 (1/2×1/2 of camera’s true resolution)
all cameras: 3 color channels, 2 frames (2 frames also has very interesting implications) (was 640×416, 2 color channels, 1 frame, only main and narrow in V8)
