Three Types and Contents of Unmanned Autonomous Driving Data Labeling [Illustration]
What is autonomous driving data annotation?
Autonomous driving data annotation is the process of marking cars , people, and objects in images or videos by using bounding boxes and defining other attributes, and teaching the model to recognize traffic elements such as pedestrians, cars, traffic signs, etc., to help ML models understand and Identify objects detected by sensors in the vehicle.
The basis for realizing autonomous driving is artificial intelligence. What is the basis for realizing artificial intelligence? The answer is: automatic driving data labeling.
At present, autonomous driving urgently needs to solve four major problems: see (positioning, obstacle avoidance), hear (decision-making, control, execution), speak (path planning, driving mode), and have a brain (edge computing) .
Label content:
1. Motorcycle; 2. Bicycle; 3. Motorcyclist/cyclist; 4. Front and rear wheel lines; 5. Tricycle; 6. Pedestrian; 7. Traffic lights; 8. Traffic signs; 9. Indifferen...