Comments (5)
Correct! The conditional command here is a "target heatmap", which is the target point projected into the camera view. I found this to work a little better, but have yet to evaluate this quantitatively
from 2020_carla_challenge.
Thanks. Interesting result. I think there is less ambiguity when one use the target heatmap instead of the high level command. That may explain the performance gain if validated.
from 2020_carla_challenge.
Hi @bradyz can you explain a bit more about this target heatmap? I am really interested in knowing a bit more about it.
from 2020_carla_challenge.
So instead of using discrete commands, we render the project the future waypoint (this is typically pretty far, maybe 50 meters or so) into the first person view as a heatmap, then concatenate this to the RGB image.
from 2020_carla_challenge.
I see. This makes sense. Thank you for the quick response!
from 2020_carla_challenge.
Related Issues (20)
- Updated image model weights for CARLA 0.9.10 HOT 6
- Map not found Error while running a docker file in local machine
- Generation of Routes and Scenarios HOT 1
- Plotting image waypoints from the BEV perspective
- Is the data collected in map view? HOT 2
- Segmentation model weights? HOT 2
- route_19.xml, route_15, route_10 does not work HOT 7
- Not able to train STAGE_1 HOT 5
- The performance is not as good as LBC
- Does map model training use data augmentations?
- CoordConverter HOT 2
- Results of running a pretrained model is FAILURE HOT 2
- Where can I download the teacher model HOT 1
- Unknown error when submitting docker image to leaderboard benchmark HOT 2
- about sensormotor agent HOT 1
- the trained time took HOT 1
- Trying to update to work with CARLA 0.9.13 HOT 3
- cannot find image_agent.py HOT 2
- Pretrained Model Failed All with AgentBlocked
- About Converter world <--> cam conversion hack HOT 1
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from 2020_carla_challenge.