Ground truth segmentation image in training phase seems to be invalid

I would also check the number of images. Obviously for single camera it should be 2 and you would expect segmentation mask to be index 1, might pay to check if 6 exist as per multi camera.

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Clarification on input sensors during evaluation

Any updates here? would be good to know before round 2 starts

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Clarification on input sensors during evaluation

After reading this thread I am still unclear about the availability of the ground truth segmentation masks during the “1 Hour” training period for round 2. It is clear they will not be available during the evaluation period.

After the code change for using multiple cameras this line in evaluator.py

self.check_for_allowed_sensors()

throws an exception when trying to add them to the sim environment.

Access to these masks is important for anyone using a segmentation model

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Clarification on input sensors during evaluation

Check that the sensors you want are enabled in the config.py file. See active_sensors, add the ones you want from the cameras dict in the Envconfig class.

class SimulatorConfig(object):
racetrack = “Thruxton”
active_sensors = [
“CameraFrontRGB”,
]
driver_params = {
“DriverAPIClass”: “VApiUdp”,
“DriverAPI_UDP_SendAddress”: “0.0.0.0”,
}
camera_params = {
“Format”: “ColorBGR8”,
“FOVAngle”: 90,
“Width”: 512,
“Height”: 384,
“bAutoAdvertise”: True,
}
vehicle_params = False

Hope this is helpful

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Need your Inputs for improving competition

Is there a way to view/playback submitted evaluations? It would be a great asset to be able to view these so that irregular behavior can be diagnosed. I understand it cannot be done for round 2. I have noticed large discrepancy between scores, performance and agent behavior in a local simulator versus the evaluation results used for grading, even if you reduce the frame rate to match the evaluation server.

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KeyError: ‘success_rate’

Hi @jyotish,

Could you please have a look at this problem, this error occurred today for my submission. The agent likely completed the entire course.

2022-02-04 07:46:05.823 | INFO | main:run_evaluation:81 - Starting evaluation on Thruxton racetrack
2022-02-04 07:46:09.866 | INFO | aicrowd_gym.clients.base_oracle_client:register_agent:210 - Registering agent with oracle…
2022-02-04 07:46:09.868 | SUCCESS | aicrowd_gym.clients.base_oracle_client:register_agent:226 - Registered agent with oracle
/home/miniconda/lib/python3.9/site-packages/numpy/core/fromnumeric.py:3440: RuntimeWarning: Mean of empty slice.
return _methods._mean(a, axis=axis, dtype=dtype,
/home/miniconda/lib/python3.9/site-packages/numpy/core/_methods.py:189: RuntimeWarning: invalid value encountered in double_scalars
ret = ret.dtype.type(ret / rcount)

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