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ValueError in evaluation.py, the answer got from infer has a wrong number. #76
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You could employ post-processing techniques, such as rule-based methods, to address this situation. For instance, you could opt to retain only the initial 12 numbers. Subsequently, you could proceed with evaluating your answers. |
@DevLinyan Thanks for the reply. I still have doubts about the cause of this error. According to your reply, this error is not due to a model inference error, but due to a bug in the evaluation code? |
Same issues |
The error you're encountering is actually caused by your own model. Typically, the model should produce the even number as output. |
For those who have the same iisues. |
We checked again and find the error caused by the aborted answer of the LLM: answer= "There is a black sedan to the front of the ego vehicle, a black sedan to the back of the ego vehicle, a black sedan to the front of the ego vehicle, a black sedan to the back of the ego vehicle, a black sedan to the front of the ego vehicle, a black sedan to the back of the ego vehicle, and a black sedan to the front of the ego vehicle. The IDs of these objects are <c1,CAM_FRONT,1055.5,500.0>, <c2,CAM_BACK,1055.5,500.0>, <c3,CAM_FRONT,1055.5,500.0>, <c4,CAM_BACK,1055.5,500.0>, <c5,CAM_FRONT,1055.5,500.0>, <c6,CAM_BACK,1055.5,500.0>, and <c7,CAM_FRONT,1055.5,500"
GT= [1055.5, 500.0, 1055.5, 500.0, 1055.5, 500.0, 1055.5, 500.0, 1055.5, 500.0, 1055.5, 500.0, 1055.5]
answer_nums = re.findall(r'\d+\.\d+', answer)
GT_nums = re.findall(r'\d+\.\d+', GT) where the answer stoped at And if you just submit the answer toserver, it will cause the same error |
Running
evaluation.py
with error:The accurate answer format should be
[880.0, 500.0, 1000.0, 500.0, 1000.0, 500.0]
and reshape to[[ 880. 500.], [1000. 500.], [1000. 500.]]
But I got a
[1055.5, 510.0, 1055.5, 510.0, 1055.5, 510.0, 1055.5, 510.0, 1055.5, 510.0, 1055.5, 510.0, 1055.5]
with 13 numbers in my answer.I have no idea why it happens.
Please help
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