I have a human flow detection project, human body detection + track tracking, which USES. TRT tensorRT for detection and. Pbfile tf for tracking.
Failure:
I. the Load tracking
Ii. The Load detection
Iii. Infer detection
Iv. Infer tracking
Success:
I. the Load detection
Ii. Infer detction
Iii. The Load tracking
Iv. Infer teacking
The failed detection model means that it will return 725 0.25 scores and incorrect boxes, as well as a classification value of 0
Sorry that we will need more information to give a further suggestion.
A possible cause is that most of the memory is occupied by the TensorFlow if loading the tracking model first.
And the occupation leads to some error in the inference.
Could you run the tegrastats to monitor the system status of each case and share it with us?