I ran head pose estimation model from GitHub - yinguobing/head-pose-estimation: Head pose estimation by TensorFlow and OpenCV and the values I get from the facial landmark model predictions are different in x86 and Xavier.In x86,the model works fine.
But when I run the model from the repo given above in the board,
I get this particular error :
mark_detector.py", line 208, in draw_marks
cv2.circle(image, (int(mark), int(mark)), 1, color, -1, cv2.LINE_AA)
OverflowError: Python int too large to convert to C long
There was no such error in x86.
I want to print the points in the image.I managed to bypass this error by typecasting.
Anyhow,the value returned by the model and x86 is different.
For x86, the values returned by the model are :
MARKS of 2020-10-14-110201_20.jpg
[0.09862911 0.2954145 ]
[0.09967319 0.41962394] … and so on
Where as in Xavier Nx it is,
MARKS of 2020-10-14-110201_14.jpg
[-7.28711919e+33 -9.70447565e+33] … and so on
Please provide suggestions on how to resolve this issue.
TensorRT Version : 184.108.40.206
Nvidia Driver Version : 32.4.3
CUDA Version : 10.2.89
CUDNN Version : 8.0.0
Operating System + Version : Ubuntu 18.04.5 LTS
Python Version : python3.6
TensorFlow Version : 1.15.2
Jetpack version - 4.4
keras version - 2.1.5