Docker of detect_objects_webcam

Accelerated Computing NGC GPU Cloud Docker and NVIDIA Docker
1

I’m trying to reproduce the result described in this tutorial: https://devblogs.nvidia.com/object-detection-gpus-10-minutes/, which uses a special docker image.
I pulled and ran the docker successful using ./setup_environment.sh, but when I called ‘python SSD_Model/detect_objects_webcam.py’ as instructed, I got the following error message:

root@b54ce065632c:/mnt# python SSD_Model/detect_objects_webcam.py
Traceback (most recent call last):
  File "SSD_Model/detect_objects_webcam.py", line 12, in <module>
    import utils.inference as inference_utils # TRT/TF inference wrappers
  File "/mnt/SSD_Model/utils/inference.py", line 57, in <module>
    import pycuda.autoinit
  File "/usr/local/lib/python3.5/dist-packages/pycuda/autoinit.py", line 9, in <module>
    context = make_default_context()
  File "/usr/local/lib/python3.5/dist-packages/pycuda/tools.py", line 204, in make_default_context
    "on any of the %d detected devices" % ndevices)
RuntimeError: make_default_context() wasn't able to create a context on any of the 1 detected devices

Anyone has any clue about this error?

2

Got same error. Tried the latest TRT image - same exception.
bob20001@ did you manage to fix that?

3

2020-02-17 13:08:10.628202: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.0
Traceback (most recent call last):
File “object.py”, line 59, in
label_map = label_map_util.load_labelmap(PATH_TO_LABELS)
File “/home/bluephin/_raishaf_ws/TensorFlow1/models/research/object_detection/utils/label_map_util.py”, line 137, in load_labelmap
with tf.gfile.GFile(path, ‘r’) as fid:
AttributeError: module ‘tensorflow’ has no attribute ‘gfile’