google.protobuf.message.DecodeError: Error parsing message

[xuexuqin]

python ./examples/object_detector.py
/root/anaconda3/lib/python3.6/site-packages/h5py/init.py:36: FutureWarning: Conversion of the second argument of issubdtype from float to np.floating is deprecated. In future, it will be treated as np.float64 == np.dtype(float).type.
from ._conv import register_converters as _register_converters
2020-03-25 16:28:09,270 - root - INFO - Allocated processes for 6 tasks
2020-03-25 16:28:09,272 - root - INFO - Started running flow.
Process Process-3:
Traceback (most recent call last):
File "/root/anaconda3/lib/python3.6/multiprocessing/process.py", line 258, in _bootstrap
self.run()
File "/root/anaconda3/lib/python3.6/multiprocessing/process.py", line 93, in run
self._target(*self._args, **self._kwargs)
File "/root/anaconda3/lib/python3.6/site-packages/videoflow-0.2.10-py3.6.egg/videoflow/engines/task_functions.py", line 15, in task_executor_fn
task.run()
File "/root/anaconda3/lib/python3.6/site-packages/videoflow-0.2.10-py3.6.egg/videoflow/core/task.py", line 88, in run
self._computation_node.open()
File "/root/anaconda3/lib/python3.6/site-packages/videoflow_contrib_detector_tf-0.1-py3.6.egg/videoflow_contrib/detector_tf/tf_object_detector.py", line 148, in open
device_id = device_id
File "/root/anaconda3/lib/python3.6/site-packages/videoflow_contrib_detector_tf-0.1-py3.6.egg/videoflow_contrib/detector_tf/tensorflow_utils.py", line 86, in init
self._load_model()
File "/root/anaconda3/lib/python3.6/site-packages/videoflow_contrib_detector_tf-0.1-py3.6.egg/videoflow_contrib/detector_tf/tensorflow_utils.py", line 99, in _load_model
graph_def.ParseFromString(serialized_graph)
google.protobuf.message.DecodeError: Error parsing message

[jadielam]

Are you getting this error running the DOckerfile, or installing it in your computer manually? If you are installing manually in your computer, what version of tensorflow are you using?

[xuexuqin]

I install it in my computer manually,and the tensorflow is 1.11.0,the python is 3.6,4

[jadielam]

You should use the same version of tensorflow that appears in the Dockerfile (1.14). Also, I would highly recommend that you use Docker to run examples instead of installing manually. If you do so, you will remove the pain of having to battle incompabilities of versions of the multiple libraries that you may have in your computer.