Intel® Distribution of OpenVINO™ Toolkit
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YOLOV3 warnings

WU__Tianwen
New Contributor I
1,251 Views

hello everyone!

My openvino version is 2020.1. When i run yolov3,some warning happen:

DeprecationWarning: shape property of IENetLayer is deprecated. Please use shape property of DataPtr instead objects returned by in_data or out_data property to access shape of input or output data on corresponding ports
out_blob = out_blob.reshape(net.layers[net.layers[layer_name].parents[0]].shape)

Although it does not affect the operation of the program,but it will print every frame.maybe it will slow the program

 

What should I do to stop it from warning?

i have tried

import warnings

warnings.filterwarnings('ignore')

but it doesn't work.    should i install openvino2020.3?

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1 Solution
Sahira_Intel
Moderator
1,213 Views

Hi,

The latest version of the OpenVINO Toolkit (2020.3) still uses the out_data property to access DataPtr for all output ports. 

In general, I think printing the warnings after every frame would slow compilation time by a little bit.

Update: As you are in v2020.1, please try changing change line 276 to out_blob = out_blob.reshape(net.layers[net.layers[layer_name].parents[0]].out_data[0].shape) in object_detection_demo_yolov3_async.py script and see if DeprecationWarning persists.

I hope this information is helpful.

Best Regards,

Sahira 

link to Github thread: https://github.com/openvinotoolkit/openvino/issues/1118

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3 Replies
WU__Tianwen
New Contributor I
1,239 Views

here is the output of "/opt/intel/openvino_2020.1.023/deployment_tools/open_model_zoo/demos/python_demos/object_detection_demo_yolov3_async/object_detection_demo_yolov3_async.py" with my own model(two classes)

[ INFO ] Layer detector/yolo-v3/Conv_14/BiasAdd/YoloRegion parameters: 
[ INFO ]          classes : 2
[ INFO ]          num     : 3
[ INFO ]          coords  : 4
[ INFO ]          anchors : [30.0, 61.0, 62.0, 45.0, 59.0, 119.0]
/opt/intel/openvino_2020.1.023/deployment_tools/open_model_zoo/demos/python_demos/object_detection_demo_yolov3_async/object_detection_demo_yolov3_async.py:276: DeprecationWarning: shape property of IENetLayer is deprecated. Please use shape property of DataPtr instead objects returned by in_data or out_data property to access shape of input or output data on corresponding ports
  out_blob = out_blob.reshape(net.layers[net.layers[layer_name].parents[0]].shape)
[ INFO ] Layer detector/yolo-v3/Conv_22/BiasAdd/YoloRegion parameters: 
[ INFO ]          classes : 2
[ INFO ]          num     : 3
[ INFO ]          coords  : 4
[ INFO ]          anchors : [10.0, 13.0, 16.0, 30.0, 33.0, 23.0]
/opt/intel/openvino_2020.1.023/deployment_tools/open_model_zoo/demos/python_demos/object_detection_demo_yolov3_async/object_detection_demo_yolov3_async.py:276: DeprecationWarning: shape property of IENetLayer is deprecated. Please use shape property of DataPtr instead objects returned by in_data or out_data property to access shape of input or output data on corresponding ports
  out_blob = out_blob.reshape(net.layers[net.layers[layer_name].parents[0]].shape)

ubuntu 16.04
python 3.5.2
openvino 2020.1
CPU intel i5-8250U GPU UHD620
warning will happen on both CPU and GPU

https://docs.openvinotoolkit.org/2020.1/ie_python_api/classie__api_1_1IENetLayer.html the api allso mentioned this warning

https://docs.openvinotoolkit.org/2020.1/ie_python_api/classie__api_1_1DataPtr.html but the api doesn't describe DataPtr 's usage in detail .

I don’t know if DataPtr is used to replace IENetLayerin the latest version of yolov3 OpenVINO

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Sahira_Intel
Moderator
1,214 Views

Hi,

The latest version of the OpenVINO Toolkit (2020.3) still uses the out_data property to access DataPtr for all output ports. 

In general, I think printing the warnings after every frame would slow compilation time by a little bit.

Update: As you are in v2020.1, please try changing change line 276 to out_blob = out_blob.reshape(net.layers[net.layers[layer_name].parents[0]].out_data[0].shape) in object_detection_demo_yolov3_async.py script and see if DeprecationWarning persists.

I hope this information is helpful.

Best Regards,

Sahira 

link to Github thread: https://github.com/openvinotoolkit/openvino/issues/1118

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WU__Tianwen
New Contributor I
1,176 Views

Thanks!

This question on github was also initiated by me,and it really works,and YOLO parsing time takes less time!

Thanks for your reply!^-^

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