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Carlyon__Shane
Beginner
146 Views

OpenVINO Serving Container(NCS) - "Cannot find plugin to use" for YOLO V3 model

I converted the darknet YOLO V3 model into TF model using this - https://github.com/mystic123/tensorflow-yolo-v3.git  and optimized by this command:

python3 /opt/intel/openvino/deployment_tools/model_optimizer/mo_tf.py --input_model frozen_darknet_yolov3_model.pb --tensorflow_use_custom_operations_config /opt/intel/openvino/deployment_tools/model_optimizer/extensions/front/tf/yolo_v3.json --input_shape=[1,416,416,3] --data_type=FP16

 

Then I tried to serve this model with OpenVINO Serving Container(with NCS) by this command:

docker run --rm -d -it --net=host --privileged -v "$(pwd)"/models/:/opt/model:z -v /dev:/dev -e DEVICE=MYRIAD -p 9001:9001 intelaipg/openvino-model-server:latest /ie-serving-py/start_server.sh ie_serving model --model_path /opt/model/darknet_yolov3 --model_name darknet_yolov3 --port 9001

 

But I am getting this error from docker log:

2019-06-09 08:51:15,732 - ie_serving.models.model - INFO - Server start updating model: darknet_yolo_v3_ncs
2019-06-09 08:51:15,732 - ie_serving.models.model - INFO - Creating inference engine object for version: 1
2019-06-09 08:51:15,732 - ie_serving.models.model - ERROR - Error occurred while loading model version: {'xml_file': '/opt/model/darknet_yolo_v3_ncs/1/frozen_darknet_yolov3_model.xml', 'bin_file': '/opt/model/darknet_yolo_v3_ncs/1/frozen_darknet_yolov3_model.bin', 'mapping_config': None, 'version_number': 1, 'batch_size': None}
2019-06-09 08:51:15,732 - ie_serving.models.model - ERROR - Content error: Cannot find plugin to use :
2019-06-09 08:51:15,733 - ie_serving.models.model - INFO - List of available versions after updatefor darknet_yolo_v3_ncs model: []
2019-06-09 08:51:15,733 - ie_serving.models.model - INFO - Default version after updatefor darknet_yolo_v3_ncs model is -1

Any idea?

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2 Replies
Carlyon__Shane
Beginner
146 Views

UPDATED:

I even tried this link: https://software.intel.com/en-us/forums/computer-vision/topic/805370#comment-1934835

 

But I am getting this error this time:

work@work-MS-7788:~$ docker run --rm -d -it -v /home/work/Downloads/models:/opt/ml/:ro -p 9001:9001 intelaipg/openvino-model-server:latest /ie-serving-py/start_server.sh ie_serving model --model_path /opt/ml/darknet_yolov3 --model_name darknet_yolov3 --port 9001
d9b907250fe457fc8096f12913f39e71f8dfcebcc965237891986bed01fab841
work@work-MS-7788:~$ docker logs d9
2019-06-10 07:48:15,038 - ie_serving.main - INFO - Log level set: INFO
2019-06-10 07:48:15,038 - ie_serving.models.model - INFO - Server start loading model: darknet_yolov3
2019-06-10 07:48:15,040 - ie_serving.models.model - INFO - Creating inference engine object for version: 1
2019-06-10 07:48:15,053 - ie_serving.models.model - ERROR - Error occurred while loading model version: {'xml_file': '/opt/ml/darknet_yolov3/1/frozen_darknet_yolov3_model.xml', 'bin_file': '/opt/ml/darknet_yolov3/1/frozen_darknet_yolov3_model.bin', 'mapping_config': None, 'version_number': 1, 'batch_size': None}
2019-06-10 07:48:15,053 - ie_serving.models.model - ERROR - Content error: Error reading network: in Layer yolov3/convolutional2/Conv2D: trying to connect an edge to non existing output port: 2.1
2019-06-10 07:48:15,054 - ie_serving.models.model - INFO - List of available versions for darknet_yolov3 model: []
2019-06-10 07:48:15,054 - ie_serving.models.model - INFO - Default version for darknet_yolov3 model is -1
2019-06-10 07:48:15,060 - ie_serving.server.start - INFO - Server listens on port 9001 and will be serving models: ['darknet_yolov3']

 

Any idea?

Shubha_R_Intel
Employee
146 Views

Dear Carlyon, Shane,

The latest OpenVino release is 2019R1.1. Yolo v3 definitely works on it, though Tiny Yolo V3 is broken. Did you follow Tensorflow MO Yolo V3 steps ? Please try again with the latest and greatest OpenVino. I recently tried myself and I know that Yolo V3 (non-Tiny) works.

Glad that you resolved your "Can't find Plugin" problem. That is always related to your plugin binary directory not being in your $PATH variable.

Thanks,

Shubha

 

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