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Hello everyone I trained MobileNet_SSD_v2 on custom dataset. I run the frozen_inference_graph.pb file on my pc got after training the model . The frozen_inference_graph.pb is working good it is detecting multiple person and the detection rate is quite good but when i convert .pb file into IR the results are very poor it is not detecting multiple person and detecting other objects as person class.
Libraries version while training MobileNet_SSD_v2 :
TensorFlow Version : 1.15.2
.pb file to IR conversion software version:
openvino : 2020.4
NCS2
TensorFlow Version : 1.15.2
Code to convert frozen graph to IR :
sudo python3 mo_tf.py --input_model ~/Downloads/fine_tuned_model/frozen_inference_graph.pb --tensorflow_use_custom_operations_config /opt/intel/openvino_2020.4.287/deployment_tools/model_optimizer/extensions/front/tf/ssd_support.json --tensorflow_object_detection_api_pipeline_config ~/Downloads/fine_tuned_model/pipeline.config
Results got from frozen_inference_graph.pb :
Results got after conversion to IR :
I am using the code available in /opt/intel/openvino_2020.4.287/deployment_tools/inference_engine/samples/python/object_detection_sample_ssd/object_detection_sample_ssd.py for testing the IR convrted .xml and .bin file
Please help me out I am stuck at this point Thankyou !
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Hi SaadSaeed,
Thanks for reaching out.
From what we can see, you need to modify your model optimizer conversion command as follows :
- Since you are using custom dataset and TensorFlow version is 1.15, use ssd_support_api_v.1.15.json instead. You can refer here to check the list of json file with the supported topologies: https://docs.openvinotoolkit.org/latest/openvino_docs_MO_DG_prepare_model_convert_model_tf_specific_Convert_Object_Detection_API_Models.html
- Add the --input_shape and --reverse_input_channels parameters. For more information please refer to the following links. https://docs.openvinotoolkit.org/2020.4/openvino_docs_MO_DG_prepare_model_convert_model_Converting_Model_General.html#when_to_specify_input_shapes
Regards,
Aznie
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