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es__we
Beginner
111 Views

When should I set the options tensorflow_use_custom_operations_config and tensorflow_object_detection_api_pipeline_config?

I have coverted some object detection models to IR format, in these cases, I do as follows:

python3 /opt/intel/openvino/deployment_tools/model_optimizer/mo_tf.py \
--input_model frozen_inference_graph.pb \
--data_type FP16 \
--reverse_input_channels \
--batch 1 \
--tensorflow_use_custom_operations_config  /opt/intel/deployment_tools/model_optimizer/extensions/front/tf/ssd_v2_support.json \
--tensorflow_object_detection_api_pipeline_config pipeline.config

It works, however, I also found that someone doesn't set these two parameters. What's more, I didn't modify the file path in pipline.config such as:

train_input_reader {
  label_map_path: "PATH_TO_BE_CONFIGURED/mscoco_label_map.pbtxt"
  tf_record_input_reader {
    input_path: "PATH_TO_BE_CONFIGURED/mscoco_train.record"
  }

Doesn't it matter?

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2 Replies
JesusE_Intel
Moderator
111 Views

Hi we,

Thanks for reaching out. The paths to be configured are only used when training the model. When using the Model Optimizer, you only need to specify the pipeline.config with the --tensorflow_object_detection_api_pipeline_config as you mentioned. 

Please let me know if this answers your question.

Regards,

Jesus

es__we
Beginner
111 Views

Thanks, I see, I feel the need to learn more about the document.

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