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

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