CODEWITHSUNDEEP
pythontensorflowtensorflow-lite
Rodrigo Laguna
Rodrigo Laguna

Reputation: 1850

How to extract metadata from tflite model

I'm loading this object detection model in python. I can load it with the following lines of code:

import tflite_runtime.interpreter as tflite

model_path = 'path_to_model_file.tf'
interpreter = tflite.Interpreter(model_path)

I'm able to perform inferences on this without any problem. However, labels are suposed to be included in the metadata, according to model's documentation, but I can't extract it.

The closest I was, it was when following this:

from tflite_support import metadata as _metadata

displayer = _metadata.MetadataDisplayer.with_model_file(model_path)
export_json_file = "extracted_metadata.json")
json_file = displayer.get_metadata_json()

# Optional: write out the metadata as a json file
with open(export_json_file, "w") as f:
  f.write(json_file)

but the very first line of code, fails with this error: {AtributeError}'int' object has no attribute 'tobytes'.

How to extract it?

Upvotes: 3

Views: 5841

Answers (1)

Lu Wang
Lu Wang

Reputation: 484

If you only care about the label file, you can simply run command like unzip model_path on Linux or Mac. TFLite model with metadata is essentially a zip file. See the public introduction for more details.

You code snippet to extract metadata works on my end. Make sure to double check model_path. It should be a string, such as "lite-model_ssd_mobilenet_v1_1_metadata_2.tflite".

If you'd like to read label files in an Android app, here is the sample code to do so.

Upvotes: 4

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