#Android support

[daggarwal01]

Does the YoloV5 weights (which are converted to .tflite format) are supported in android, for tensorflow lite implementation.

[github-actions]

Hello @daggarwal01, thank you for your interest in our work! Please visit our Custom Training Tutorial to get started, and see our Jupyter Notebook , Docker Image, and Google Cloud Quickstart Guide for example environments.

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[glenn-jocher]

@daggarwal01 export pipeline is pytorch > onnx > tflite. See the tutorials to get started: https://docs.ultralytics.com/yolov5

[daggarwal01]

I tried converting the weights using this pipeline,I succeed in converting it from .pt to .onnx and then to .pb, but while converting it into .tflite using the below mention code ,it showed me error. I looked for all the options but still stuck.

Convert the model.

converter = tf.lite.TFLiteConverter.from_frozen_graph("./models/model_simple.pb",input_arrays=['main_input'],output_arrays=['main_output'])
tf_lite_model = converter.convert()

Save the TF Lite model.

open('.models/model_simple.tflite', 'wb').write(tf_lite_model)

with tf.io.gfile.GFile('model.tflite', 'wb') as f:
f.write(tflite_model)

[glenn-jocher]

@daggarwal01 since this error was generated by external packages, the best place to raise an issue and ask questions regarding your error is on the relevant package repo.

[github-actions]

This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.