Convert model to tflite model

I want to run this code on raspberry pi 4. In the first step, I should convert this model to tflite model. I use the following link https://www.tensorflow.org/lite/convert/index to convert the model but it raises the following error. OSError: SavedModel file does not exist at: ./models/mobilenet-float16-stride16/{saved_model.pbtxt|saved_model.pb}

I also use the following code for model conversion python -m tf_bodypix \ convert-to-tflite \ --model-path \ "https://storage.googleapis.com/tfjs-models/savedmodel/bodypix/mobilenet/float/075/model-stride16.json" \ --optimize \ --quantization-type=float16 \ --output-model-file "./mobilenet-float16-stride16.tflite" it works and the model convert to tflite but when I want to use it in tensorflow lite based on this link https://www.tensorflow.org/lite/guide/inference, I found that the input model dimension is array([1, 1, 1, 3], dtype=int32). Can you help me to solve this problem?

[MrRiahi]

I created a pull request in the past few days.

[de-code]

What if you try to use the tflite model with tf-bodypix? If you pass a file ending with .tflite to the load_model method, then it should use the tflite API. You should also be able to use the CLI.

You can find the implementation in the code: https://github.com/de-code/python-tf-bodypix/blob/v0.3.8/tf_bodypix/model.py#L455-L504

The ranks of the input shapes are not always the same, and sometimes it is a 4D tensor, sometimes a 3D tensor (depending on the conversion method). If it is a 4D tensor and you can simply resize the tensor to make it 4D. In that case the first dimension will typically be the batch size. The other feature of tflite or the model is that the width and height is dynamic. With tflite you need to resize the actual tensor (see linked code block).