[Question] Resizeable models

[pinto0309]

[Question] Resizeable models

[PINTO0309]

The tool is designed to optimize the model to the limit for low-spec edge devices, so there are no plans to support variable resolution or variable batches at this time. This may be implemented in the future.

[a-storm]

Hi! Is it still impossible to convert model with variable batch size from OV to TF?

[PINTO0309]

• OpenVINO -> ONNX
  https://github.com/PINTO0309/openvino2tensorflow

• ONNX ->sbi4onnx -> N batch ONNX
  https://github.com/PINTO0309/simple-onnx-processing-tools

• N batch ONNX -> TF

$ onnx-tf convert -i mobileone_s0_Nx3xHxW.onnx -o saved_model

/usr/local/lib/python3.8/dist-packages/tensorflow_addons/utils/ensure_tf_install.py:53: UserWarning: Tensorflow Addons supports using Python ops for all Tensorflow versions above or equal to 2.3.0 and strictly below 2.5.0 (nightly versions are not supported). 
 The versions of TensorFlow you are currently using is 2.9.0 and is not supported. 
Some things might work, some things might not.
If you were to encounter a bug, do not file an issue.
If you want to make sure you're using a tested and supported configuration, either change the TensorFlow version or the TensorFlow Addons's version. 
You can find the compatibility matrix in TensorFlow Addon's readme:
https://github.com/tensorflow/addons
  warnings.warn(
2022-07-29 20:04:51,012 - onnx-tf - INFO - Start converting onnx pb to tf saved model
WARNING:absl:Found untraced functions such as gen_tensor_dict while saving (showing 1 of 1). These functions will not be directly callable after loading.
2022-07-29 20:05:07,449 - onnx-tf - INFO - Converting completes successfully.
INFO:onnx-tf:Converting completes successfully.

$ saved_model_cli show --dir saved_model/ --all

MetaGraphDef with tag-set: 'serve' contains the following SignatureDefs:

signature_def['__saved_model_init_op']:
  The given SavedModel SignatureDef contains the following input(s):
  The given SavedModel SignatureDef contains the following output(s):
    outputs['__saved_model_init_op'] tensor_info:
        dtype: DT_INVALID
        shape: unknown_rank
        name: NoOp
  Method name is: 

signature_def['serving_default']:
  The given SavedModel SignatureDef contains the following input(s):
    inputs['input'] tensor_info:
        dtype: DT_FLOAT
        shape: (-1, 3, -1, -1)
        name: serving_default_input:0
  The given SavedModel SignatureDef contains the following output(s):
    outputs['184'] tensor_info:
        dtype: DT_FLOAT
        shape: (-1, 1000)
        name: StatefulPartitionedCall:0
  Method name is: tensorflow/serving/predict

Concrete Functions:
  Function Name: '__call__'
        Named Argument #1
          input

  Function Name: 'gen_tensor_dict'