Onnx2tf

- Added to read from local test image data file if available in current working dir instead of getting from remote

What's Changed
* added to read from local test image data file if available in current working dir instead of getting from remote by dimalukas in https://github.com/PINTO0309/onnx2tf/pull/433
* v1.15.2 -> v1.15.3 by PINTO0309 in https://github.com/PINTO0309/onnx2tf/pull/434

New Contributors
* dimalukas made their first contribution in https://github.com/PINTO0309/onnx2tf/pull/433

**Full Changelog**: https://github.com/PINTO0309/onnx2tf/compare/1.15.2...1.15.3

- Add verbosity flag to provide better configuration of prints
- `non_verbose` just sets verbosity to "error" and is kept around for backwards compatibility.
- Merge Color into logging file
- Color objects are callable and wrap a string with the Color and Color.RESET
- `print` statements use the proper logging method

- `CI`
- Maximize free disk space

What's Changed
* Add verbosity flag and refactor logging by democat3457 in https://github.com/PINTO0309/onnx2tf/pull/431
* Maximize free disk space by PINTO0309 in https://github.com/PINTO0309/onnx2tf/pull/432

New Contributors
* democat3457 made their first contribution in https://github.com/PINTO0309/onnx2tf/pull/431

**Full Changelog**: https://github.com/PINTO0309/onnx2tf/compare/1.15.1...1.15.2

- Improved stability when models exceeding the ProtocolBuffers size limit of 2 GB are targeted for conversion.
- However, if the model size is about 4 GB, as in StableDiffusion, the conversion target is expected to require resources of about `128 GB RAM + 1 TB SWAP` or `512 GB RAM` or `1 TB RAM`, etc...
- Since it is not possible to prepare such a huge resource in the development environment, it is not possible to confirm that the conversion completes successfully.
- TensorFlow's `saved_model` format uses the same file format as ONNX ([Protocol Buffers](https://protobuf.dev/)), so it cannot generate models with file sizes larger than 2 GB.
- `ConstantOfShape`
- Improved stability of `ConstantOfShape` conversions
- [Conversion error with stable diffusion model. 424](https://github.com/PINTO0309/onnx2tf/issues/424)

What's Changed
* Improved stability when models exceeding the ProtocolBuffers size limit of 2 GB are targeted for conversion. by PINTO0309 in https://github.com/PINTO0309/onnx2tf/pull/428


**Full Changelog**: https://github.com/PINTO0309/onnx2tf/compare/1.15.0...1.15.1

- Support for `Float32` inverse conversion of `Float16` models.
- https://github.com/opencv/opencv_zoo
- [text_recognition_CRNN_EN_2023feb_fp16.onnx.zip](https://github.com/PINTO0309/onnx2tf/files/12178287/text_recognition_CRNN_EN_2023feb_fp16.onnx.zip)

What's Changed
* Support for `Float32` inverse conversion of `Float16` models by PINTO0309 in https://github.com/PINTO0309/onnx2tf/pull/427


**Full Changelog**: https://github.com/PINTO0309/onnx2tf/compare/1.14.7...1.15.0

- `acquisition_of_validation_data`
- Fix `acquisition_of_validation_data` to skip processing if the input tensor is a `tf.Tensor` and has the attribute `numpy`.
- `Inverse`
- Fixed to convert to `tf.Tensor` when the input tensor is `np.ndarray`.
- Improved overall stability of model conversion behavior

What's Changed
* Fix `acquisition_of_validation_data` to skip processing if the input tensor is a `tf.Tensor` and has the attribute `numpy`. by PINTO0309 in https://github.com/PINTO0309/onnx2tf/pull/423


**Full Changelog**: https://github.com/PINTO0309/onnx2tf/compare/1.14.6...1.14.7

- `Inverse`
- Fix Abort problem with Inverse transformations when the input tensor is `np.ndarray`.
- [[TODO] Fix Abort problem with Inverse transformations when the input tensor is np.ndarray. 421](https://github.com/PINTO0309/onnx2tf/issues/421)

What's Changed
* Fix Abort problem with Inverse transformations when the input tensor is np.ndarray by PINTO0309 in https://github.com/PINTO0309/onnx2tf/pull/422


**Full Changelog**: https://github.com/PINTO0309/onnx2tf/compare/1.14.5...1.14.6