Metadata-Version: 2.1
Name: blackonnx
Version: 1.0.0
Summary: Adapt ONNX models to enable nnoir conversion
Home-page: https://github.com/Idein/nnoir/tree/master/blackonnx
Author: Idein Inc.
Author-email: christian@idein.jp
License: MIT
Description: # blackonnx
        
        This package purpose is to allow the use of NN models generated by AutoML services ([Google Cloud Vision](https://cloud.google.com/vision/overview/docs#automl-vision),
        [Azure custom Vision](https://azure.microsoft.com/en-us/services/cognitive-services/custom-vision-service/)),
        to an [Actcast](https://actcast.io/) application.
        
        The format for NN models in Actcast is [nnoir](https://github.com/Idein/nnoir), and the tool [nnoir-onnx](https://pypi.org/project/nnoir-onnx/) allows conversion from [ONNX](https://github.com/onnx/onnx) format to nnoir.
        
        Some ONNX operators used in AutoML-generated models may not be supported by nnoir-onnx, and using this package allows the conversion by modifying an onnx model by replacing unsupported nodes to equivalent supported ones.
        
        See #Examples section for use samples.
        
        ## Installation
        
        ```bash
        pip3 install blackonnx
        ```
        
        ## Usage
        
        In a python script:
        
        ```python
        import onnx
        from blackonnx import fix
        
        model = onnx.load("path/to/mymodel.onnx")  # open onnx model
        
        fix.fix_quantize(model)  # apply fixes in-place
        .
        .
        .
        
        onnx.save(model, "mymodel_fixed.onnx")  # save fixed model
        ```
        
        or using commd line:
        
        ```bash
        user~$ blackonnx -o mymodel_fixed.onnx path/to/mymodel.onnx --fixes fix_quantize 
        ```
        
        Omitting `fixes` argument applies all fixes (in alphabetical order).
        For models created with Google Cloud Vision, the recommanded fixes are
        
        ```bash
        ... --fixes fix_quantize 
        ```
        
        And for Azure custom vision models:
        
        ```bash
        ... --fixes fix_postprocess 
        ```
        
        ## Example
        
        Follow the instructions in `examples/tutorial.md` for details.
        
        ## Origin of the Name
        
        The name `blackonnx` comes from [black onyx](https://en.wikipedia.org/wiki/Onyx) because of the property: artificially colored to black. Our IR is nnoir, which comes from black in french.
        We mean this tool adapt onnx models for nnoir.
        
Keywords: Adapt ONNX models to enable nnoir conversion
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3 :: Only
Requires-Python: >=3.6.*
Description-Content-Type: text/markdown
