Metadata-Version: 2.1
Name: gradient-decode-dicom
Version: 0.0.5
Summary: Gradient Decode DICOM is a dicom image and tag reader op for TensorFlow
Home-page: https://github.com/gradienthealth/gradient_decode_dicom
Author: Marcelo Lerendegui
Author-email: marcelo@gradienthealth.io
License: Apache 2.0
Description: # TensorFlow Decode DICOM
        
        ## Operations
        
        Decode DICOM contains two Tensorflow Operations that allow reading information from DICOM files.
        
        ### Decode DICOM Image
            loads a dicom image file and returns its pixel information in the specified output format.
        
        ### Decode DICOM Data
            loads a dicom image file and returns a sting tensor with the values of each of the supplied tags.
        
        
        #### Inputs
        
        ##### contents:
            * Description: byte string with the file bytes. Use tf.io.read_file to read the file contents into a string.
            * Type: string
        
        #### Attributes
        
        ##### dtype:
            * Description: Type for the output tensor
            * Type: Dtype
            * Possible Values: uint8, uint16, uint32, uint64, float, float16, double
            * Default Value: uint16
        
        ##### color_dim:
            * Description: Whether or not to include the color_dimension. If decoded image is monochrome and this attribute is True the output tensor will have an extra singleton dimension for the color.
            * Type: Bool
            * Default Value: True
            
        ##### on_error:
            * Description: This attribute establishes the behavior in case an error occurs on opening the image or if the output type cannot accomodate all the possible input values. *'strict'* throws an error, *'skip'* returns 0 and *'lossy'* continues with the operation as if no error occurred.
            * Possible Values: 'strict', 'skip', 'lossy'
            * Default Value: 'skip'
        
        ##### scale:
            * Description: This attribute establishes what to do with the scale of the input values. *'auto'* will autoscale the input values, if the output type is integer, *'auto'* will use the maximum output scale, if the output is float, *'auto'* will scale to [0,1]. *'preserve'* keeps the values as they are, an input value greater than the maximum possible output will be clipped.  
            * Possible Values: 'auto', 'preserve'
            * Default Value: 'preserve'
        
        #### Outputs
        
        ##### output:
            * Description: Pixel data of the DICOM image
            * Type: Tensor of selected type (see attribute dtype)
            * Dimensions: [F, I, J, C]
                * F: Number of frames
                * I: Number of rows
                * J: Number of columns
                * C: Color dimensions
        
        
        ## Installation
        
        ```bash
            pip install gradient-decode-dicom
        ```
        
Keywords: tensorflow dicom custom op machine learning
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: Software Development :: Libraries
Description-Content-Type: text/markdown
