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Identification

identify_document_is_signed(input, auto_fit=True)

Identify if the document is signed or not from an image.

Note

This method is not intended to be used for document verification, i.e. it does not check if the document is valid or not, and also does not collect any information from the document. It only verifies whether the document presents a signature or not.

Note

The method assumes that the signature is well seen in the image, i.e. it should be easily identified by a human eye.

Info

For the auto_fit option, If the input image is not consistent to the ML model input shape, then the method will fit it before prediction. If the user does not want this behavior, e.g. one may want to already provide an input data with the correct shape, then the user should set auto_fit to False.

Parameters:

Name Type Description Default
input array

An image representing the document with or without a signature.

 required
auto_fit bool

Fits the input shape to ML model needs. Defaults to True.

 True

Returns:

Name Type Description
tuple

The predicted document type and extra information.
Source code in cucaracha/tasks/identification.py 
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def identify_document_is_signed(input: np.array, auto_fit: bool = True):
    """
    Identify if the document is signed or not from an image.

    Note:
        This method is not intended to be used for document verification, i.e.
        it does not check if the document is valid or not, and also does not
        collect any information from the document. It only verifies whether
        the document presents a signature or not.

    Note:
        The method assumes that the signature is well seen in the image, i.e.
        it should be easily identified by a human eye.

    Info:
        For the `auto_fit` option, If the input image is not consistent to the
        ML model input shape, then the method will fit it before prediction.
        If the user does not want this behavior, e.g. one may want to already
        provide an input data with the correct shape, then the user should set
        `auto_fit` to `False`.

    Args:
        input (np.array): An image representing the document with or without a signature.
        auto_fit (bool, optional): Fits the input shape to ML model needs. Defaults to True.

    Returns:
        tuple: The predicted document type and extra information.
    """
    return call_cucacha_image_task(input, 'doc_is_signed', auto_fit)

identify_personal_document(input, auto_fit=True)

Identify the personal document type from an image, seting the document type based on the Brazilian personal documents such as CNH, CPF and RG.

If the document is not identified as CNH, CPF or RG, the method will return the string 'others' to exemplify an unrecognized document type.

Note

This method is not intended to be used for document verification, i.e. it does not check if the document is valid or not, and also does not collect any information from the document. It only identifies the type as CNH, CPF or RG.

Note

The method assumed that the input image is taken considering the majority of the image space of being as the document itself. Images with partial document or with a lot of noise may not be correctly identified.

Info

For the auto_fit option, If the input image is not consistent to the ML model input shape, then the method will fit it before prediction. If the user does not want this behavior, e.g. one may want to already provide an input data with the correct shape, then the user should set auto_fit to False.

Parameters:

Name Type Description Default
input array

An image representing the personal document.

 required
auto_fit bool

Fits the input shape to ML model needs. Defaults to True.

 True

Returns: tuple: The predicted document type and extra information.

Source code in cucaracha/tasks/identification.py 
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def identify_personal_document(input: np.array, auto_fit: bool = True):
    """
    Identify the personal document type from an image, seting the document
    type based on the Brazilian personal documents such as CNH, CPF and RG.

    If the document is not identified as CNH, CPF or RG, the method will return
    the string 'others' to exemplify an unrecognized document type.

    Note:
        This method is not intended to be used for document verification, i.e.
        it does not check if the document is valid or not, and also does not
        collect any information from the document. It only identifies the type
        as CNH, CPF or RG.

    Note:
        The method assumed that the input image is taken considering the
        majority of the image space of being as the document itself. Images
        with partial document or with a lot of noise may not be correctly
        identified.

    Info:
        For the `auto_fit` option, If the input image is not consistent to the
        ML model input shape, then the method will fit it before prediction.
        If the user does not want this behavior, e.g. one may want to already
        provide an input data with the correct shape, then the user should set
        `auto_fit` to `False`.

    Args:
        input (np.array): An image representing the personal document.
        auto_fit (bool, optional): Fits the input shape to ML model needs. Defaults to True.
    Returns:
        tuple: The predicted document type and extra information.
    """
    return call_cucacha_image_task(input, 'cnh_cpf_rg', auto_fit)