def toImage(self, array, origin=""):
"""
Converts an array with metadata to a two-dimensional image.
:param array array: The array to convert to image.
:param str origin: Path to the image, optional.
:return: a :class:`Row` that is a two dimensional image.
.. versionadded:: 2.3.0
"""
if array.ndim != 3:
raise ValueError("Invalid array shape")
height, width, nChannels = array.shape
ocvTypes = ImageSchema.ocvTypes
if nChannels == 1:
mode = ocvTypes["CV_8UC1"]
elif nChannels == 3:
mode = ocvTypes["CV_8UC3"]
elif nChannels == 4:
mode = ocvTypes["CV_8UC4"]
else:
raise ValueError("Invalid number of channels")
data = bytearray(array.astype(dtype=np.uint8).ravel())
# Creating new Row with _create_row(), because Row(name = value, ... )
# orders fields by name, which conflicts with expected schema order
# when the new DataFrame is created by UDF
return _create_row(self.imageFields,
[origin, height, width, nChannels, mode, data])
def toImage(array, path="", ocvType=16):
length = np.prod(array.shape)
data = bytearray(
array.astype(dtype=np.int8)[:, :, (2, 1, 0)].reshape(length))
height = array.shape[0]
width = array.shape[1]
# Creating new Row with _create_row(), because Row(name = value, ... ) orders fields by name,
# which conflicts with expected ImageSchema order when the new DataFrame is created by UDF
return _create_row(ImageFields, [path, height, width, ocvType, data])
def toImage(self, array: np.ndarray, origin: str = "") -> Row:
"""
Converts an array with metadata to a two-dimensional image.
Parameters
----------
array : :class:`numpy.ndarray`
The array to convert to image.
origin : str
Path to the image, optional.
Returns
-------
:class:`Row`
that is a two dimensional image.
.. versionadded:: 2.3.0
"""
if not isinstance(array, np.ndarray):
raise TypeError(
"array argument should be numpy.ndarray; however, it got [%s]."
% type(array))
if array.ndim != 3:
raise ValueError("Invalid array shape")
height, width, nChannels = array.shape
ocvTypes = ImageSchema.ocvTypes
if nChannels == 1:
mode = ocvTypes["CV_8UC1"]
elif nChannels == 3:
mode = ocvTypes["CV_8UC3"]
elif nChannels == 4:
mode = ocvTypes["CV_8UC4"]
else:
raise ValueError("Invalid number of channels")
# Running `bytearray(numpy.array([1]))` fails in specific Python versions
# with a specific Numpy version, for example in Python 3.6.0 and NumPy 1.13.3.
# Here, it avoids it by converting it to bytes.
if LooseVersion(np.__version__) >= LooseVersion("1.9"):
data = bytearray(array.astype(dtype=np.uint8).ravel().tobytes())
else:
# Numpy prior to 1.9 don't have `tobytes` method.
data = bytearray(array.astype(dtype=np.uint8).ravel())
# Creating new Row with _create_row(), because Row(name = value, ... )
# orders fields by name, which conflicts with expected schema order
# when the new DataFrame is created by UDF
return _create_row(self.imageFields,
[origin, height, width, nChannels, mode, data])
def toImage(self, array, origin=""):
"""
Converts an array with metadata to a two-dimensional image.
:param `numpy.ndarray` array: The array to convert to image.
:param str origin: Path to the image, optional.
:return: a :class:`Row` that is a two dimensional image.
.. versionadded:: 2.3.0
"""
if not isinstance(array, np.ndarray):
raise TypeError(
"array argument should be numpy.ndarray; however, it got [%s]." % type(array))
if array.ndim != 3:
raise ValueError("Invalid array shape")
height, width, nChannels = array.shape
ocvTypes = ImageSchema.ocvTypes
if nChannels == 1:
mode = ocvTypes["CV_8UC1"]
elif nChannels == 3:
mode = ocvTypes["CV_8UC3"]
elif nChannels == 4:
mode = ocvTypes["CV_8UC4"]
else:
raise ValueError("Invalid number of channels")
# Running `bytearray(numpy.array([1]))` fails in specific Python versions
# with a specific Numpy version, for example in Python 3.6.0 and NumPy 1.13.3.
# Here, it avoids it by converting it to bytes.
if LooseVersion(np.__version__) >= LooseVersion('1.9'):
data = bytearray(array.astype(dtype=np.uint8).ravel().tobytes())
else:
# Numpy prior to 1.9 don't have `tobytes` method.
data = bytearray(array.astype(dtype=np.uint8).ravel())
# Creating new Row with _create_row(), because Row(name = value, ... )
# orders fields by name, which conflicts with expected schema order
# when the new DataFrame is created by UDF
return _create_row(self.imageFields,
[origin, height, width, nChannels, mode, data])
def toImage(array, path = "", ocvType = 16):
"""
Converts a one-dimensional array to a 2 dimensional image
Args:
array (array):
path (str):
ocvType (int):
Returns:
object: 2 dimensional image
"""
length = np.prod(array.shape)
data = bytearray(array.astype(dtype=np.int8)[:,:,(2,1,0)].reshape(length))
height = array.shape[0]
width = array.shape[1]
# Creating new Row with _create_row(), because Row(name = value, ... ) orders fields by name,
# which conflicts with expected ImageSchema order when the new DataFrame is created by UDF
return _create_row(ImageFields, [path, height, width, ocvType, data])
def toImage(array, path="", mode=16):
"""
Converts a one-dimensional array to a 2 dimensional image
Args:
array (array):
path (str):
ocvType (int):
Returns:
object: 2 dimensional image
"""
length = np.prod(array.shape)
data = bytearray(array.astype(dtype=np.int8)[:, :, (2, 1, 0)].reshape(length))
height = array.shape[0]
width = array.shape[1]
# Creating new Row with _create_row(), because Row(name = value, ... ) orders fields by name,
# which conflicts with expected ImageSchema order when the new DataFrame is created by UDF
return _create_row(ImageFields, [path, height, width, 3, mode, data])
def toImage(self, array, origin=""):
"""
Converts an array with metadata to a two-dimensional image.
:param `numpy.ndarray` array: The array to convert to image.
:param str origin: Path to the image, optional.
:return: a :class:`Row` that is a two dimensional image.
.. versionadded:: 2.3.0
"""
if not isinstance(array, np.ndarray):
raise TypeError(
"array argument should be numpy.ndarray; however, it got [%s]."
% type(array))
if array.ndim != 3:
raise ValueError("Invalid array shape %s" % str(array.shape))
height, width, nChannels = array.shape
dtype = array.dtype
if not dtype in self._numpyToOcvMap:
raise ValueError(
"Unexpected/unsupported array data type '%s', currently only supported formats are %s"
% (str(array.dtype), str(self._numpyToOcvMap.keys())))
ocvName = "CV_%sC%d" % (self._numpyToOcvMap[dtype], nChannels)
ocvType = self.ocvTypeByName(ocvName)
# Running `bytearray(numpy.array([1]))` fails in specific Python versions
# with a specific Numpy version, for example in Python 3.6.0 and NumPy 1.13.3.
# Here, it avoids it by converting it to bytes.
data = bytearray(array.tobytes())
# Creating new Row with _create_row(), because Row(name = value, ... )
# orders fields by name, which conflicts with expected schema order
# when the new DataFrame is created by UDF
return _create_row(
self.imageFields,
[origin, height, width, nChannels, ocvType.mode, data])