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"""This module provides conversions between numpy.ndarray and QImage
- :func:`convertArrayToQImage`
- :func:`convertQImageToArray`
"""
__authors__ = ["T. Vincent"]
__license__ = "MIT"
__date__ = "04/09/2018"
import sys
import numpy
from numpy.lib.stride_tricks import as_strided as _as_strided
from .. import qt
[docs]
def convertArrayToQImage(array: numpy.ndarray) -> qt.QImage:
"""Convert an array-like image to a QImage.
The created QImage is using a copy of the array data.
Limitation: Only RGB or RGBA images with 8 bits per channel are supported.
:param array: Array-like image data of shape (height, width, channels)
Channels are expected to be either RGB or RGBA.
:type array: numpy.ndarray of uint8
:return: Corresponding Qt image with RGB888 or ARGB32 format.
"""
array = numpy.array(array, copy=False, order="C", dtype=numpy.uint8)
if array.ndim != 3 or array.shape[2] not in (3, 4):
raise ValueError("Image must be a 3D array with 3 or 4 channels per pixel")
if array.shape[2] == 4:
format_ = qt.QImage.Format_ARGB32
# RGBA -> ARGB + take care of endianness
if sys.byteorder == "little": # RGBA -> BGRA
array = array[:, :, (2, 1, 0, 3)]
else: # big endian: RGBA -> ARGB
array = array[:, :, (3, 0, 1, 2)]
array = numpy.array(array, order="C") # Make a contiguous array
else: # array.shape[2] == 3
format_ = qt.QImage.Format_RGB888
height, width, depth = array.shape
qimage = qt.QImage(
array.data, width, height, array.strides[0], format_ # bytesPerLine
)
return qimage.copy() # Making a copy of the image and its data
[docs]
def convertQImageToArray(image: qt.QImage) -> numpy.ndarray:
"""Convert a QImage to a numpy array.
If QImage format is not one of:
- Format_Grayscale8
- Format_RGB888
- Format_RGBA8888
- Format_ARGB32,
it is first converted to one of this format.
The created numpy array is using a copy of the QImage data.
:param QImage image: The QImage to convert.
:return: Image array of uint8 of shape:
- (height, width) for grayscale images
- (height, width, channels (3 or 4)) for RGB and RGBA images
"""
supportedFormats = (
qt.QImage.Format_Grayscale8,
qt.QImage.Format_ARGB32,
qt.QImage.Format_RGB888,
qt.QImage.Format_RGBA8888,
)
# Convert to supported format if needed
if image.format() not in supportedFormats:
if image.hasAlphaChannel():
image = image.convertToFormat(qt.QImage.Format_RGBA8888)
else:
image = image.convertToFormat(qt.QImage.Format_RGB888)
format_ = image.format()
if format_ == qt.QImage.Format_Grayscale8:
channels = 1
elif format_ == qt.QImage.Format_RGB888:
channels = 3
else:
channels = 4
ptr = image.bits()
if qt.BINDING == "PyQt5":
ptr.setsize(image.byteCount())
elif qt.BINDING == "PyQt6":
ptr.setsize(image.sizeInBytes())
elif qt.BINDING == "PySide6":
ptr = ptr.tobytes()
else:
raise RuntimeError("Unsupported Qt binding: %s" % qt.BINDING)
# Create an array view on QImage internal data
view = _as_strided(
numpy.frombuffer(ptr, dtype=numpy.uint8),
shape=(image.height(), image.width(), channels),
strides=(image.bytesPerLine(), channels, 1),
)
if format_ == qt.QImage.Format_ARGB32:
# Convert from ARGB to RGBA
# Not a byte-ordered format: do care about endianness
if sys.byteorder == "little": # BGRA -> RGBA
view = view[:, :, (2, 1, 0, 3)]
else: # big endian: ARGB -> RGBA
view = view[:, :, (1, 2, 3, 0)]
if channels == 1: # Remove channel dimension
view = view[:, :, 0]
# Format_RGB888 and Format_RGBA8888 do not need reshuffling channels:
# They are byte-ordered and already in the right order
return numpy.array(view, copy=True, order="C")
