def array_to_qimage(arr, copy=False):
"""Convert NumPy array to QImage object"""
# https://gist.githubusercontent.com/smex/5287589/raw/toQImage.py
if arr is None:
return QImage()
if len(arr.shape) not in (2, 3):
raise NotImplementedError("Unsupported array shape %r" % arr.shape)
data = arr.data
ny, nx = arr.shape[:2]
stride = arr.strides[0] # bytes per line
color_dim = None
if len(arr.shape) == 3:
color_dim = arr.shape[2]
if arr.dtype == np.uint8:
if color_dim is None:
qimage = QImage(data, nx, ny, stride, QImage.Format_Indexed8)
# qimage.setColorTable([qRgb(i, i, i) for i in range(256)])
qimage.setColorCount(256)
elif color_dim == 3:
qimage = QImage(data, nx, ny, stride, QImage.Format_RGB888)
elif color_dim == 4:
qimage = QImage(data, nx, ny, stride, QImage.Format_ARGB32)
else:
raise TypeError("Invalid third axis dimension (%r)" % color_dim)
elif arr.dtype == np.uint32:
qimage = QImage(data, nx, ny, stride, QImage.Format_ARGB32)
else:
raise NotImplementedError("Unsupported array data type %r" % arr.dtype)
if copy:
return qimage.copy()
return qimage
def oldToQImage(array):
"""Converts a numpy array to a QImage
A Python version of PyQt4.Qwt5.toQImage(array) in PyQwt < 5.2.
Function written by Gerard Vermeulen
"""
if array.ndim != 2:
raise RuntimeError('array must be 2-D')
nx, ny = array.shape # width, height
xstride, ystride = array.strides
if array.dtype == numpy.uint8:
image = QImage(nx, ny, QImage.Format_Indexed8)
f_array = numpy.reshape(array,(nx*ny,),order='F')
for j in range(ny):
pointer = image.scanLine(j)
pointer.setsize(nx*array.itemsize)
memory = numpy.frombuffer(pointer, numpy.uint8)
first_value = j*nx
last_value = (j+1)*nx
memory[:] = f_array[first_value:last_value]
image.setColorCount(256)
for i in range(256):
image.setColor(i, qRgb(i, i, i))
return image
elif array.dtype == numpy.uint32:
image = Qt.QImage(
array.tostring(), width, height, Qt.QImage.Format_ARGB32)
f_array = numpy.reshape(array,(nx*ny,),order='F')
for j in xrange(ny):
pointer = image.scanLine(j)
pointer.setsize(nx*array.itemsize)
memory = numpy.frombuffer(pointer, numpy.uint32)
first_value = j*nx
last_value = (j+1)*nx
memory[:] = f_array[first_value:last_value]
return image
else:
raise RuntimeError('array.dtype must be uint8 or uint32')
