def pil_to_ipl(im_pil):
im_ipl = cvCreateImageHeader(cvSize(im_pil.size[0], im_pil.size[1]),
IPL_DEPTH_8U, 3)
data = im_pil.tostring('raw', 'RGB', im_pil.size[0] * 3)
cvSetData(im_ipl, cast(data, POINTER(c_byte)), im_pil.size[0] * 3)
cvCvtColor(im_ipl, im_ipl, CV_RGB2BGR)
im_ipl._depends = (data, )
return im_ipl
def __init__(self, parent, img):
wx.Panel.__init__(self, parent, -1)
# Convert the raw image data to something wxpython can handle.
cv.cvCvtColor(img, img, cv.CV_BGR2RGB)
self.bmp = wx.BitmapFromBuffer(img.width, img.height,\
img.imageData)
# Display the resulting image
sbmp = wx.StaticBitmap(self, -1, bitmap=self.bmp)
def pil_to_ipl(im_pil):
im_ipl = cvCreateImageHeader(cvSize(im_pil.size[0], im_pil.size[1]),
IPL_DEPTH_8U, 3)
data = im_pil.tostring('raw', 'RGB', im_pil.size[0] * 3)
cvSetData(im_ipl, cast(data, POINTER(c_byte)), im_pil.size[0] * 3)
cvCvtColor(im_ipl, im_ipl, CV_RGB2BGR)
im_ipl._depends = (data,)
return im_ipl
def run(self): if self.capture: webcam_frame = cv.QueryFrame( self.capture ) else: print "Capture failed!" return if self.inverted_video.get_active(): cv.ConvertImage(webcam_frame, webcam_frame, cv._CVTIMG_FLIP) cv.ConvertImage(webcam_frame, self.display_frame, cv._CVTIMG_SWAP_RB) if False: # PROCESS WEBCAM FRAME HERE... inputImage = cv.cvCreateImage(cv.cvGetSize(webcam_frame), cv.IPL_DEPTH_8U, 1) cv.cvCvtColor(webcam_frame, inputImage, cv.CV_RGB2GRAY); cv.cvThreshold(inputImage, inputImage, 128, 255, cv.CV_THRESH_BINARY) mysize = cv.cvGetSize(webcam_frame) height = mysize.height width = mysize.width # Find horizontal first-moment: if False: mysum = 0 for i in range(height): mysum += sum(inputImage[i,:]) print "Sum:", mysum cv.cvMerge( inputImage, inputImage, inputImage, None, self.display_frame ) incoming_pixbuf = gtk.gdk.pixbuf_new_from_data( self.display_frame.imageData, gtk.gdk.COLORSPACE_RGB, False, 8, self.display_frame.width, self.display_frame.height, self.display_frame.widthStep) incoming_pixbuf.copy_area(0, 0, self.display_frame.width, self.display_frame.height, self.webcam_pixbuf, 0, 0) self.video_image.queue_draw() return self.video_enabled_button.get_active()
def pil_to_ipl(im_pil):
"""Converts a PIL.Image into an IplImage
This function may be obsolete. Use cvCreateImageFromPilImage() instead.
"""
im_ipl = cvCreateImageHeader(cvSize(im_pil.size[0], im_pil.size[1]),
IPL_DEPTH_8U, 3)
data = im_pil.tostring('raw', 'RGB', im_pil.size[0] * 3)
cvSetData(im_ipl, cast(data, POINTER(c_byte)), im_pil.size[0] * 3)
cvCvtColor(im_ipl, im_ipl, CV_BGR2RGB)
im_ipl._depends = (data,)
return im_ipl
def pil_to_ipl(im_pil):
"""Converts a PIL.Image into an IplImage
This function may be obsolete. Use cvCreateImageFromPilImage() instead.
"""
im_ipl = cvCreateImageHeader(cvSize(im_pil.size[0], im_pil.size[1]),
IPL_DEPTH_8U, 3)
data = im_pil.tostring('raw', 'RGB', im_pil.size[0] * 3)
cvSetData(im_ipl, cast(data, POINTER(c_byte)), im_pil.size[0] * 3)
cvCvtColor(im_ipl, im_ipl, CV_BGR2RGB)
im_ipl._depends = (data,)
return im_ipl
def Ipl2NumPy(input):
"""Converts an OpenCV image to a numpy array.
Supported input image formats are
IPL_DEPTH_8U x 1 channel
IPL_DEPTH_8U x 3 channels
IPL_DEPTH_32F x 1 channel
IPL_DEPTH_32F x 2 channels
IPL_DEPTH_32S x 1 channel
IPL_DEPTH_64F x 1 channel
IPL_DEPTH_64F x 2 channels
"""
import ipdb
ipdb.set_trace()
if not isinstance(input, cv.CvMat):
raise TypeError, 'must be called with a cv.CvMat!'
# data type dictionary:
# (channels, depth) : numpy dtype
ipl2dtype = {
(1, cv.IPL_DEPTH_8U): numpy.uint8,
(3, cv.IPL_DEPTH_8U): numpy.uint8,
(1, cv.IPL_DEPTH_32F): numpy.float32,
(2, cv.IPL_DEPTH_32F): numpy.float32,
(1, cv.IPL_DEPTH_32S): numpy.int32,
(1, cv.IPL_DEPTH_64F): numpy.float64,
(2, cv.IPL_DEPTH_64F): numpy.float64
}
key = (input.nChannels, input.depth)
if not ipl2dtype.has_key(key):
raise ValueError, 'unknown or unsupported input mode'
# Get the numpy array and reshape it correctly
# ATTENTION: flipped dimensions width/height on 2007-11-15
if input.nChannels == 1:
array_1d = numpy.fromstring(input.imageData, dtype=ipl2dtype[key])
return numpy.reshape(array_1d, (input.height, input.width))
elif input.nChannels == 2:
array_1d = numpy.fromstring(input.imageData, dtype=ipl2dtype[key])
return numpy.reshape(array_1d, (input.height, input.width, 2))
elif input.nChannels == 3:
# Change the order of channels from BGR to RGB
rgb = cv.cvCreateImage(cv.cvSize(input.width, input.height),
input.depth, 3)
cv.cvCvtColor(input, rgb, cv.CV_BGR2RGB)
array_1d = numpy.fromstring(rgb.imageData, dtype=ipl2dtype[key])
return numpy.reshape(array_1d, (input.height, input.width, 3))
def Ipl2NumPy(input):
"""Converts an OpenCV image to a numpy array.
Supported input image formats are
IPL_DEPTH_8U x 1 channel
IPL_DEPTH_8U x 3 channels
IPL_DEPTH_32F x 1 channel
IPL_DEPTH_32F x 2 channels
IPL_DEPTH_32S x 1 channel
IPL_DEPTH_64F x 1 channel
IPL_DEPTH_64F x 2 channels
"""
import ipdb
ipdb.set_trace()
if not isinstance(input, cv.CvMat):
raise TypeError, "must be called with a cv.CvMat!"
# data type dictionary:
# (channels, depth) : numpy dtype
ipl2dtype = {
(1, cv.IPL_DEPTH_8U): numpy.uint8,
(3, cv.IPL_DEPTH_8U): numpy.uint8,
(1, cv.IPL_DEPTH_32F): numpy.float32,
(2, cv.IPL_DEPTH_32F): numpy.float32,
(1, cv.IPL_DEPTH_32S): numpy.int32,
(1, cv.IPL_DEPTH_64F): numpy.float64,
(2, cv.IPL_DEPTH_64F): numpy.float64,
}
key = (input.nChannels, input.depth)
if not ipl2dtype.has_key(key):
raise ValueError, "unknown or unsupported input mode"
# Get the numpy array and reshape it correctly
# ATTENTION: flipped dimensions width/height on 2007-11-15
if input.nChannels == 1:
array_1d = numpy.fromstring(input.imageData, dtype=ipl2dtype[key])
return numpy.reshape(array_1d, (input.height, input.width))
elif input.nChannels == 2:
array_1d = numpy.fromstring(input.imageData, dtype=ipl2dtype[key])
return numpy.reshape(array_1d, (input.height, input.width, 2))
elif input.nChannels == 3:
# Change the order of channels from BGR to RGB
rgb = cv.cvCreateImage(cv.cvSize(input.width, input.height), input.depth, 3)
cv.cvCvtColor(input, rgb, cv.CV_BGR2RGB)
array_1d = numpy.fromstring(rgb.imageData, dtype=ipl2dtype[key])
return numpy.reshape(array_1d, (input.height, input.width, 3))
def test05_Ipl2NumPy(self):
"""Test the adaptors.Ipl2NumPy function."""
a = adaptors.Ipl2NumPy(self.ipl_image)
a_1d = numpy.reshape(a, (a.size, ))
# For 3-channel IPL images the order of channels will be BGR
# but NumPy array order of channels will be RGB so a conversion
# is needed before we can compare both images
if self.ipl_image.nChannels == 3:
rgb = cv.cvCreateImage(cv.cvSize(self.ipl_image.width, self.ipl_image.height), self.ipl_image.depth, 3)
cv.cvCvtColor(self.ipl_image, rgb, cv.CV_BGR2RGB)
self.assert_(a_1d.tostring() == rgb.imageData,
'The returned image has not been properly constructed.')
else:
self.assert_(a_1d.tostring() == self.ipl_image.imageData,
'The returned image has not been properly constructed.')
def Ipl2NumPy(input):
"""Converts an OpenCV/IPL image to a numpy array.
Supported input image formats are
IPL_DEPTH_8U x 1 channel
IPL_DEPTH_8U x 3 channels
IPL_DEPTH_32F x 1 channel
IPL_DEPTH_64F x 1 channel
"""
if not isinstance(input, cv.CvMat):
raise TypeError, 'must be called with a cv.CvMat!'
# assert that the channels are interleaved
if input.dataOrder != 0:
raise ValueError, 'dataOrder must be 0 (interleaved)!'
# data type dictionary:
# (channels, depth) : numpy dtype
ipl2dtype = {
(1, cv.IPL_DEPTH_8U) : numpy.uint8,
(3, cv.IPL_DEPTH_8U) : numpy.uint8,
(1, cv.IPL_DEPTH_32F) : numpy.float32,
(1, cv.IPL_DEPTH_64F) : numpy.float64
}
key = (input.nChannels, input.depth)
if not ipl2dtype.has_key(key):
raise ValueError, 'unknown or unsupported input mode'
# Get the numpy array and reshape it correctly
if input.nChannels == 1:
array_1d = numpy.fromstring(input.imageData, dtype=ipl2dtype[key])
return numpy.reshape(array_1d, (input.height, input.width))
elif input.nChannels == 3:
# Change the order of channels from BGR to RGB
rgb = cv.cvCreateImage(cv.cvSize(input.width, input.height), input.depth, 3)
cv.cvCvtColor(input, rgb, cv.CV_BGR2RGB)
array_1d = numpy.fromstring(rgb.imageData, dtype=ipl2dtype[key])
return numpy.reshape(array_1d, (input.height, input.width, 3))
