def create_image(self, buffer, create_alpha=True):
self.extension = self.extension or '.tif'
self.no_data_value = None
# FIXME: opencv doesn't support gifs, even worse, the library
# segfaults when trying to decoding a gif. An exception is a
# less drastic measure.
try:
if FORMATS[self.extension] == 'GIF':
raise ValueError("opencv doesn't support gifs")
except KeyError:
pass
if FORMATS[self.extension] == 'TIFF':
self.buffer = buffer
img0 = self.read_tiff(buffer, create_alpha)
else:
imagefiledata = cv.CreateMatHeader(1, len(buffer), cv.CV_8UC1)
cv.SetData(imagefiledata, buffer, len(buffer))
img0 = cv.DecodeImageM(imagefiledata, cv.CV_LOAD_IMAGE_UNCHANGED)
if FORMATS[self.extension] == 'JPEG':
try:
info = JpegFile.fromString(buffer).get_exif()
if info:
self.exif = info.data
self.exif_marker = info.marker
except Exception:
pass
return img0
def get_sample(filename, iscolor=cv.CV_LOAD_IMAGE_COLOR):
image_cache = {}
if not filename in image_cache:
#filedata = filename
imagefiledata = cv.CreateMatHeader(1, len(filedata), cv.CV_8UC1)
cv.SetData(imagefiledata, filedata, len(filedata))
image_cache[filename] = cv.DecodeImageM(imagefiledata, iscolor)
return image_cache[filename]
def image_from_archive(archive, name):
"""
Load image PGM file from tar archive.
Used for tarfile loading and unit test.
"""
member = archive.getmember(name)
filedata = archive.extractfile(member).read()
imagefiledata = cv.CreateMat(1, len(filedata), cv.CV_8UC1)
cv.SetData(imagefiledata, filedata, len(filedata))
return cv.DecodeImageM(imagefiledata)
def png_buf_to_opencv(filedata):
imagefiledata = cv.CreateMat(1, len(filedata), cv.CV_8UC1)
cv.SetData(imagefiledata, filedata, len(filedata))
return cv.DecodeImageM(imagefiledata)
cv.Copy(tmp, q1)
cv.Copy(q4, tmp)
cv.Copy(q2, q4)
cv.Copy(tmp, q2)
if __name__ == "__main__":
if len(sys.argv) > 1:
im = cv.LoadImage(sys.argv[1], cv.CV_LOAD_IMAGE_GRAYSCALE)
else:
url = 'https://code.ros.org/svn/opencv/trunk/opencv/samples/c/baboon.jpg'
filedata = urllib2.urlopen(url).read()
imagefiledata = cv.CreateMatHeader(1, len(filedata), cv.CV_8UC1)
cv.SetData(imagefiledata, filedata, len(filedata))
im = cv.DecodeImageM(imagefiledata, cv.CV_LOAD_IMAGE_GRAYSCALE)
realInput = cv.CreateImage(cv.GetSize(im), cv.IPL_DEPTH_64F, 1)
imaginaryInput = cv.CreateImage(cv.GetSize(im), cv.IPL_DEPTH_64F, 1)
complexInput = cv.CreateImage(cv.GetSize(im), cv.IPL_DEPTH_64F, 2)
cv.Scale(im, realInput, 1.0, 0.0)
cv.Zero(imaginaryInput)
cv.Merge(realInput, imaginaryInput, None, None, complexInput)
dft_M = cv.GetOptimalDFTSize(im.height - 1)
dft_N = cv.GetOptimalDFTSize(im.width - 1)
dft_A = cv.CreateMat(dft_M, dft_N, cv.CV_64FC2)
image_Re = cv.CreateImage((dft_N, dft_M), cv.IPL_DEPTH_64F, 1)
image_Im = cv.CreateImage((dft_N, dft_M), cv.IPL_DEPTH_64F, 1)
def lin2srgb(x):
a = 0.055
return numpy.where(x <= 0.0031308,
x * 12.92,
(1 + a) * numpy.power(x, 1 / 2.4) - a)
if __name__ == "__main__":
if len(sys.argv) > 1:
img0 = cv.LoadImageM( sys.argv[1], cv.CV_LOAD_IMAGE_COLOR)
else:
url = 'https://code.ros.org/svn/opencv/trunk/opencv/samples/c/lena.jpg'
filedata = urllib2.urlopen(url).read()
imagefiledata = cv.CreateMatHeader(1, len(filedata), cv.CV_8UC1)
cv.SetData(imagefiledata, filedata, len(filedata))
img0 = cv.DecodeImageM(imagefiledata, cv.CV_LOAD_IMAGE_COLOR)
cv.NamedWindow("original", 1)
cv.ShowImage("original", img0)
# Image was originally bytes in range 0-255. Turn it into an array of floats in range 0.0 - 1.0
n = numpy.asarray(img0) / 255.0
# Use NumPy to do some transformations on the image
# Negate the image by subtracting it from 1.0
cv.NamedWindow("negative")
cv.ShowImage("negative", cv.fromarray(1.0 - n))
# Assume the image was sRGB, and compute the linear version.
cv.NamedWindow("linear")
