def NumpytoIM(img, usm=None, verbose=False):
if verbose:
print "Converting numpy array to ImageMagick"
out_img = PMImage()
if img.dtype == 'uint16':
out_img.depth(16)
else:
out_img.depth(8)
out_img.magick('RGB')
h,w,c = img.shape
size_str = str(w)+'x'+str(h)
out_img.size(size_str)
b = Blob()
b.data = img.tostring()
out_img.read(b)
out_img.magick('PNG')
# Check if USM sharpening should be used
if usm != None:
if verbose:
print "Running unsharp mask filter"
r,s,a,t = (usm)
out_img.unsharpmask(r,s,a,t)
return out_img
def thumbnail(self, infile, outfile, size, quality, no_upscale=False):
#image = Image(infile)
#image.resize(size)
#image.write(outfile)
quality = str(quality)
if infile.endswith('.gif') or no_upscale:
size = size+'>'
resize = run(['/usr/bin/convert', '-interlace', "Plane", '-quality', quality, '-strip', '-thumbnail', size, infile, outfile])
image = Image(outfile)
return { 'width': image.size().width(), \
'height': image.size().height() }
def thumbnail(self, infile, outfile, size, quality, no_upscale=False):
#image = Image(infile)
#image.resize(size)
#image.write(outfile)
quality = str(quality)
if infile.endswith('.gif') or no_upscale:
size = size + '>'
resize = run([
'/usr/bin/convert', '-interlace', "Plane", '-quality', quality,
'-strip', '-thumbnail', size, infile, outfile
])
image = Image(outfile)
return { 'width': image.size().width(), \
'height': image.size().height() }
def to_imagemagick(img, bits=16):
'''Convert numpy array to Imagemagick format.
:param img: image to convert
:type img: Numpy ndarray
:rtype: PythonMagick.Image
'''
if not isinstance(img, PMImage):
img = _scale(img, bits=bits)
LOGGER.debug("Converting from Numpy to ImageMagick.")
out_img = PMImage()
if img.dtype == np.uint8:
out_img.depth(8)
else:
out_img.depth(16)
shape = img.shape
# Convert also B&W images to 3-channel arrays
if len(shape) == 2:
tmp = np.empty((shape[0], shape[1], 3), dtype=img.dtype)
tmp[:, :, 0] = img
tmp[:, :, 1] = img
tmp[:, :, 2] = img
img = tmp
out_img.magick('RGB')
out_img.size(str(shape[1]) + 'x' + str(shape[0]))
blob = Blob()
blob.data = img.tostring()
out_img.read(blob)
out_img.magick('PNG')
return out_img
return img
def resize(self, req, width, height):
file_path = req.cfg.attachments_path + '/' + self.webname()
if self.mime_type.startswith('image') \
and guess_extension(self.mime_type) in _image_exts:
img = Image(file_path.encode('utf-8'))
img.fileName(
'image.'+self.file_name.encode('utf-8').split('.')[-1])
size = img.size()
blob = Blob()
if width > size.width() and height > size.height():
img.write(blob)
else:
img.scale(Geometry(width, height))
img.write(blob)
return blob.data
elif guess_extension(self.mime_type) == '.svg':
with open(file_path.encode('utf-8'), 'rb') as svg:
return svg.read()
else:
req.log_error(self.mime_type)
return None
# Set the named file as first entry in the image list
# This file will be the base for alignment and intensity normalization
if base_image is not None:
idx = frames.index(base_image)
f = frames.pop(idx)
frames.insert(0,f)
if verbose:
print "%s will be used as base image" % frames[0]
# Determine image size
base_img_fname = frames[0]
if verbose:
print "Reading %s" % base_img_fname
img = PMImage(base_img_fname)
w,h = img.size().width(), img.size().height()
if img.monochrome():
c = 1
else:
c = 3
print "Detected image size is %d x %d (width x height)" % (w,h)
print "%s will be used as base image" % frames[0]
img = IMtoNumpy(img,pre_usm,verbose=verbose)
# Get data used for aligning images
align_ref_data = None
if align_ref_loc is not None:
xc = align_ref_loc[0]
yc = align_ref_loc[1]