def __init__(self, start_response, scaled_size, logger):
self.start_response = start_response
self.scaled_size = scaled_size
self.outbuffer = Blob()
self.content_length = None
self.logger = logger
self.scale = True
def finish_response(self, app_iter):
if not self.scale:
self.start_response(self.status, self.headers)
self.output = app_iter
return
CONTENT_LENGTH.delete(self.headers)
inBuffer = StringIO()
try:
for s in app_iter:
self.logger.debug("Writing %d bytes into image buffer." %
len(s))
inBuffer.write(s)
finally:
if hasattr(app_iter, 'close'):
app_iter.close()
rawImg = Blob()
rawImg.data = inBuffer.getvalue()
inBuffer.close()
image = Image(rawImg)
self.logger.debug("Scaling image to %s" % self.scaled_size)
image.scale(self.scaled_size[0])
image.write(self.outbuffer)
content_length = self.outbuffer.length()
CONTENT_LENGTH.update(self.headers, content_length)
CACHE_CONTROL.update(self.headers, s_maxage=CACHE_CONTROL.ONE_HOUR)
self.start_response(self.status, self.headers)
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 finish_response(self, app_iter):
if not self.scale:
self.start_response(self.status, self.headers)
self.output = app_iter
return
CONTENT_LENGTH.delete(self.headers)
inBuffer = StringIO()
try:
for s in app_iter:
self.logger.debug("Writing %d bytes into image buffer." % len(s))
inBuffer.write(s)
finally:
if hasattr(app_iter, 'close'):
app_iter.close()
rawImg = Blob()
rawImg.data = inBuffer.getvalue()
inBuffer.close()
image = Image(rawImg)
self.logger.debug("Scaling image to %s" % self.scaled_size)
image.scale(self.scaled_size[0])
image.write(self.outbuffer)
content_length = self.outbuffer.length()
CONTENT_LENGTH.update(self.headers, content_length)
CACHE_CONTROL.update(self.headers, s_maxage=CACHE_CONTROL.ONE_HOUR)
self.start_response(self.status, self.headers)
def __init__(self, start_response, scaled_size, logger):
self.start_response = start_response
self.scaled_size = scaled_size
self.outbuffer = Blob()
self.content_length = None
self.logger = logger
self.scale = True
def GetDecimalDegrees(self, image):
blob = Blob()
# Remove a bit of the anti-aliasing. After this, I got better
# results distinguishing the 3 from the 8.
image.sharpen()
image.sharpen()
image.sharpen()
image.sharpen()
image.magick("PNG")
image.quality(100)
image.write(blob)
tesseract.ProcessPagesBuffer(blob.data, blob.length(), self._api)
text = self._api.GetUTF8Text().replace(' ', '')
coordinates = re.split("°|'|\"| ", text)[:3]
return self._ConvertToDecimalDegrees(coordinates)
class ImageScalerResponse(object):
def __init__(self, start_response, scaled_size, logger):
self.start_response = start_response
self.scaled_size = scaled_size
self.outbuffer = Blob()
self.content_length = None
self.logger = logger
self.scale = True
def scaler_start_response(self, status, headers, exc_info=None):
if status.startswith('304'):
CONTENT_LENGTH.delete(self.headers)
if not status.startswith('2'):
self.scale = False
self.headers = headers
self.status = status
return self.outbuffer.data
def write(self):
if self.scale:
return [self.outbuffer.data]
else:
return self.output
def finish_response(self, app_iter):
if not self.scale:
self.start_response(self.status, self.headers)
self.output = app_iter
return
CONTENT_LENGTH.delete(self.headers)
inBuffer = StringIO()
try:
for s in app_iter:
self.logger.debug("Writing %d bytes into image buffer." %
len(s))
inBuffer.write(s)
finally:
if hasattr(app_iter, 'close'):
app_iter.close()
rawImg = Blob()
rawImg.data = inBuffer.getvalue()
inBuffer.close()
image = Image(rawImg)
self.logger.debug("Scaling image to %s" % self.scaled_size)
image.scale(self.scaled_size[0])
image.write(self.outbuffer)
content_length = self.outbuffer.length()
CONTENT_LENGTH.update(self.headers, content_length)
CACHE_CONTROL.update(self.headers, s_maxage=CACHE_CONTROL.ONE_HOUR)
self.start_response(self.status, self.headers)
class ImageScalerResponse(object):
def __init__(self, start_response, scaled_size, logger):
self.start_response = start_response
self.scaled_size = scaled_size
self.outbuffer = Blob()
self.content_length = None
self.logger = logger
self.scale = True
def scaler_start_response(self, status, headers, exc_info=None):
if status.startswith('304'):
CONTENT_LENGTH.delete(self.headers)
if not status.startswith('2'):
self.scale = False
self.headers = headers
self.status = status
return self.outbuffer.data
def write(self):
if self.scale:
return [self.outbuffer.data]
else:
return self.output
def finish_response(self, app_iter):
if not self.scale:
self.start_response(self.status, self.headers)
self.output = app_iter
return
CONTENT_LENGTH.delete(self.headers)
inBuffer = StringIO()
try:
for s in app_iter:
self.logger.debug("Writing %d bytes into image buffer." % len(s))
inBuffer.write(s)
finally:
if hasattr(app_iter, 'close'):
app_iter.close()
rawImg = Blob()
rawImg.data = inBuffer.getvalue()
inBuffer.close()
image = Image(rawImg)
self.logger.debug("Scaling image to %s" % self.scaled_size)
image.scale(self.scaled_size[0])
image.write(self.outbuffer)
content_length = self.outbuffer.length()
CONTENT_LENGTH.update(self.headers, content_length)
CACHE_CONTROL.update(self.headers, s_maxage=CACHE_CONTROL.ONE_HOUR)
self.start_response(self.status, self.headers)
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 walk_menu(entry):
if isinstance(entry, xdg.Menu.Menu) and entry.Show is True:
map(walk_menu, entry.getEntries())
elif isinstance(entry, xdg.Menu.MenuEntry) and entry.Show is True:
# byte 1 signals another entry
conn.sendall('\x01')
img_path = icon_attr(entry.DesktopEntry).encode('utf-8')
if img_path and os.path.isfile(img_path):
try:
# Create an empty image and set the background color to
# transparent. This is important to have transparent background
# when converting from SVG
img = Image()
img.backgroundColor(Color(0, 0, 0, 0xffff))
img.read(img_path)
# scale the image to 48x48 pixels
img.scale(Geometry(48, 48))
# ensure the image is converted to ICO
img.magick('ICO')
b = Blob()
img.write(b)
# icon length plus data
conn.sendall(struct.pack('i', len(b.data)))
conn.sendall(b.data)
except Exception:
conn.sendall(struct.pack('i', 0))
else:
conn.sendall(struct.pack('i', 0))
name = entry.DesktopEntry.getName()
# name length plus data
conn.sendall(struct.pack('i', len(name)))
conn.sendall(name)
command = re.sub(' -caption "%c"| -caption %c',
' -caption "%s"' % name, entry.DesktopEntry.getExec())
command = re.sub(' [^ ]*%[fFuUdDnNickvm]', '', command)
if entry.DesktopEntry.getTerminal():
command = 'xterm -title "%s" -e %s' % (name, command)
# command length plus data
conn.sendall(struct.pack('i', len(command)))
conn.sendall(command)
def to_numpy(img):
'''Convert ImageMagick data to numpy array.
:param img: image to convert
:type img: PythonMagick.Image
:rtype: Numpy ndarray
'''
if not isinstance(img, np.ndarray):
LOGGER.debug("Converting from ImageMagick to Numpy.")
img.magick('RGB')
blob = Blob()
img.write(blob)
out_img = np.fromstring(blob.data, dtype='uint' + str(img.depth()))
height, width, chans = img.rows(), img.columns(), 3
if img.monochrome():
chans = 1
return out_img.reshape(height, width, chans)
return img