def do_color(self):
"""usage: color <image:pic1>
Enhance color in the top image.
"""
import ImageEnhance
factor = float(self.do_pop())
image = self.do_pop()
enhancer = ImageEnhance.Color(image)
self.push(enhancer.enhance(factor))
def do_sharpness(self):
"""usage: sharpness <image:pic1>
Enhance sharpness in the top image.
"""
import ImageEnhance
factor = float(self.do_pop())
image = self.do_pop()
enhancer = ImageEnhance.Color(image)
self.push(enhancer.enhance(factor))
def adjustImage(infile):
im = Image.open(infile)
for f in range(40, 20, -1):
factor = f / 20.0
outfile = os.path.splitext(infile)[0] + ('-%f.png' % factor)
enhancer = ImageEnhance.Brightness(im)
tmp = enhancer.enhance(factor)
enhancer = ImageEnhance.Contrast(tmp)
tmp = enhancer.enhance(1.15)
enhancer = ImageEnhance.Color(tmp)
enhancer.enhance(1.15).save(outfile)
def getImage(self):
"""Returns a PIL Image instance."""
buffer, width, height = self.getBuffer()
if buffer:
if self.color:
return ImageTk.Image.fromstring('RGB', (width, height), buffer,
'raw', 'BGR', 0, -1)
else:
return ImageEnhance.Color(
ImageTk.Image.fromstring('RGB', (width, height), buffer,
'raw', 'BGR', 0,
-1)).enhance(self.color)
def enhance_signature(img):
bw = ImageEnhance.Color(img).enhance(0.0)
bright = ImageEnhance.Brightness(bw).enhance(2.2)
contrast = ImageEnhance.Contrast(bright).enhance(2.0)
sign = contrast.convert("RGBA")
datas = sign.getdata()
#--- Algo to detect non-signatured areas and reduce its alpha to zero --#
newData = []
for item in datas:
if item[0] > 200 and item[1] > 200 and item[2] > 200:
newData.append((255, 255, 255, 0))
else:
newData.append(item)
sign.putdata(newData)
sign.save("signature_alpha.png", "PNG")
def enhance(pixbuf,
brightness=1.0,
contrast=1.0,
saturation=1.0,
sharpness=1.0,
autocontrast=False):
"""Return a modified pixbuf from <pixbuf> where the enhancement operations
corresponding to each argument has been performed. A value of 1.0 means
no change. If <autocontrast> is True it overrides the <contrast> value,
but only if the image mode is supported by ImageOps.autocontrast (i.e.
it is L or RGB.)
"""
im = pixbuf_to_pil(pixbuf)
if brightness != 1.0:
im = ImageEnhance.Brightness(im).enhance(brightness)
if autocontrast and im.mode in ('L', 'RGB'):
im = ImageOps.autocontrast(im, cutoff=0.1)
elif contrast != 1.0:
im = ImageEnhance.Contrast(im).enhance(contrast)
if saturation != 1.0:
im = ImageEnhance.Color(im).enhance(saturation)
if sharpness != 1.0:
im = ImageEnhance.Sharpness(im).enhance(sharpness)
return pil_to_pixbuf(im)
def enhance(image, factor):
image = ImageEnhance.Color(image).enhance(factor / 5)
image = ImageEnhance.Contrast(image).enhance(factor)
return image
def _decolor_fired(self):
print "Color diminishing the image!"
im = Image.open("image.jpg")
im_decolor_enhanced = ImageEnhance.Color(im).enhance(0.5)
im_decolor_enhanced.save("image.jpg", "JPEG")
self.display_image()
def _color_fired(self):
print "Color enhancing the image!"
im = Image.open("image.jpg")
im_color_enhanced = ImageEnhance.Color(im).enhance(2)
im_color_enhanced.save("image.jpg", "JPEG")
self.display_image()
out = channelMap(divide, self.black).convert("RGBA")
out.putalpha(maskgray)
return out
def save(self, *args):
self.create().save(*args)
for filename in files:
filesuffix = filename.replace("arrow", "", 1)
im = Image.open(filename)
im_alpha = (im.copy().split())[-1]
im_bright = ImageEnhance.Brightness(im).enhance(2)
im_dark = ImageEnhance.Brightness(im).enhance(.5)
im_weak = ImageEnhance.Color(im_dark).enhance(.2)
im_bright.putalpha(im_alpha)
im_weak.putalpha(im_alpha)
im_dark.putalpha(im_alpha)
im_middle = im_weak # depends on active/inactive?
(imw, imh) = im.size
skippix = 4 # should be factor of imh (typically 64)
holdtypes = {"_active": im_bright, "_inactive": im_dark, "_dead": im_weak}
for im_middle_name, im_middle in holdtypes.iteritems():
# stepmania has bottomcap, but we're scrolling the other direction
htopcap = NotBrokenRGBA((imw, imh)) #Image.new("RGBA", (imw, imh))
hbody = NotBrokenRGBA((imw, 2 * imh)) # Image.new("RGB", (imw, 2*imh))
x = x - h2 / 2
y = y - h1 / 2
sigma = 1.5
g = np.exp(-(x**2 + y**2) / (2 * sigma**2))
return g / g.sum()
filename = options.filename
print filename, options.alpha
im = Image.open(filename)
outputDir = options.output
print "loading image ", filename, "... ",
enhancer = ImageEnhance.Color(im)
imGray = enhancer.enhance(0.).convert("L").resize(
(options.res_size, options.res_size),
Image.ANTIALIAS).filter(ImageFilter.MedianFilter(options.kernel_size))
print "done."
print "applying threshold... ",
hist = scipy.ndimage.filters.gaussian_filter1d(np.array(
imGray.histogram()[100:200]),
sigma=10)
val = np.argmin(hist) + options.threshold
contrast = ImageEnhance.Contrast(imGray)
