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)