本文整理汇总了Python中ImageChops类的典型用法代码示例。如果您正苦于以下问题：Python ImageChops类的具体用法？Python ImageChops怎么用？Python ImageChops使用的例子？那么恭喜您, 这里精选的类代码示例或许可以为您提供帮助。
在下文中一共展示了ImageChops类的15个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: contrast
def contrast(self, cropped_img):
"""
Provides a high contrast board image for input into Tesseract OCR
"""
# Convert the board image into greyscal
bwImg = cropped_img.convert("L")
# Multiply board image with inverted image so that text is black
bwImgM = ImageChops.multiply(ImageChops.invert(bwImg), bwImg)
# Increase contrast
enhancedImg = ImageEnhance.Contrast(bwImgM)
bwImgM = enhancedImg.enhance(5.0)
# Produce pixel image object (array) for operation (operates in place)
bwMDat = bwImgM.load()
# If the pixel value is not black, make it white
# (No colours any more, I want them to turn black)
for i in range(0, bwImgM.size[1]):
for j in range(0, bwImgM.size[0]):
if bwMDat[j, i] != 0:
bwMDat[j, i] = 255
# Debugging
# bwImgM.show()
return bwImgM示例2: Problem1ImageSolver
def Problem1ImageSolver():
[dirImagesQuestions, dirImagesAnswers] = get_images_for_directory("Representations/Frames/Problem 1/")
print "Problem 1 Image Questions: \n=================="
compare_k = dirImagesQuestions.keys()[0]
compare_v = dirImagesQuestions[compare_k]
compare_v = ImageChops.invert(compare_v)
compare_v = findRelevantBoxEdges(compare_v)
# print compare_k
for k,v in dirImagesQuestions.iteritems():
temp_v = ImageChops.invert(dirImagesQuestions[k])
temp_v = findRelevantBoxEdges(temp_v)
image_equality = check_shape_equality(compare_v, temp_v)
equality_string = ""
if not image_equality:
equality_string = "different"
else:
equality_string = "equal with " + image_equality[1] + " transformation"
print str(k) + " and " + str(compare_k) + " are " + equality_string
print "\nProblem 1 Image Answers: \n=================="
for k,v in dirImagesAnswers.iteritems():
temp_v = ImageChops.invert(dirImagesAnswers[k])
temp_v = findRelevantBoxEdges(temp_v)
# if compare_v.size != temp_v.size:
# print str(compare_k) + " is " + str(compare_v.size) + " but " + str(k) + " is " + str(temp_v.size)
image_equality = check_shape_equality(compare_v, temp_v)
equality_string = ""
if not image_equality:
equality_string = "different"
else:
equality_string = "equal with " + image_equality[1] + " transformation"
print str(k) + " and " + str(compare_k) + " are " + equality_string示例3: autofocus
def autofocus(self,step=5000):
if self.slide.pos[2] >= 0: step = -step
self.slide.moveZ(-step/2)
z_start = self.slide.pos[2]
self.frames.fillBuffer()
self.slide.displaceZ(step)
z_frames = self.frames.getBuffer()
#sample every kth plus its lth neighbor: for k=10,l=2 sample frame 0,10,20 and 2,12,22
k = 10
l = 2
sample_ind = [ind*k for ind in range(len(z_frames)/k)]
sample_ind2 = [ind*k+l for ind in range(len(z_frames)/k)]
f = [z_frames[ind] for ind in sample_ind]
f2 = [z_frames[ind] for ind in sample_ind2]
n = len(f)
diffs = []
for i in range(n-2):
diffs.append(ImageChops.difference(f[i],f2[i]))
motion = []
for f in diffs:
f = ImageChops.multiply(f,self.curr_mask)
motion.append(ImageStat.Stat(f).sum[0])
#g = Gnuplot.Gnuplot()
#g.plot(motion)
max_frame = scipy.argmax(motion)
max_focus = (max_frame/float(n))*step + z_start
self.slide.moveZ(max_focus)
return max_focus示例4: matchTemplate
def matchTemplate(searchImage, templateImage):
minScore = -1000
matching_xs = 0
matching_ys = 0
# convert images to "L" to reduce computation by factor 3 "RGB"->"L"
searchImage = searchImage.convert(mode="L")
templateImage = templateImage.convert(mode="L")
searchWidth, searchHeight = searchImage.size
templateWidth, templateHeight = templateImage.size
# make a copy of templateImage and fill with color=1
templateMask = Image.new(mode="L", size=templateImage.size, color=1)
# loop over each pixel in the search image
for xs in range(searchWidth - templateWidth + 1):
for ys in range(searchHeight - templateHeight + 1):
# for ys in range(10):
# set some kind of score variable to "All equal"
score = templateWidth * templateHeight
# crop the part from searchImage
searchCrop = searchImage.crop((xs, ys, xs + templateWidth, ys + templateHeight))
diff = ImageChops.difference(templateImage, searchCrop)
notequal = ImageChops.darker(diff, templateMask)
countnotequal = sum(notequal.getdata())
score -= countnotequal
if minScore < score:
minScore = score
matching_xs = xs
matching_ys = ys
if minScore > 100:
print "Location=", (matching_xs, matching_ys), "Score=", minScore
quit()示例5: loadImage
def loadImage(self, path):
global zoomAmount, currentImage
pixmap = QtGui.QPixmap(path)
self.ui.image.setPixmap(pixmap)
self.ui.image.setFixedSize(pixmap.size())
self.zoomedPixmap = pixmap.scaled (self.ui.image.width()*zoomAmount, self.ui.image.height()*zoomAmount, QtCore.Qt.KeepAspectRatio)
myPixmap = self.zoomedPixmap.copy(0,0, self.ui.zoomImage.width(), self.ui.zoomImage.height())
self.ui.zoomImage.setPixmap(myPixmap)
self.ui.zoomImage.setFixedSize(myPixmap.size())
currentImage = Image.open(path)
# convert to grayscale
if currentImage.mode != "L":
currentImage= currentImage.convert("L")
# Sobel operator
# edge1 = currentImage.filter(ImageFilter.Kernel((3,3), [1, 0, -1, 2, 0, -2, 1, 0, -1], scale=4))
# edge2 = currentImage.filter(ImageFilter.Kernel((3,3), [1, 2, 1, 0, 0, 0, -1, -2, -1], scale=4))
# edge3 = currentImage.filter(ImageFilter.Kernel((3,3), [-1, 0, 1, -2, 0, 2, -1, 0, 1], scale=4))
# edge4 = currentImage.filter(ImageFilter.Kernel((3,3), [-1, -2, -1, 0, 0, 0, 1, 2, 1], scale=4))
# Scharr operator
edge1 = currentImage.filter(ImageFilter.Kernel((3,3), [3, 0, -3, 10, 0, -10, 3, 0, -3], scale=16))
edge2 = currentImage.filter(ImageFilter.Kernel((3,3), [3, 10, 3, 0, 0, 0, -3, -10, -3], scale=16))
edge3 = currentImage.filter(ImageFilter.Kernel((3,3), [-3, 0, 3, -10, 0, 10, -3, 0, 3], scale=16))
edge4 = currentImage.filter(ImageFilter.Kernel((3,3), [-3, -10, -3, 0, 0, 0, 3, 10, 3], scale=16))
currentImage = ImageChops.add(ImageChops.add(ImageChops.add(edge1, edge2), edge3), edge4)示例6: color_grad_magnitude
def color_grad_magnitude(image):
red, green, blue = image.split()
red_grad_mag = grad_magnitude(red)
green_grad_mag = grad_magnitude(green)
blue_grad_mag = grad_magnitude(blue)
tmp_image = ImageChops.lighter(red_grad_mag, green_grad_mag)
return ImageChops.lighter(tmp_image, blue_grad_mag)示例7: draw_line
def draw_line(image, point, neighbor, size):
width, height = size
center_point = (width//2, height//2)
offset = (width//2 - point[0], height//2 - point[1])
image = ImageChops.offset(image, offset[0], offset[1])
draw = ImageDraw.Draw(image)
to_point = ((neighbor[0] + offset[0]) % width, (neighbor[1] + offset[1]) % height)
draw.line((center_point, to_point))
return ImageChops.offset(image, -offset[0], -offset[1])示例8: dilate
def dilate(self, image):
paddedImage = self.createPaddedImage(image, 1)
thresholdImg = paddedImage.point(lambda i, v=128: i > v and 255)
thresholdImg = ImageChops.invert(thresholdImg)
filteredImg = thresholdImg.filter(ImageFilter.FIND_EDGES)
thresholdImg = filteredImg.point(lambda i, v=128: i > v and 255)
arithImg = ImageChops.add(paddedImage, thresholdImg)
box = (1, 1, arithImg.size[0]-1, arithImg.size[1]-1)
outImage = arithImg.crop(box)
return outImage示例9: screen_mode
def screen_mode(im, wm, wmbuffer):
imsize = im.size
wmsize = wm.size
brightness = float(_OPACITY) / 100
brightval = int(round(255 * brightness))
wm_pos = _wm_pos(wmbuffer, imsize, wmsize)
black_bg = Image.new('RGB', imsize, (0, 0, 0) )
black_bg.paste(wm, wm_pos)
darkener = Image.new('RGB', imsize, (brightval, brightval, brightval) )
darkened_fit_wm = ImageChops.multiply(black_bg, darkener)
return ImageChops.screen(darkened_fit_wm, im)示例10: addup
def addup(ims,offset):
##must be of len 2**m
n=1
while len(ims)>1:
newims=[]
for i in range(0,len(ims),2):
#print 'offset = %d'%(-offset*n)
newims.append(ImageChops.add(ims[i],ImageChops.offset(ims[i+1],offset*n,0),2,0))
ims = newims
n*=2
return ims[0]示例11: vignette
def vignette(image, off=0.2, stop=0.7, center_w=0.5, center_h=0.5):
width, height = image.size
vlayer = create_circular_gradient(image.size, 1.3, center_w, center_h, False)
curv = list(curves.create_curve([(0, 0), (96, 200), (255, 255)]))
vlayer = curves.apply_curves(vlayer, curv)
vlayer = vlayer.filter(ImageFilter.BLUR).convert("RGB")
clouds = create_clouds_bw(vlayer.size, 3)
clouds = ImageEnhance.Brightness(clouds).enhance(3)
clouds = ImageEnhance.Contrast(clouds).enhance(0.9)
clouds = ImageChops.multiply(clouds, ImageChops.invert(vlayer))
return ImageChops.multiply(image, ImageChops.invert(clouds))示例12: addup2
def addup2(ims,offset):
##must be of len 2**m
n=len(ims)+1
#do all the offsets
ims = [ImageChops.offset(im,-offset*(n/2-i),0) for i,im in enumerate(ims)]
#add all the images, two at a time to avoid overflow
while len(ims)>1:
ims = [ImageChops.add(ims[i],ims[i+1],2,0) for i in range(0,len(ims),2)]
return ims[0]示例13: seg_mask
def seg_mask(iseries, sbinfilepath, segmaskfilepath, segsbfilepath,origfilepath,expfilepath,segexpfilepath,segorigfilepath):
#iseries is a filename, without jpg on the end and with sb on the end
# First, apply mask to sb image - mask is black (or grey) on white background
filename = re.sub('_mask','',iseries) + '.jpg' #this is the sb image
# print 'Initial', filename
maskim = Image.open(segmaskfilepath+ re.sub('.jpg','_mask.jpg',filename)).convert("L")
# Mask not always black so first make sure it is
threshold = 141
maskim = maskim.point(lambda p: p > threshold and 255)
threshfilename = re.sub('_sb','_sbthres', filename)
sbim = Image.open(sbinfilepath + threshfilename)
try:
# print 'Get thresh'
seg_sb = ImageChops.lighter(sbim,maskim)
seg_sb.save(segsbfilepath+ re.sub('.jpg','_seg.jpg',threshfilename) )
except IOError:
print 'error in file'
#Now open the original image - get rid of sb from filename
filename = re.sub('_sb','', filename)
origim = Image.open(origfilepath + filename).convert("L")
seg_orig = ImageChops.lighter(origim,maskim)
seg_orig.save(segorigfilepath+ re.sub('.jpg','_seg_orig.jpg',filename))
#Now open the exp image and apply mask
# First make mask white on black
maskim = ImageChops.invert(maskim)
# Now extract all the pixels that are white and make this region a transparent region on the mask
maskim = maskim.convert('LA')
datas = maskim.getdata()
newData = list()
for item in datas:
if item[0] == 255:
newData.append((255, 0))
else:
newData.append(item)
maskim.putdata(newData)
#img.save("img2.png", "PNG")
l,a = maskim.split()
# Check that exp file exists
if os.path.exists(expfilepath + re.sub('ish','exp',filename)):
#seg_exp = ImageChops.logical_and(expim,maskim)
expim = Image.open(expfilepath + re.sub('ish','exp',filename)).convert("LA") # should be a grayscale image
expim.paste(maskim, mask = a)
expim = expim.convert("L")
expim.save(segexpfilepath+ re.sub('.jpg','_seg_exp.tif',filename))
else: print 'N'示例14: combine
def combine(ims,offset):
n=len(ims)-1
#do all the offsets
ims = [ImageChops.offset(im,-offset*(n/2-i),0) for i,im in enumerate(ims)]
#add all the images, two at a time to avoid overflow
while len(ims)>1:
ims = [ImageChops.add(ims[i],ims[i+1],2,0) for i in range(0,len(ims),2)]
#return the final result image
return ims[0]示例15: _gen_pants
def _gen_pants(self):
if self.command.has_key("pants"):
self.base_image = self.image["pants"]
self.pattern_image = self.image[self.command["pants"]]
if self.command.has_key("color"):
self.color_image = Image.new("RGBA", (240, 240), self.command["color"])
if self.command.has_key("base_color"):
self.base_color_image = Image.new("RGBA", (240, 240), self.command["base_color"])
self.icon.paste(self.base_image, mask=self.base_image)
self.icon = ImageChops.composite(self.icon, self.base_color_image, self.image["base_mask"])
self.icon = ImageChops.composite(self.icon, self.color_image, self.pattern_image)
self.icon.paste(self.image["frame"], mask=self.image["frame"])本文标签属性：
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代码：代码零九
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