def generate_cloud_nm_channel(srcImg):
# channels
r, g, b, a = srcImg.split()
# helper images
gray = Image.new('L', srcImg.size, (127))
yellowRGB = Image.new('RGB', srcImg.size, (255, 255, 0))
# discard 'too yellow' values
oneMinusYellowness = ImageChops.difference(Image.merge('RGB', (r, g, b)), yellowRGB)
yR, yG, yB = oneMinusYellowness.split()
oneMinusYellowness = ImageChops.lighter(yR, yG)
yellowness = ImageChops.invert(oneMinusYellowness)
yellowness = ImageChops.lighter(yellowness, gray)
yellowness = ImageChops.subtract(yellowness, gray)
yellowness = ImageChops.add(yellowness, yellowness)
#yellowness.save("Y:/art/source/particles/textures/clouds/yellowness.png")
halfRed = ImageChops.multiply(r, gray) # 50% red
halfGreen = ImageChops.multiply(g, gray) # 50% green
# compose
dstImg = ImageChops.subtract(ImageChops.add(gray, halfRed), halfGreen)
dstImg = ImageChops.composite(gray, dstImg, yellowness)
return dstImg
def add_images(self, im1, im2):
offset= self.findOffset(im1, im2)
if offset==(0,0):
return ImageChops.add(im1, im2)
else:
return ImageChops.add(im1, ImageChops.offset(im2,offset[0], offset[1]))
def main():
# on crée une image à partir de la librairie Image
image = Image.new("RGB", (W, H), "black")
# on crée la scène
lumiere = Lumiere(Vector(-10, -20, 50), 1000000000)
origin = Vector(0, 0, 55)
fov = 90 * 3.14 / 180
direction = Vector(0, 0, 1).getNormalized
up = Vector(0, 1, 0).getNormalized
right = direction.cross(up) * (-1)
camera = Camera(origin, fov, direction, up, right)
materiau_opaque1 = Materiau([1, 0, 0], False, 0) # rouge
materiau_opaque2 = Materiau([0, 1, 0], False, 0) # vert
materiau_opaque3 = Materiau([0, 0, 1], False, 0) # bleu
materiau_opaque4 = Materiau([0, 1, 1], False, 0) # cyan
materiau_opaque5 = Materiau([1, 1, 1], False, 0) # blanc
materiau_opaque6 = Materiau([1, 1, 0], False, 0) # jaune
materiau_reflechissant = Materiau([1, 1, 1], True, 0)
materiau_transparent = Materiau([1, 1, 1], False, 1.5)
s1 = Sphere(Vector(0, -2, 25), 10, materiau_transparent)
s2 = Sphere(Vector(0, 0, 1000), 940, materiau_opaque5) # arrière
s3 = Sphere(Vector(0, 0, -1000), 940, materiau_opaque5) # devant
s4 = Sphere(Vector(1000, 0, 0), 940, materiau_opaque3) # droite
s5 = Sphere(Vector(-1000, 0, 0), 940, materiau_opaque1) # gauche
s6 = Sphere(Vector(0, 1000, 0), 990, materiau_opaque6) # dessous
s7 = Sphere(Vector(0, -1000, 0), 940, materiau_opaque2) # dessus
scene = Scene([s1, s2, s3, s4, s5, s6, s7], lumiere, camera)
# variable pour le multiprocessing
out_q = Queue()
imageProcess = []
imageQuadrant = []
# on lance des process pour chaque quadran
for i in xrange(n_quadrants):
imageProcess.append(Process(target=scene.getImage, args=(image, n_rebonds, i, out_q, n_echantillons, diffus)))
imageProcess[i].start()
for i in xrange(n_quadrants):
imageQuadrant.append(out_q.get())
for i in xrange(n_quadrants):
imageProcess[i].join()
# on reconstruit l'image depuis les quadrans
image_haute = ImageChops.add(imageQuadrant[0], imageQuadrant[1])
image_basse = ImageChops.add(imageQuadrant[2], imageQuadrant[3])
image = ImageChops.add(image_haute, image_basse)
image.show()
image.save("image.jpg")
def test_uri(self, name, uri):
filename = os.path.join(self.directory, name)
file1 = filename+'.runner1.png'
file2 = filename+'.runner2.png'
self.c1.doURI(uri, file1)
self.c2.doURI(uri, file2)
while ( file1 not in self.saved_release_images and file2 not in self.saved_nightly_images ) and (
uri not in self.framebusters) and (uri not in self.timeouts):
sleep(1)
if (uri in self.framebusters):
print "FrameBusted "+uri
return
if (uri in self.timeouts):
print "Timeout "+uri
return
rms = None
counter = 0
while rms is None and counter < 6:
try:
rms, image1, image2, hist1, hist2 = diff_images(file1, file2)
except:
print 'Image is not ready, waiting 10 seconds.'
sleep(10)
counter += 1
if counter >= 6:
print "Timeout exceeded waiting for image to be saved"
return
result = {"uri":uri, "release_image":file1, "nightly_image":file2, "difference":rms}
if rms != 0:
result["images_differ"] = True
image1RGB = image1.convert('RGB')
image2RGB = image2.convert('RGB')
ImageChops.difference(image1RGB, image2RGB).save(filename+'.diff.difference.png')
result["diff_difference_image"] = filename+'.diff.difference.png'
ImageChops.multiply(image1, image2).save(filename+'.diff.multiply.png')
result["diff_multiply_image"] = filename+'.diff.multiply.png'
ImageChops.screen(image1, image2).save(filename+'.diff.screen.png')
result["diff_screen_image"] = filename+'.diff.screen.png'
ImageChops.add(image1, image2).save(filename+'.diff.add.png')
result["diff_add_image"] = filename+'.diff.add.png'
ImageChops.subtract(image1RGB, image2RGB).save(filename+'.diff.subtract.png')
result["diff_subtract_image"] = filename+'.diff.subtract.png'
ImageChops.lighter(image1, image2).save(filename+'.diff.lighter.png')
result["diff_lighter_image"] = filename+'.diff.lighter.png'
ImageChops.darker(image1, image2).save(filename+'.diff.darker.png')
result["diff_darker_image"] = filename+'.diff.darker.png'
else:
result["images_differ"] = False
return result
def chooseStrategy(self, figures):
# everyone is the same
figures_a_ = figures['A']
figures_b_ = figures['B']
figures_c_ = figures['C']
figures_d_ = figures['D']
figures_e_ = figures['E']
figures_f_ = figures['F']
figures_g_ = figures['G']
figures_h_ = figures['H']
# overlays
rowAB = ImageChops.add(figures_a_, figures_b_)
rowBC = ImageChops.add(figures_b_, figures_c_)
rowDE = ImageChops.add(figures_d_, figures_e_)
rowEF = ImageChops.add(figures_e_, figures_f_)
colAD =ImageChops.multiply(figures_a_, figures_d_)
colADG= ImageChops.multiply(colAD, figures_g_)
colBE =ImageChops.multiply(figures_b_, figures_e_)
colBEH= ImageChops.multiply(colBE, figures_h_)
#common permutations
ab = ImageChops.multiply(figures_a_,figures_b_)
ac = ImageChops.multiply(figures_a_,figures_c_)
df = ImageChops.multiply(figures_d_,figures_f_)
abc = ImageChops.multiply(ab,figures_c_)
de = ImageChops.multiply(figures_d_,figures_e_)
de_F=ImageChops.multiply(de,figures_f_)
#difs
difAB=self.imageUtils.invertGrayScaleImage(ImageChops.difference(figures_a_, figures_b_))
difDE=self.imageUtils.invertGrayScaleImage(ImageChops.difference(figures_d_, figures_e_))
if self.areEqual(figures_a_, figures_b_)[0] and self.areEqual(figures_b_, figures_c_)[0]:
if self.areEqual(figures_d_, figures_e_)[0] and self.areEqual(figures_e_, figures_f_)[0]:
return 'row_equals'
elif ((self.areEqual(figures_a_, figures_d_)[0] or self.areEqual(figures_a_, figures_e_)[0] or self.areEqual(figures_a_,figures_f_)[0]) \
and (self.areEqual(figures_b_, figures_d_)[0] or self.areEqual(figures_b_, figures_e_)[0] or self.areEqual(figures_b_, figures_f_)[0]) \
and (self.areEqual(figures_c_, figures_d_)[0] or self.areEqual(figures_c_, figures_e_)[0] or self.areEqual(figures_c_, figures_f_)[0])):
return 'one_of_each'
elif self.areEqual(rowAB, rowBC)[0] and self.areEqual(rowDE, rowEF)[0]:
return "one_cancels"
elif self.areEqual(colADG, colBEH)[0]:
return "cancel_out"
elif self.areEqual(ab, figures_c_)[0] and self.areEqual(de, figures_f_)[0] :
return "productAB"
elif self.areEqual(ac, figures_b_)[0] and self.areEqual(df, figures_e_)[0]:
return "productAC"
elif self.areEqual(difAB, figures_c_)[0] and self.areEqual(difDE, figures_f_)[0]:
return "diffAB"
elif self.isShared(figures):
return "shared"
elif self.areEqual(abc, de_F)[0]:
return "common_perms"
def execute(self, image, query):
athor = get_image_object(self.image, self.storage)
x2, y2 = athor.size
x1 = get_coords(image.size[0], athor.size[0], self.x)
y1 = get_coords(image.size[1], athor.size[1], self.y)
box = (
x1,
y1,
x1 + x2,
y1 + y2,
)
# Note that if you paste an "RGBA" image, the alpha band is ignored.
# You can work around this by using the same image as both source image and mask.
image = image.copy()
if athor.mode == 'RGBA':
if image.mode == 'RGBA':
channels = image.split()
alpha = channels[3]
image = Image.merge('RGB', channels[0:3])
athor_channels = athor.split()
athor_alpha = athor_channels[3]
athor = Image.merge('RGB', athor_channels[0:3])
image.paste(athor, box, mask=athor_alpha)
# merge alpha
athor_image_alpha = Image.new('L', image.size, color=0)
athor_image_alpha.paste(athor_alpha, box)
new_alpha = ImageChops.add(alpha, athor_image_alpha)
image = Image.merge('RGBA', image.split() + (new_alpha,))
else:
image.paste(athor, box, mask=athor)
else:
image.paste(athor, box)
return image
def autocrop_image(inputfilename, outputfilename = None, color = 'white', newWidth = None,
doShow = False ):
im = Image.open(inputfilename)
try:
# get hex colors
rgbcolor = hex_to_rgb( color )
except Exception:
if color not in _all_possible_colornames:
raise ValueError("Error, color name = %s not in valid set of color names.")
rgbcolor = webcolors.name_to_rgb(color)
bg = Image.new(im.mode, im.size, rgbcolor)
diff = ImageChops.difference(im, bg)
diff = ImageChops.add(diff, diff, 2.0, -100)
bbox = diff.getbbox()
if bbox:
cropped = im.crop(bbox)
if newWidth is not None:
height = int( newWidth * 1.0 / cropped.size[0] * cropped.size[1] )
cropped = cropped.resize(( newWidth, height ))
if outputfilename is None:
cropped.save(inputfilename)
else:
cropped.save(os.path.expanduser(outputfilename))
if doShow:
cropped.show( )
return True
else:
return False
def trim(im, color):
bg = Image.new(im.mode, im.size, 0)
diff = ImageChops.difference(im, bg)
diff = ImageChops.add(diff, diff, 2.0, -100)
bbox = diff.getbbox()
if bbox:
return color.crop(bbox)
def trim(im):
bg = Image.new(im.mode, im.size, im.getpixel((0,0)))
diff = ImageChops.difference(im, bg)
diff = ImageChops.add(diff, diff, 50.0, -1)
bbox = diff.getbbox()
if bbox:
return im.crop(bbox)
def DetectBorder(image):
"""Determine whether or not an image contains a border.
Args:
image: A PIL Image object.
Returns:
A boolean representing whether or not the image has a border.
"""
image_width, image_height = image.size
bg = Image.new(image.mode, image.size, image.getpixel((0, 0)))
diff = ImageChops.difference(image, bg)
# Adjusting the offset to 115 correctly identified one of the clear cases.
# Could potentially make this a flag in order to test thresholds.
diff = ImageChops.add(diff, diff, 2.0, -115)
bbox = diff.getbbox()
return all((
# Ensure that the upper-left bounding box coordinate has no value on the
# X- or Y-axis (non-zero).
bbox[0], bbox[1],
# Ensure that the sum of the upper-left X and lower_right X is less than
# the original width.
(bbox[0] + bbox[2]) <= image_width,
# Ensure that the sum of the upper-left Y and lower_right Y is less than
# the original height.
(bbox[1] + bbox[3]) <= image_height
))
def trim(_directory, legend = True):
os.chdir(_directory)
for subdir, dirs, files in os.walk(_directory):
for fn in files:
fn = os.path.join(subdir, fn)
if os.path.splitext(fn)[1] == '.png':
im = Image.open(fn)
bg = Image.new(im.mode, im.size, im.getpixel((0,0)))
diff = ImageChops.difference(im, bg)
diff = ImageChops.add(diff, diff, 2.0, -100)
bbox = diff.getbbox()
im = im.crop(bbox)
data = np.asarray(im)
if legend == True and (np.sum(data[::, data.shape[1] - 1,0]) > 255*1*data.shape[0]*.1 and \
np.sum(data[::, data.shape[1] - 1,0]) < 255*1*data.shape[0]*.75) or \
np.sum(data[::, data.shape[1] - 1,0]) == 0 or \
re.search("TAT", os.path.splitext(fn)[0]):
i = data.shape[1] - 1
while np.sum(data[::,i,::]) <> 255*data.shape[2]*data.shape[0]:
i = i - 1
while np.sum(data[::,i,::]) == 255*data.shape[2]*data.shape[0]:
i = i - 1
w, h = im.size
im = im.crop((0,0,i,h))
im.save(os.path.splitext(fn)[0] + "_cut" + os.path.splitext(fn)[1])
def create_heatmap(xs, ys, imageSize, blobSize, cmap):
blob = Image.new('RGBA', (blobSize * 2, blobSize * 2), '#000000')
blob.putalpha(0)
colour = 255 / int(math.sqrt(len(xs)))
draw = ImageDraw.Draw(blob)
draw.ellipse((blobSize / 2, blobSize / 2, blobSize * 1.5, blobSize * 1.5),
fill=(colour, colour, colour))
blob = blob.filter(ImageFilter.GaussianBlur(radius=blobSize / 2))
heat = Image.new('RGBA', (imageSize, imageSize), '#000000')
heat.putalpha(0)
xScale = float(imageSize - 1) / (max(xs) - min(xs))
yScale = float(imageSize - 1) / (min(ys) - max(ys))
xOff = min(xs)
yOff = max(ys)
for i in range(len(xs)):
xPos = int((xs[i] - xOff) * xScale)
yPos = int((ys[i] - yOff) * yScale)
blobLoc = Image.new('RGBA', (imageSize, imageSize), '#000000')
blobLoc.putalpha(0)
blobLoc.paste(blob, (xPos - blobSize, yPos - blobSize), blob)
heat = ImageChops.add(heat, blobLoc)
norm = Normalize(vmin=min(min(heat.getdata())),
vmax=max(max(heat.getdata())))
sm = ScalarMappable(norm, cmap)
heatArray = pil_to_array(heat)
rgba = sm.to_rgba(heatArray[:, :, 0], bytes=True)
rgba[:, :, 3] = heatArray[:, :, 3]
coloured = Image.fromarray(rgba, 'RGBA')
return coloured
def trim(origin_im, blur=True,
pre_percentage=PERCENTAGE_TO_CROP_SCAN_IMG, upper_lower_cut=True):
im = crop_by_percentage(origin_im, pre_percentage)
if blur:
im_blurred = im.filter(ImageFilter.GaussianBlur(radius=2))
bg = Image.new(im_blurred.mode, im_blurred.size, im.getpixel((0, 0)))
diff = ImageChops.difference(im_blurred, bg)
diff = ImageChops.add(diff, diff, 2.0, -100)
bbox = diff.getbbox()
else:
bg = Image.new(im.mode, im.size, im.getpixel((0, 0)))
diff = ImageChops.difference(im, bg)
bbox = diff.getbbox()
if bbox:
if upper_lower_cut:
return im.crop(bbox)
else:
width, height = im.size
bbox = list(bbox)
bbox[0] = max(0, bbox[0] - int(width * 0.05))
bbox[1] = 0
bbox[2] = min(width, bbox[2] + int(width * 0.05))
bbox[3] = height
return im.crop(bbox)
else:
# raise Exception("Error while cropping image, there is no bounding box to crop")
return im
def autoCrop(self, image): bg = Image.new(image.mode, image.size, image.getpixel((0,0))) diff = ImageChops.difference(image, bg) diff = ImageChops.add(diff, diff, 2.0, -200) bbox = diff.getbbox() if bbox: return image.crop(bbox)
def crop_image(self):
try:
image = Image.open(StringIO(urllib.urlopen(self.image).read()))
except:
raise
else:
image_out = StringIO()
border = Image.new(image.mode, image.size, image.getpixel((0, 0)))
diff = ImageChops.difference(image, border)
diff = ImageChops.add(diff, diff, 2.0, -100)
bbox = diff.getbbox()
if bbox:
image = image.crop(bbox)
image.save(image_out, 'JPEG')
else:
raise ValueError('Unable to determine image bounding box')
s3 = boto3.resource('s3')
region = os.environ.get('AWS_DEFAULT_REGION')
bucket = s3.Bucket(os.environ.get('AWS_S3_BUCKET'))
key = self.venue.replace(" ", "_") + '-' + self.title_raw.replace(" ", "_") + '-' + self.start.strftime("%y-%m-%d") + '.jpg'
try:
bucket.put_object(Key = key, Body = image_out.getvalue(), ACL='public-read')
except:
raise
else:
self.image = 'http://s3-{}.amazonaws.com/{}/{}'.format(region, bucket.name, key)
self.save()
def trim(im, color): #crop based on the binary image to zoom into the largest area
bg = Image.new(im.mode, im.size, 0)
diff = ImageChops.difference(im, bg)
diff = ImageChops.add(diff, diff, 2.0, -100)
bbox = diff.getbbox()
if bbox:
return color.crop(bbox) #actually returns the cropped image color, not im
def apply_edge_detector(input_image):
# Apply median filter with 3x3 window
median_image = input_image.filter(
ImageFilter.MedianFilter(3))
# Apply 3x3 center difference filters
# Apply for X
kernel_x = (0, 0, 0,
1, 0, -1,
0, 0, 0)
kernelx_image = median_image.filter(
ImageFilter.Kernel((3, 3), kernel_x, scale=2))
# Apply for Y
kernel_y = (0, 1, 0,
0, 0, 0,
0, -1, 0)
kernely_image = median_image.filter(
ImageFilter.Kernel((3, 3), kernel_y, scale=2))
# Sum the pixels of X and Y
merged = ImageChops.add(
kernelx_image, kernely_image)
# Thresholding
merged = merged.point(lambda x: 0 if x < 10 else 255)
return merged
def trim(im):
"""Trim whitespace from image."""
bg = Image.new(im.mode, im.size, im.getpixel((0,0)))
diff = ImageChops.difference(im, bg)
diff = ImageChops.add(diff, diff, 2.0, -100)
bbox = diff.getbbox()
if bbox:
return im.crop(bbox)
def bounding_box(im, tolerance=0):
"""
A bounding box algorithm that has some tolerance for fuzziness.
"""
bg = Image.new(im.mode, im.size, im.getpixel((0, 0)))
diff = ImageChops.difference(im, bg)
diff = ImageChops.add(diff, diff, 2.0, -tolerance)
return diff.getbbox()
def trim_img(imageG):
# Crop Image
image_diff = Image.new(imageG.mode, imageG.size, imageG.getpixel((0,0)))
diff = ImageChops.difference(imageG, image_diff)
diff = ImageChops.add(diff, diff, 2.0, -100)
bbox = diff.getbbox()
if bbox:
return imageG.crop(bbox)
def trim(im):
'''Trim borders of a picture automatically'''
bg = Image.new(im.mode, im.size, im.getpixel((0,0)))
diff = ImageChops.difference(im, bg)
diff = ImageChops.add(diff, diff, 1.0, -100)
bbox = diff.getbbox()
if bbox:
return im.crop(bbox)
def preprocessing(filename):
im = Image.open(filename)
bg = Image.new(im.mode, im.size, im.getpixel((0,0)))
diff = ImageChops.difference(im, bg)
diff = ImageChops.add(diff, diff, 2.0, -100)
bbox = diff.getbbox()
if bbox:
return im.crop(bbox)
def _trim(im):
px = im.getpixel((0,0))
bg = Image.new(im.mode, im.size, px)
diff = ImageChops.difference(im, bg)
diff = ImageChops.add(diff, diff, 2.0, -100)
bbox = diff.getbbox()
if bbox:
return im.crop(bbox)
def multiply_image(img, file, amount=1.0):
path = "%s%s" % (filter_path, file)
filterImg = Image.open(path)
if (amount != 1.0):
filterImg = ImageChops.add(filterImg, ImageChops.constant(filterImg, (1-amount)*255).convert("RGB"))
return ImageChops.multiply(filterImg, img)
def neImage(image1, image2):
"""Returns a boolean image that is True where image1 != image2."""
resultImage = Image.new('1', image1.size)
diffImage = ImageChops.difference(image1, image2).point(lambda x: x != 0 and 255)
bands = diffImage.split()
for band in bands:
resultImage = ImageChops.add(resultImage, band)
return resultImage
def trim(image):
background = Image.new(image.mode, image.size, image.getpixel((0,0)))
difference = ImageChops.difference(image, background)
difference = ImageChops.add(difference, difference, 2.0, -100)
bbox = difference.getbbox()
if bbox:
return image.crop(bbox)
def trim(self):
bg = Image.new(self.image.mode, self.image.size, self.image.getpixel((0, 0)))
diff = ImageChops.difference(self.image, bg)
diff = ImageChops.add(diff, diff, 2.0, -100)
bbox = diff.getbbox()
if bbox:
return self.image.crop(bbox)
else:
return self.image
def removeFrame(imgArray):
bg = Image.new(imgArray.mode, imgArray.size, imgArray.getpixel((0, 0)))
diff = ImageChops.difference(imgArray, bg)
diff = ImageChops.add(diff, diff, 2.0, -100)
bbox = diff.getbbox()
if bbox:
return imgArray.crop(bbox)
else:
return imgArray
def RoundCorner(image, radius):
"""
Generate the rounded corner image for orgimage.
"""
image = image.convert('RGBA')
#generate the mask image
mask = Image.new('RGBA', image.size, (0,0,0,0))
draw = aggdraw.Draw(mask)
brush = aggdraw.Brush('black')
width, height = mask.size
draw.rectangle((0, 0, mask.size[0], mask.size[1]), aggdraw.Brush('white'))
#north-west corner
draw.pieslice((0,0,radius*2,radius*2), 90, 180, None, brush)
#north-east corner
draw.pieslice((width-radius*2, 0, width, radius*2), 0, 90, None, brush)
#south-west corner
draw.pieslice((0, height-radius*2, radius*2, height), 180, 270, None, brush)
#south-east corner
draw.pieslice((width-radius*2, height-radius*2, width, height), 270, 360, None, brush)
#center rectangle
draw.rectangle((radius, radius, width-radius, height-radius), brush)
#four edge rectangle
draw.rectangle((radius, 0, width-radius, radius), brush)
draw.rectangle((0, radius, radius, height-radius), brush)
draw.rectangle((radius, height-radius, width-radius, height), brush)
draw.rectangle((width-radius, radius, width, height-radius), brush)
draw.flush()
del draw
return ImageChops.add(mask, image)
def trim(im):
bg = Image.new(im.mode, im.size, im.getpixel((19,19)))
diff = ImageChops.difference(im, bg)
diff = ImageChops.add(diff, diff, 1.0, 0)
bbox = diff.getbbox()
if bbox:
return im.crop((0,0,max(bbox[2],5),max(bbox[3],8)))
else:
return im.crop((0,0,5,8))
def do_add(self):
"""usage: add <image:pic1> <image:pic2> <int:offset> <float:scale>
Pop the two top images, produce the scaled sum with offset.
"""
from PIL import ImageChops
image1 = self.do_pop()
image2 = self.do_pop()
scale = float(self.do_pop())
offset = int(self.do_pop())
self.push(ImageChops.add(image1, image2, scale, offset))
def trim(im):
pixel = (255, 255, 255) # ориентируемся на белый цвет
# pixel = im.getpixel((0,0)) # ориентируемся на пиксель с левого верхнего края
bg = Image.new(im.mode, im.size, pixel)
diff = ImageChops.difference(im, bg)
diff = ImageChops.add(diff, diff, 2.0, -100)
bbox = diff.getbbox()
logger.info(bbox)
if bbox:
return im.crop(bbox)
else:
return im
def black_or_b(diff_image, image, reference, opacity=0.85):
"""Copied from https://stackoverflow.com/a/30307875 """
thresholded_diff = diff_image
for _ in range(3):
thresholded_diff = ImageChops.add(thresholded_diff, thresholded_diff)
size = diff_image.size
mask = new_gray(size, int(255 * (opacity)))
shade = new_gray(size, 0)
new = reference.copy()
new.paste(shade, mask=mask)
new.paste(image, mask=thresholded_diff)
return new
def trim(img):
"""removes border around image"""
img = img + 1
im = Image.fromarray(img)
bg = Image.new(im.mode, im.size, im.getpixel((0, 0)))
diff = ImageChops.difference(im, bg)
diff = ImageChops.add(diff, diff, 2.0, -100)
bbox = diff.getbbox()
if bbox:
return np.array(im.crop(bbox))
else:
return np.array(im)
def gentext(s, h):
fn = "../../.fonts/IBMPlexSans-SemiBold.otf"
fn = "../../.fonts/Arista-Pro-Alternate-Light-trial.ttf"
font = ImageFont.truetype(fn, h)
im = Image.new("L", (8000, 1000))
draw = ImageDraw.Draw(im)
draw.text((1, 1), s, font=font, fill=255)
return im.crop(im.getbbox())
glow = im.filter(ImageFilter.GaussianBlur(10))
im = ImageChops.add(im, glow)
return im.crop(im.getbbox())
def trim(self, im):
'''removes a border around an image '''
bg = Image.new(im.mode, im.size, im.getpixel((0, 0)))
diff = ImageChops.difference(im, bg)
diff = ImageChops.add(diff, diff, 2.0, -100)
# TODO: Works not with the US format
bbox = diff.getbbox()
if bbox:
bbox = tuple([bbox[0] - 2, bbox[1] - 2, bbox[2] + 2, bbox[3] + 2])
return im.crop(bbox)
else:
return im
def glowText(img,
text=None,
font_size=35,
font_set=None,
alpha=0.5,
blur=2,
logo=None):
width, height = img.size
ratio = 2
width = width * ratio
height = height * ratio
font_size = font_size * ratio
blur = blur * ratio
if font_set is None:
_font = ImageFont.truetype("Arial.ttf", font_size)
else:
_font = ImageFont.truetype(font_set, font_size)
canvas = Image.new('RGBA', (width, height), (0, 0, 0, 0))
draw = ImageDraw.Draw(canvas)
if text:
w, h = draw.textsize(text, font=_font)
else:
w, h = 0, 0
xoffset = 0
if logo is not None:
lg_w, lg_h = logo.size
hoffset = 1
lg_nh = round(font_size * hoffset)
lg_nw = round(lg_w * lg_nh / lg_h)
logo = logo.resize((lg_nw, lg_nh), Image.ANTIALIAS)
xoffset = lg_nw + font_size / 4
w = w + xoffset
try:
canvas.paste(logo, (round(
(width - w) / 2), round(height - 2 * font_size)), logo)
except:
canvas.paste(logo, (round(
(width - w) / 2), round(height - 2 * font_size)))
if text:
draw.text(((width - w) / 2 + xoffset, height - 2 * font_size),
text,
fill=(255, 255, 255, 255),
font=_font)
canvas_blur = canvas.filter(ImageFilter.GaussianBlur(radius=blur))
canvas = ImageChops.add(canvas, canvas_blur)
canvas = canvas.resize(img.size, Image.ANTIALIAS)
paste_mask = canvas.split()[-1].point(lambda i: i * alpha)
img.paste(canvas, (0, 0), mask=paste_mask)
return img
def trim(im):
bg = Image.new(im.mode, im.size, im.getpixel((0, 0)))
diff = ImageChops.difference(im, bg)
diff = ImageChops.add(
diff, diff, 2.0, -100
) # Adds two images, dividing the result by scale and adding the offset.
bbox = diff.getbbox(
) # Calculates the bounding box of the non-zero regions in the image.
if bbox:
return im.crop(
bbox
) # argument is the crop rectangle, as a (left, upper, right, lower)-tuple.
def hr_addimage(self,A,B,C,problem): a = ImageChops.invert(Image.open(A.visualFilename)) b = ImageChops.invert(Image.open(B.visualFilename)) c = Image.open(C.visualFilename) c1 = ImageChops.invert(ImageChops.add(a,b)) ch = c.histogram() c1h = c1.histogram() rms = np.sqrt(reduce(operator.add,map(lambda a,b: (a-b)**2, ch, c1h))/len(ch)) if rms<=15.0: return 1 else: return 0
def trim(im):
"""
https://stackoverflow.com/questions/10615901/trim-whitespace-using-pil
"""
bg = Image.new(im.mode, im.size, im.getpixel((2, 2)))
diff = ImageChops.difference(im, bg)
diff = ImageChops.add(diff, diff, 0.0, 0)
bbox = diff.getbbox()
if bbox:
return im.crop(bbox)
else:
return im
def get_thumbnail0(img):
bg = Image.new(img.mode, img.size, img.getpixel((0, 0)))
diff = ImageChops.difference(img, bg)
diff = ImageChops.add(diff, diff, 2.0, -100)
bbox = diff.getbbox()
if bbox:
img = img.crop(bbox)
else:
return get_thumbnail(img)
size = (128, 128)
img.thumbnail(size)
return img
def spot_light(pil_img):
w, h = pil_img.size
effect_img = np.zeros((h, w, 3))
scale_w = random.choice([5, 6, 7, 8, 9])
scale_h = random.choice([5, 6, 7, 8, 9])
x = random.choice(range(w // scale_w, w - w // scale_w))
y = random.choice(range(h // scale_h, h - h // scale_h))
light = random.choice(range(128, 220))
effect_img[y - h // scale_h:y + h // scale_h,
x - w // scale_w:x + w // scale_w] = light
effect_img = PIL.Image.fromarray(effect_img.astype(np.uint8))
return ImageChops.add(pil_img, effect_img)
def trim_borders(im):
''' Trim image borders.
From: http://stackoverflow.com/questions/10615901/trim-whitespace-using-pil
'''
bg = Image.new(im.mode, im.size, im.getpixel((0, 0)))
diff = ImageChops.difference(im, bg)
diff = ImageChops.add(diff, diff, 1.1, -100)
bbox = diff.getbbox()
if bbox:
return im.crop(bbox)
return im
def auto_crop(self):
bg = PilImage.new(
self._image.mode,
self._image.size,
self._image.getpixel((1, 1))
)
diff = ImageChops.difference(self._image, bg)
diff = ImageChops.add(diff, diff, 2.0, -100)
bbox = diff.getbbox()
diff.close()
self._image = self._image.crop(bbox)
return self
def trims(im):
#Crea una nueva imagen
bg = Image.new(im.mode, im.size, im.getpixel((1, 1)))
#Regresa el valor absoluto de la diferencia pixel x pixel entre dos imagenes
diff = ImageChops.difference(im, bg)
#Aniade dos imagenes, dividiendo el resultado por escala y agregando el offset
diff = ImageChops.add(diff, diff, 2.0, -100)
#Corta los bordes
bbox = diff.getbbox()
if bbox:
#Recorta la imagen (devuelve una region rectangular)
return im.crop(bbox)
def render(self, process_count, occlusion=False, path=False):
# Call ray trace for each pixel in image
cam = self.scene.cam
cam_to_screen = np.linalg.norm(cam.cam_to - cam.cam_from)
screen_width = 2 * math.tan(cam.fov / 2) * cam_to_screen
screen_height = screen_width * cam.height / cam.width
increment = screen_width / cam.width
top_left = cam.cam_to - ((screen_width / 2) * cam.u) - (
(screen_height / 2) * cam.v)
ranges = split_range(cam.width, process_count)
processes = []
for i, (start, end) in enumerate(ranges):
im = Image.new('RGB', (cam.width, cam.height))
o_im = Image.new('RGB',
(cam.width, cam.height)) if occlusion else None
process = Process(target=self.render_part,
args=(cam, top_left, increment, start, end, im,
o_im, path, 'tmp' + str(i) + '.png'))
processes.append(process)
process.start()
for process in processes:
process.join()
im = Image.new('RGB', (cam.width, cam.height))
for i in range(process_count):
im_tmp = Image.open('tmp' + str(i) + '.png')
im = ImageChops.add(im, im_tmp)
os.remove('tmp' + str(i) + '.png')
o_im, f_im = None, None
if occlusion:
o_im = Image.new('RGB', (cam.width, cam.height))
for i in range(process_count):
o_im_tmp = Image.open('otmp' + str(i) + '.png')
o_im = ImageChops.add(o_im, o_im_tmp)
os.remove('otmp' + str(i) + '.png')
f_im = ImageChops.add(
im, Image.fromarray(np.uint8(self.k_a * np.array(o_im))))
return im, o_im, f_im
def test_sanity(self):
im = hopper("L")
ImageChops.constant(im, 128)
ImageChops.duplicate(im)
ImageChops.invert(im)
ImageChops.lighter(im, im)
ImageChops.darker(im, im)
ImageChops.difference(im, im)
ImageChops.multiply(im, im)
ImageChops.screen(im, im)
ImageChops.add(im, im)
ImageChops.add(im, im, 2.0)
ImageChops.add(im, im, 2.0, 128)
ImageChops.subtract(im, im)
ImageChops.subtract(im, im, 2.0)
ImageChops.subtract(im, im, 2.0, 128)
ImageChops.add_modulo(im, im)
ImageChops.subtract_modulo(im, im)
ImageChops.blend(im, im, 0.5)
ImageChops.composite(im, im, im)
ImageChops.offset(im, 10)
ImageChops.offset(im, 10, 20)
def __call__(self, img):
if random.random() < 0.9:
img = img.convert("HSV")
zero = np.zeros((self.H, self.W, 3))
a = random.random() * 30
zero[:, :, 0] += a
zero = Image.fromarray(zero.astype('uint8'))
if random.random() < 0.5:
img = ImageChops.add(img, zero)
else:
img = ImageChops.subtract(img, zero)
img = img.convert("RGB")
return img
def widespace_remover(self, image):
'''
Remove widespace before and after text
return: cropped image
'''
im = self.checkImageOrObject(image)
if im:
bg = Image.new(im.mode, im.size, im.getpixel((0, 0)))
diff = ImageChops.difference(im, bg)
diff = ImageChops.add(diff, diff, 2.0, -100)
bbox = diff.getbbox()
if bbox:
return im.crop(bbox)
def trim(im):
bg = Image.new(im.mode, im.size, im.getpixel((0,0)))
diff = ImageChops.difference(im, bg)
diff = ImageChops.add(diff, diff, 2.0, -100)
bbox = diff.getbbox()
lenth=bbox[2]-bbox[0]
high=bbox[3]-bbox[1]
len=max([lenth,high])
if len < 16:
len=16
nbox=(bbox[0],bbox[1],bbox[0]+len,bbox[1]+len)
if nbox:
return im.crop(nbox)
def trim(img):
"""
:param img:
:return:
"""
border = Image.new(img.mode, img.size, img.getpixel((0, 0)))
diff = ImageChops.difference(img, border)
diff = ImageChops.add(diff, diff, 2.0, -100)
bbox = diff.getbbox()
if bbox:
img = img.crop(bbox)
return img
def trim(im):
'''
Trims a uniform background around the mesh to be close to the corners so we
can infer the xmax,xmin, ymax, ymin from the geometry of the mesh as the
image boundaries. It is also located outside of a class so that it can be
used in the multiprocess package to take advantage of multi-core processing.
'''
bg = Image.new(im.mode, im.size, im.getpixel((0, 0)))
diff = ImageChops.difference(im, bg)
diff = ImageChops.add(diff, diff, 2.0, -100)
bbox = diff.getbbox()
if bbox:
return im.crop(bbox)
def trim(im):
bg = Image.new(im.mode, im.size, 'white')
diff = ImageChops.difference(im, bg)
diff = ImageChops.add(diff, diff, 2.0, -55)
bbox = diff.getbbox()
if bbox:
a = max(0, bbox[0] - 20)
b = max(0, bbox[1] - 20)
c = min(im.size[0], bbox[2] + 20)
d = min(im.size[1], bbox[3] + 20)
bbox = (a, b, c, d)
return im.crop(bbox)
return im
def resize_trim_PIL(input_PIL, width, height, border):
# resize
image_output = scale(input_PIL, [width, height])
image_output = ImageOps.expand(image_output, border=border, fill='white')
# trim
bg = Image.new(image_output.mode, image_output.size,
image_output.getpixel((0, 0)))
diff = ImageChops.difference(image_output, bg)
diff = ImageChops.add(diff, diff, 2.0, -100)
bbox = diff.getbbox()
image_output = image_output.crop(bbox)
return image_output
def trim(im):
try:
img = Image.open("./input/" + im)
bg = Image.new(img.mode, img.size, img.getpixel((0, 0)))
diff = ImageChops.difference(img, bg)
diff = ImageChops.add(diff, diff, 2.0, -100)
bbox = diff.getbbox()
os.remove("./input/" + im)
return img.crop(bbox)
except:
print("kan " + str(im) + " niet doen")
def trim(im):
'''
This function trims the white space of an image
:param im: image
:return: trimmed image
'''
bg = Image.new(im.mode, im.size, im.getpixel((0, 0)))
diff = ImageChops.difference(im, bg)
diff = ImageChops.add(diff, diff, 2.0, -100)
bbox = diff.getbbox()
if bbox:
return im.crop(bbox)
def agfa(img):
img = multiply_image(img, "noise.png")
img = apply_vignette(img, 0.75)
img = contrast(img)
img.load()
r,g,b = img.split()
g = brightness(g, 1.2)
b = brightness(b, 1.2)
r = brightness(r, 0.7)
r = ImageChops.add(r, ImageChops.constant(r, 0.3*255))
img = Image.merge("RGB", (r,g,b))
img = color(img, 0.7)
return img
def trim(path):
im = Image.open(path)
bg = Image.new(im.mode, im.size, (255, 255, 255))
diff = ImageChops.difference(im, bg)
diff = ImageChops.add(diff, diff, 2.0, -100)
# Bounding box given as a 4-tuple defining the left, upper, right, and
# lower pixel coordinates.
# If the image is completely empty, this method returns None.
bbox = diff.getbbox()
if bbox:
return im.crop(bbox)
else:
return im
def trim(im):
"""Trim black borders from an image
:param im:
:type im: Image
:return:
"""
bg = Image.new(im.mode, im.size, im.getpixel((0,0)))
diff = ImageChops.difference(im, bg)
diff = ImageChops.add(diff, diff, 2.0, -100)
bbox = diff.getbbox()
if bbox:
return im.crop(bbox)
def compositeChromeKey(img1, img2, bg=None):
# merge img1 over img2 by using a transparent mask, which generated by chrome key
# if bg is valid, we merge img2 and bg firstly
img2_ch = splitImageChannels('F', img2)
if bg:
# get chrome key of img2 to merge with bg
bg_ch = splitImageChannels('F', bg)
if img2_ch[3] and bg_ch[3]:
alpha = ImageChops.add(img2_ch[3].convert('L'),
bg_ch[3].convert('L'))
img2_mask = chromeKeyBluescreen(img2_ch[0], img2_ch[1], img2_ch[2])
img2 = Image.composite(img2, bg, img2_mask.convert(
'L')) # Image.composite doesn't works with 'F' mode mask
img2.putalpha(alpha)
img1_ch = splitImageChannels('F', img1)
img1_mask = chromeKeyBluescreen(img1_ch[0], img1_ch[1], img1_ch[2])
out = Image.composite(img1, img2, img1_mask.convert('L'))
if img2_ch[3] and img1_ch[3]:
alpha = ImageChops.add(img1_ch[3].convert('L'),
img2_ch[3].convert('L'))
out.putalpha(alpha)
return out