def create_photo_strips():
'''using the original images we build a color and black and white photo strip and save it to photos/strips'''
strip = Image.new('RGB', (PHOTO_HEIGHT + (BORDER_WIDTH * 2) + FOOTER_HEIGHT, (PHOTO_WIDTH * PHOTO_COUNT) + (BORDER_WIDTH * 2)), BG_COLOR)
for i in range(PHOTO_COUNT):
photo = Image.open(PHOTO_FOLDER + str(i+1) + '.' + PHOTO_FILE_EXTENSION)
w, h = map(lambda x: x/2, photo.size)
photo = ImageOps.fit(photo, (PHOTO_WIDTH, PHOTO_HEIGHT), centering=(0.5, 0.5))
photo = photo.rotate(270)
photo = ImageOps.autocontrast(photo, cutoff=0)
strip.paste(photo, (FOOTER_HEIGHT, (i * PHOTO_WIDTH) + (i * BORDER_WIDTH)))
#append footer
font = ImageFont.truetype('font_1.ttf', 40)
footer_img = Image.new("RGB", ((PHOTO_COUNT * PHOTO_WIDTH) + (PHOTO_COUNT * BORDER_WIDTH), FOOTER_HEIGHT), BG_COLOR)
draw = ImageDraw.Draw(footer_img)
draw.text((220, 40), "ashley & david's wedding, july 28, 2012", font=font, fill=(100,100,0))
strip.paste(footer_img.rotate(270), (0,0))
strip.save(COLOR_FOLDER + current_timestamp() + '.png', PHOTO_FORMAT)
ImageOps.grayscale(strip).save(GREYSCALE_FOLDER + current_timestamp() + '.png', PHOTO_FORMAT)
strip_to_print = Image.new('RGB', (PAGE_WIDTH, PAGE_HEIGHT), BG_COLOR)
strip_to_print.paste(ImageOps.grayscale(strip), (-BORDER_WIDTH, -BORDER_WIDTH))
strip_to_print.save('to_print.png', PHOTO_FORMAT)
return 'to_print.png'
def get_difference_image(im1, im2):
try:
import cv2
result = cv2.matchTemplate(numpy.array(im1),
numpy.array(im2)[32:-32, 32:-32],
cv2.TM_CCOEFF_NORMED)
#Image.fromarray(result * 255).show()
off = numpy.unravel_index(result.argmax(), result.shape)
minoff = off[0] - 32, off[1] - 32
except ImportError:
# pick a sample
pix1 = numpy.array(ImageOps.grayscale(im1))[32:64, 32:64]
pix2 = numpy.array(ImageOps.grayscale(im2))[32:64, 32:64]
mindiff = sys.maxint
minoff = (0, 0)
# find best alignment for the sample
for xoff in range(-20, 20):
for yoff in range(-20, 20):
#print xoff, yoff
pix2off = pix2
pix2off = numpy.roll(pix2off, xoff, 0)
pix2off = numpy.roll(pix2off, yoff, 1)
diff = sum((numpy.maximum(pix1, pix2off) -
numpy.minimum(pix1, pix2off)).flatten())
if diff < mindiff:
mindiff = diff
minoff = xoff, yoff
print mindiff, minoff
# align the full images
xoff, yoff = minoff
pix1 = numpy.array(im1)
pix2 = numpy.array(im2)
pix2off = pix2
pix2off = numpy.roll(pix2off, minoff[0], 0)
pix2off = numpy.roll(pix2off, minoff[1], 1)
diff = numpy.maximum(pix1, pix2off) - numpy.minimum(pix1, pix2off)
# only show the overlap
xoff = abs(xoff)
yoff = abs(yoff)
diff = diff[xoff:diff.shape[0] - 2 * xoff, yoff:diff.shape[1] - 2 * yoff]
#Image.fromarray(diff).show()
return diff
def get_difference_image(im1, im2):
try:
import cv2
result = cv2.matchTemplate(numpy.array(im1), numpy.array(im2)[32:-32, 32:-32], cv2.TM_CCOEFF_NORMED)
#Image.fromarray(result * 255).show()
off = numpy.unravel_index(result.argmax(), result.shape)
minoff = off[0]-32, off[1]-32
except ImportError:
# pick a sample
pix1 = numpy.array(ImageOps.grayscale(im1))[32:64, 32:64]
pix2 = numpy.array(ImageOps.grayscale(im2))[32:64, 32:64]
mindiff = sys.maxint
minoff = (0, 0)
# find best alignment for the sample
for xoff in range(-20, 20):
for yoff in range(-20, 20):
#print xoff, yoff
pix2off = pix2
pix2off = numpy.roll(pix2off, xoff, 0)
pix2off = numpy.roll(pix2off, yoff, 1)
diff = sum((numpy.maximum(pix1, pix2off) - numpy.minimum(pix1, pix2off)).flatten())
if diff < mindiff:
mindiff = diff
minoff = xoff, yoff
print mindiff, minoff
# align the full images
xoff, yoff = minoff
pix1 = numpy.array(im1)
pix2 = numpy.array(im2)
pix2off = pix2
pix2off = numpy.roll(pix2off, minoff[0], 0)
pix2off = numpy.roll(pix2off, minoff[1], 1)
diff = numpy.maximum(pix1, pix2off) - numpy.minimum(pix1, pix2off)
# only show the overlap
xoff = abs(xoff)
yoff = abs(yoff)
diff = diff[xoff:diff.shape[0]-2*xoff, yoff:diff.shape[1]-2*yoff]
#Image.fromarray(diff).show()
return diff
def getSeatSix():
im = ImageOps.grayscale(ImageGrab.grab
((xPad+530,yPad+60,xPad+593,yPad+76)))
a = array(im.getcolors())
im.save(os.getcwd() + '\\SeatSixBubble.png', 'PNG')
print 'table 6 bubble = %d' % a.sum()
return a.sum()
def getSeatFive():
im = ImageOps.grayscale(ImageGrab.grab
((xPad+429,yPad+60,xPad+492,yPad+76)))
a = array(im.getcolors())
im.save(os.getcwd() + '\\SeatFiveBubble.png', 'PNG')
print 'table 5 bubble = %d' % a.sum()
return a.sum()
def getSeatFour():
im = ImageOps.grayscale(ImageGrab.grab
((xPad+328,yPad+60,xPad+391,yPad+76)))
a = array(im.getcolors())
im.save(os.getcwd() + '\\SeatFourBubble.png', 'PNG')
print 'table 4 bubble = %d' % a.sum()
return a.sum()
def getSeatTwo():
im = ImageOps.grayscale(ImageGrab.grab
((xPad+126,yPad+60,xPad+189,yPad+76)))
im.save(os.getcwd() + '\\SeatTwoBubble.png', 'PNG')
a = array(im.getcolors())
print 'table 2 bubble = %d' % a.sum()
return a.sum()
def getSeatThree():
im = ImageOps.grayscale(ImageGrab.grab
((xPad+227,yPad+60,xPad+290,yPad+76)))
a = array(im.getcolors())
## im.save(os.getcwd() + '\\SeatThreeBubble.png', 'PNG')
print 'table 3 bubble = %d' % a.sum()
return a.sum()
def geticonshape(shape, dim_horiz, dim_vert):
iconimage = ''.join([shape, '_icon.png'])
img = Image.open(iconimage)
img = ImageOps.grayscale(img)
img = ImageOps.autocontrast(img)
img = img.resize((dim_horiz, dim_vert), Image.BILINEAR)
return img
def plotfig2image(fig):
"""Convert a matplotlib pyplot figure to a numpy image."""
imgdata = StringIO.StringIO()
fig.savefig(imgdata, format='png')
imgdata.seek(0) # rewind the data
im = ImageOps.grayscale(Image.open(imgdata))
return numpy.asarray(im)
def filter(infile, outfile):
# img = Image.open(infile)
img = ImageOps.grayscale(Image.open(infile))
# differrentiate
# flist = [-1, 0, 1,
# -2, 0, 2,
# -1, 0, 1]
# 8傍近接ラプラシアン
# flist = [1, 1, 1,
# 1, -8, 1,
# 1, 1, 1]
# 4傍近接ラプラシアン
# flist = [0, 1, 0,
# 1, -4, 1,
# 0, 1, 0]
flist = [-0.1, -0.2, -0.1, -0.2, 2.2, -0.2, -0.1, -0.2, -0.1]
# flt = ImageFilter.Kernel((3,3), flist, scale=1, offset=128)
flt = ImageFilter.Kernel((3, 3), flist, scale=1)
imgx = img.filter(flt)
# imgx = img.filter(ImageFilter.EMBOSS)
# imgx.show()
imgx.save(outfile)
return
def extract_region(image, coordinates):
"""
Crop the given image using the given coordinates into output file.
"""
output = hashlib.md5(image + coordinates).hexdigest()
root = '/var/ccsd-scripts/regions/%s/%s/' % (output[:2], output[2:4])
if not os.path.isdir(root):
os.makedirs(root)
output = os.path.join(root, output + '.tiff')
if not os.path.exists(output):
print("extracting_region(%r, %r)" % (image, coordinates))
# Cache the Image object to speed things up.
#
# This way, we only open an original image up once and crop as
# many times as needed -- rather than opening the same
# original image a bunch of times.
#
# We only store the active Image object and discard it once we
# move onto the next image to keep the cache from growing too
# big. Since we only open image files once, this isn't a huge
# deal.
if not IMAGE_CACHE['active'] == image:
IMAGE_CACHE['active'] = image
IMAGE_CACHE['im'] = Image.open(image)
im = IMAGE_CACHE['im']
box = coords(coordinates)
region = im.crop(box)
pix = region.load()
# If the top-leftmost pixel isn't white, coerce to black and white.
if pix[0,0] != (255, 255, 255):
region = ImageOps.grayscale(region)
# http://stackoverflow.com/questions/6485254/how-to-i-use-pil-image-pointtable-method-to-apply-a-threshold-to-a-256-gray-im
region = region.point(lambda p: p > 50 and 255)
region.save(output)
return output
def grab():
box = (c,b,z,q)
im = ImageOps.grayscale(ImageGrab.grab(box))
a = array(im.getcolors())
a = a.sum()
print a
return a
def grab(): box = (X_PAD + 1, Y_PAD +1,X_PAD + 640, Y_PAD + 480) im = ImageOps.grayscale(ImageGrab.grab(box)) a = array(im.getcolors()) a = a.sum() print a return a
def main(argv):
if len(argv) != 2:
raise ValueError(
'Expected path to image. Usage: ./{0} <path-to-image>'.format(
argv[0]))
filename = argv[1]
img = ImageOps.grayscale(Image.open(filename))
packed_grayscales = []
data = img.getdata()
for i in xrange(0, len(data), 4):
packed_int = 0
for j in xrange(4):
if i + j >= len(data):
break
packed_int <<= 8
packed_int += data[i + j]
packed_grayscales.append(packed_int)
width, height = img.size
print string.Template(_TEMPLATE).substitute(
width=width,
height=height,
grayscales=', '.join(str(p) for p in packed_grayscales))
def plotfig2image(fig):
"""Convert a matplotlib pyplot figure to a numpy image."""
imgdata = StringIO.StringIO()
fig.savefig(imgdata, format='png')
imgdata.seek(0) # rewind the data
im = ImageOps.grayscale(Image.open(imgdata))
return numpy.asarray( im )
def get_bar(): #returns whether the bar is red or gray
box = (Cord.redBar[0], Cord.redBar[1], Cord.redBar[0] + 2,
Cord.redBar[1] + 5)
im = ImageOps.grayscale(ImageGrab.grab(box))
a = array(im.getcolors())
a = a.sum()
return a
def tats(image):
image = image.convert('RGB')
colours = util.get_dominant_colours(image, 9)
colours = util.order_colours_by_brightness(colours)
bg = random.choice(colours[:3])
light = random.choice(colours[3:6])
dark = random.choice(colours[6:])
dist = math.sqrt(sum(map(lambda (a, b): math.pow(a - b, 2), zip(light, dark))))
if dist < 100:
light = util.modify_hls(light, l=lambda l: l + 100)
light = util.modify_hls(light, s=lambda s: s + 100)
dark = util.modify_hls(dark, s=lambda s: s + 100)
layer = Image.open(os.path.dirname(os.path.abspath(__file__)) + '/' +
'assets/tats.png')
layer.load()
r, g, b, a = layer.split()
layer = layer.convert('RGB')
layer = ImageOps.grayscale(layer)
layer = ImageOps.colorize(layer, tuple(dark), tuple(light))
layer.putalpha(a)
im = Image.new('RGB', layer.size, tuple(bg))
im.paste(layer, mask=layer)
return im
def getSeatTwo():
im = ImageOps.grayscale(ImageGrab.grab
((xPad+126,yPad+60,xPad+189,yPad+76)))
## im.save(os.getcwd() + '\\SeatTwoBubble.png', 'PNG')
a = array(im.getcolors())
print 'table 2 bubble = %d' % a.sum()
return a.sum()
def __init__(self, player):
self.board = Board()
self.player = player
sig = Image.open("sig.png")
sig = ImageOps.grayscale(sig)
sigp = sig.load()
n = []
for i in range(sig.size[0]):
n.append(sigp[i, 0])
# Assinatura em formato de string
n = ' '.join(map(str, n))
raw_input("Posicione a janela e pressione enter para comecar...")
sleep(2)
scp = self.screenCapture()
w = scp[1]
h = scp[2]
scp = scp[0]
for j in range(h):
cl = []
for i in range(w):
cl.append(scp[i, j])
h = ' '.join(map(str, cl))
m = h.find(n)
if m >= 0:
m = len(h[0:m].split(" "))
print "Signature found on %d, %d" % (m, j)
#self.offset = (m, j-18)
self.offset = (m+1, j+4)
break
def tats(image):
image = image.convert('RGB')
colours = util.get_dominant_colours(image, 9)
colours = util.order_colours_by_brightness(colours)
bg = random.choice(colours[:3])
light = random.choice(colours[3:6])
dark = random.choice(colours[6:])
dist = math.sqrt(
sum(map(lambda (a, b): math.pow(a - b, 2), zip(light, dark))))
if dist < 100:
light = util.modify_hls(light, l=lambda l: l + 100)
light = util.modify_hls(light, s=lambda s: s + 100)
dark = util.modify_hls(dark, s=lambda s: s + 100)
layer = Image.open(
os.path.dirname(os.path.abspath(__file__)) + '/' + 'assets/tats.png')
layer.load()
r, g, b, a = layer.split()
layer = layer.convert('RGB')
layer = ImageOps.grayscale(layer)
layer = ImageOps.colorize(layer, tuple(dark), tuple(light))
layer.putalpha(a)
im = Image.new('RGB', layer.size, tuple(bg))
im.paste(layer, mask=layer)
return im
def getSeatSix():
im = ImageOps.grayscale(ImageGrab.grab
((xPad+530,yPad+60,xPad+593,yPad+76)))
a = array(im.getcolors())
## im.save(os.getcwd() + '\\SeatSixBubble.png', 'PNG')
print 'table 6 bubble = %d' % a.sum()
return a.sum()
def ocr_cell(im, cells, x, y):
"""Return OCRed text from this cell"""
fbase = "working/%d-%d" % (x, y)
ftif = "%s.tif" % fbase
ftxt = "%s.txt" % fbase
cmd = "tesseract %s %s" % (ftif, fbase)
# extract cell from whole image, grayscale (1-color channel), monochrome
region = im.crop(cells[x][y])
region = ImageOps.grayscale(region)
region = region.point(lambda p: p > 200 and 255)
# determine background color (most used color)
histo = region.histogram()
if histo[0] > histo[255]: bgcolor = 0
else: bgcolor = 255
# trim borders by finding top-left and bottom-right bg pixels
pix = region.load()
x1,y1 = 0,0
x2,y2 = region.size
x2,y2 = x2-1,y2-1
while pix[x1,y1] != bgcolor:
x1 += 1
y1 += 1
while pix[x2,y2] != bgcolor:
x2 -= 1
y2 -= 1
# save as TIFF and extract text with Tesseract OCR
trimmed = region.crop((x1,y1,x2,y2))
trimmed.save(ftif, "TIFF")
subprocess.call([cmd], shell=True, stderr=subprocess.PIPE)
lines = [l.strip() for l in open(ftxt).readlines()]
return lines[0]
def grab(): box = (X_PAD + 1, Y_PAD +1,X_PAD + 640, Y_PAD + 480) im = ImageOps.grayscale(ImageGrab.grab(box)) a = array(im.getcolors()) a = a.sum() print a return a
def __init__(self, player):
self.board = Board()
self.player = player
sig = Image.open("sig.png")
sig = ImageOps.grayscale(sig)
sigp = sig.load()
n = []
for i in range(sig.size[0]):
n.append(sigp[i, 0])
# Assinatura em formato de string
n = ' '.join(map(str, n))
raw_input("Posicione a janela e pressione enter para comecar...")
sleep(2)
scp = self.screenCapture()
w = scp[1]
h = scp[2]
scp = scp[0]
for j in range(h):
cl = []
for i in range(w):
cl.append(scp[i, j])
h = ' '.join(map(str, cl))
m = h.find(n)
if m >= 0:
m = len(h[0:m].split(" "))
print
"Signature found on %d, %d" % (m, j)
# self.offset = (m, j-18)
self.offset = (m + 1, j + 4)
break
def addUniqueData(self, filename, inputType, normalized=False):
import os
if not os.path.isfile(filename):
raise Exception("addUniqueData : \"" + filename + "\" is not a file")
if inputType >= DataCategory.TRAIN and inputType <= DataCategory.TEST:
im = Normalize(self.Size(), filename, offset=self.__offset)
array = []
import ImageOps
if self.__grayScale:
im = ImageOps.grayscale(im)
if self.__negate:
im = ImageOps.invert(im)
if normalized:
array = [float(x) / 255. for x in list(im.getdata())]
else:
array = [x for x in list(im.getdata())]
else:
for p in list(im.getdata()):
# array.append(zip([float(x)/255. for x in p]))
for i in xrange(len(p)):
if normalized:
array.append(float(p[i]) / 255.)
else:
array.append(p[i])
array = [x for x in array]
self.Inputs()[inputType].append(array)
import string
groundTruth = string.split(os.path.splitext(os.path.split(filename)[1])[0], '-')[0]
self.Targets()[inputType].append(int(groundTruth))
else:
raise Exception("Incorrect DataCategory")
def getSeatThree():
im = ImageOps.grayscale(ImageGrab.grab
((xPad+227,yPad+60,xPad+290,yPad+76)))
a = array(im.getcolors())
## im.save(os.getcwd() + '\\SeatThreeBubble.png', 'PNG')
print 'table 3 bubble = %d' % a.sum()
return a.sum()
def display_file(epd, file_name):
"""display centre of image then resized image"""
image = Image.open(file_name)
image = ImageOps.grayscale(image)
# crop to the middle
w,h = image.size
x = w / 2 - epd.width / 2
y = h / 2 - epd.height / 2
cropped = image.crop((x, y, x + epd.width, y + epd.height))
bw = cropped.convert("1", dither=Image.FLOYDSTEINBERG)
epd.display(bw)
epd.update()
time.sleep(3) # delay in seconds
rs = image.resize((epd.width, epd.height))
bw = rs.convert("1", dither=Image.FLOYDSTEINBERG)
epd.display(bw)
epd.update()
time.sleep(3) # delay in seconds
def getSeatFour():
im = ImageOps.grayscale(ImageGrab.grab
((xPad+328,yPad+60,xPad+391,yPad+76)))
a = array(im.getcolors())
## im.save(os.getcwd() + '\\SeatFourBubble.png', 'PNG')
print 'table 4 bubble = %d' % a.sum()
return a.sum()
def game_logic(screen, dt, player):
global TRACES
im = screen_grab(box=PLAYABLE_BOX)
#return True
#im = screen_grab(box=PLAYABLE_BOX)
im_gray = ImageOps.grayscale(im)
coords = get_coords()
if coords[0] < 0 or coords[1] < 0:
print "Mouse out"
return False
if im.getpixel(END_GAME_OK) == (232, 97, 1):
return True
if im.getpixel(GET_READY) == (244, 198, 0) or im.getpixel(START_BUTTON) == (217, 83, 14):
return True
diff_array = asarray(ImageChops.difference(im_gray,BACKGROUND_GRAY))
#grayscale_array_to_pygame(screen, diff_array)
bird, pipes = find_elements(diff_array)
draw_game(screen, bird, pipes)
player.see(dt, bird, pipes)
pygame.draw.rect(screen, BLUE, [player.x - 3, player.y - 3, 6, 6])
font = pygame.font.SysFont("monospace", 15)
label = font.render("%d %d"%(player.speed_y, player.accel_y), 1, (255,255,0))
screen.blit(label, (10, FLOOR_Y + 26))
player.play()
return True
def image_file_features(infile, cl_options):
im = Image.open(infile)
hist_features = {}
if cl_options.histogram:
hist_features = array_to_features(im.histogram(), 'pixhist_')
if cl_options.equalize:
im = ImageOps.grayscale( ImageOps.equalize(im) )
if cl_options.blur:
im_blur = scipy.ndimage.gaussian_filter(im, sigma=cl_options.blur)
im = Image.fromarray(numpy.uint8(im_blur)) # from numpy->Grayscale Image
if cl_options.horiz_ema:
# scale to be independent of image size ?????
im_ema = horiz_exp_mov_avg(im, cl_options.horiz_ema)
im = Image.fromarray(numpy.uint8(im_ema)) # from numpy->Grayscale Image
if cl_options.thumb_size:
thumb_size = (cl_options.thumb_size, cl_options.thumb_size)
im.thumbnail(thumb_size, Image.ANTIALIAS)
if cl_options.thumb_dir:
basename = os.path.basename(infile).split('.')[0]
thumb_file = cl_options.thumb_dir + '/' + basename + '.png'
im.save(thumb_file, "png")
pix_features = {}
if cl_options.pixels:
pix_values = im.getdata() # returns a 1-D/flattened sequence of pixel values
pix_features = array_to_features(pix_values, 'pix_')
return dict(pix_features.items() + hist_features.items())
def grab(): #screenshots of the game area
box = (x_padding + 1, y_padding + 1, x_padding + 1824, y_padding + 476)
im = ImageOps.grayscale(ImageGrab.grab(box))
a = array(im.getcolors())
a = a.sum()
print a
return a
def geticonshape(shape, dim_horiz, dim_vert): iconimage = ''.join([shape, '_icon.png']) img = Image.open(iconimage) img = ImageOps.grayscale(img) img = ImageOps.autocontrast(img) img = img.resize((dim_horiz, dim_vert), Image.BILINEAR) return img
def grayscale(image, amount=100):
grayscaled = ImageOps.grayscale(image)
if amount < 100:
grayscaled = imtools.blend(image, grayscaled, amount / 100.0)
if image.mode == "RGBA":
grayscaled.putalpha(imtools.get_alpha(image))
return grayscaled
def composeForFacebook(self,images):
print("composing for facebook")
strip = Image.new('RGB', (self.facebookLayout["width"], self.facebookLayout["width"]), (0,0,0))
count=0
dim=self.facebookLayout["photoDim"]
positions={0:[5,5],1:[dim,5],2:[5,dim],3:[dim,dim]}
#for inFile in glob.glob(os.path.join(imageDir, '*.JPG')):
for img in images:
if count>3:break
# print("\t"+str(inFile))
#img=Image.open(inFile)
posX,posY=positions[count]
bbox=img.getbbox()
img=img.crop(((bbox[2]/2)-(bbox[3]/2),0,(bbox[2]/2)+(bbox[3]/2),bbox[3]))
img=img.resize((dim-10,dim-10))
#img = ImageOps.autocontrast(img, cutoff=2)
if self.grey:
img=ImageOps.grayscale(img)
enh=ImageEnhance.Brightness(img)
img=enh.enhance(0.8)
enh=ImageEnhance.Contrast(img)
img=enh.enhance(1.3)
strip.paste(img,(posX,posY))
count=count+1
overlay=self.facebookLayout["overlay"]
strip.paste(overlay,None,overlay)
#path=os.path.join(imageDir, 'facebookStrip.PNG')
#path=self.saveImageToOutgoing(strip,"facebook")
#dateString=datetime.datetime.now().strftime('%Y-%m-%d_%H-%M')
#path=os.path.join(self.outgoingPath,dateString+'_facebook.PNG')
#strip.save(path, 'PNG')
print("\n")
return [strip,"facebook"]
def transformer(image, seuil, ampl_theta=1):
# Prend en paramètres une image pré-traitée (une image don't il ne reste que les contours) et un seuil qui est une entier naturel compris entre 0 et 255
longueur, hauteur = image.size
image = ImageOps.grayscale(image)
pixels = image.load()
theta_m = math.atan(hauteur/float(longueur))
print theta_m
dim_espace_hough = (180,int(longueur*math.cos(theta_m)+hauteur*math.sin(theta_m)))
image_hough = Image.new("L", (dim_espace_hough[0],dim_espace_hough[1]))
pix = image_hough.load()
za = ImageDraw.Draw(image_hough)
print dim_espace_hough
for x in range(longueur):
for y in range(hauteur):
if pixels[(x,y)] > seuil:
for theta in range(dim_espace_hough[0]):
rho = x * math.cos(math.radians(theta))+ y * math.sin(math.radians(theta))
# print rho
if pix[theta,(int(rho)%dim_espace_hough[1])] == 255:
pass
else:
za.point((theta, (int(rho)%dim_espace_hough[1])), fill = 100 + pix[theta,int(rho)%dim_espace_hough[1]])
pix = image_hough.load()
return image_hough
"""
def grayscale(image, amount=100):
grayscaled = ImageOps.grayscale(image)
if amount < 100:
grayscaled = imtools.blend(image, grayscaled, amount / 100.0)
if image.mode == 'RGBA':
grayscaled.putalpha(imtools.get_alpha(image))
return grayscaled
def grab():
box = (x_pad + 1,y_pad+1,x_pad+640,y_pad+480)
im = ImageOps.grayscale(ImageGrab.grab(box))
a = array(im.getcolors())
a = a.sum()
print a
return a
def grab():
im = ImageOps.grayscale(
ImageGrab.grab(bbox=(x_pad + 1, y_pad + 1, x_pad + 641, y_pad + 480)))
a = array(im.getcolors())
a = a.sum()
print a
return a
def _capture_interesting_frame(self, pad, buffer):
"""
this is the buffer probe which processes every frame that is being
played by the capture pipeline. since the first frame is not random, we
skip this frame by setting the self.first_analyze flag.
if the current frame is found intersting we save it. if not we decrease
self.tries to limit the number of tries
"""
if not self.first_analyze:
#get current buffer's capabilities
caps = buffer.get_caps ()
#we are interested in it's dimension
height, width = caps[0]['height'], caps[0]['width']
#using PIL we grab the image in raw RGB mode from the buffer data
im = Image.frombuffer('RGB', (width, height), buffer.data,'raw', 'RGB', 0, 1)
#here we check the standard variance of a grayscale version of the
#current frame against the BORING_IMAGE_VARIANCE
if ImageStat.Stat(ImageOps.grayscale(im)).var[0] > \
BORING_IMAGE_VARIANCE:
#success! save our interesting image
self.image = im
else:
#the image is just useless... retry...
self.tries -= 1
else:
self.first_analyze = False
return True
def processImage(self, im):
im = im.resize((320, 240))
im = ImageOps.grayscale(im)
im = im.filter(ImageFilter.BLUR)
if not self.prevImage:
self.prevImage = im
return
imd = ImageChops.difference(im, self.prevImage)
def mappoint(pix):
if pix > 20:
return 255
else:
return 0
imbw = imd.point(mappoint)
hist = imbw.histogram()
percentWhitePix = hist[-1] / (hist[0] + hist[-1])
motionDetected = (percentWhitePix > self.DETECTION_THRESHOLD)
self.factory.motionStateMachine.step(motionDetected)
motionSustained = self.factory.motionStateMachine.inSustainedMotion()
print '%d %d' % (motionDetected, motionSustained)
sys.stdout.flush()
self.prevImage = im
def ImageListFile2Array(filename):
patch_size = (8,8)
stride_size = (6,6)
imgArray = None
image_list = open(filename)
for image_file in image_list:
#delete the enter space
image_file = image_file.rstrip()
print image_file
#read images
im = Image.open(image_file)
#convert to grayscal
gray_im = ImageOps.grayscale(im)
w = gray_im.size[0] - patch_size[0]
h = gray_im.size[1] - patch_size[1]
y = 0
while y <= h:
x = 0
while x <= w:
box = (x,y,x+patch_size[0],y+patch_size[1])
crop_im = gray_im.crop(box)
data = np.asarray(crop_im)
data = data.reshape(1,data.size)
if imgArray is None:
imgArray = data
else:
imgArray = np.vstack((imgArray, data))
x+=stride_size[0]
y+=stride_size[1]
return imgArray
def CalcLBP(img, radius=1, neighborPixels=8):
#Function to calculate local binary pattern of an image
#pass in a img
#returns an lbp list
xmax = img.size[0]
ymax = img.size[1]
#convert image to grayscale
grayimage = ImageOps.grayscale(img)
#make a copy to return
returnimage = Image.new("L", (xmax,ymax))
uniform_hist = numpy.zeros(256, int)
#print "uniform_hist = ", uniform_hist
#print "size = ", uniform_hist.ndim
meanRGB = 0
imagearray = grayimage.load()
neighborRGB = numpy.empty([8], dtype=int)
center = (5,5)
radius = 1
angleStep = 360 / neighborPixels
lbp_list = []
for y in range(1, ymax-1, 1):
for x in range(1, xmax-1, 1):
centerRGB = imagearray[x, y]
#print 'Center Pixel = ', x, y
#meanRGB = centerRGB
index = 0
lbp = 0
for ang in range(0, 359, angleStep):
xx = round(x + radius * math.cos(math.radians(ang)))
yy = round(y + radius * math.sin(math.radians(ang)))
neighborRGB[index] = imagearray[xx,yy]
#print 'pixel = ',xx, yy, 'neighbor# = ', index, 'center val = ', centerRGB, 'current pixel val = ', neighborRGB[index]
if imagearray[xx,yy] >= centerRGB:
lbp = lbp + (2**index)
index = index + 1
#print "LBP = ", lbp
#lbp = 0
#for i in range(neighborPixels):
#comparing against mean adds a sec vs comparing against center pixel
#if neighborRGB[i] >= meanRGB:
# if neighborRGB[i] >= centerRGB:
# lbp = lbp + (2**i)
#comparing against mean adds a sec vs comparing against center pixel
#meanRGB= centerRGB + neighborRGB.sum()
#meanRGB = meanRGB / (neighbors+1)
#compute Improved local binary pattern (center pixel vs the mean of neighbors)
#putpixel adds 1 second vs storing to array
uniform = is_uniformLBP( digitlist(lbp, numdigits=8, base=2))
#print "LBP = ", lbp, " bits = ", decimal2binary(lbp), digitlist(lbp, numdigits=8, base=2), " is_uniformLBP(digits) = ", uniform
get_uniform_variations(lbp)
lbp_list.append(lbp)
#time.sleep(1)
returnimage.putpixel((x,y), lbp)
#print "LBP LIST = ", lbp_list, " count = ", len(lbp_list)
LBP_Section_Histogram = get_LBP_uniform_histogram(lbp_list)
#print 'LBP fingerprint for that section = ', LBP_Section_Histogram
#print returnimage.histogram()
#return returnimage
return LBP_Section_Histogram
def triangles(original, n=30, size=150, width=700,
height=700, min_distance=70, opacity=220):
original = original.convert('RGB')
colours = util.get_dominant_colours(original, 8)
colours_ordered = util.order_colours_by_brightness(colours)
brightest_colour = list(random.choice(colours_ordered[:3]))
brightest_colour.append(0)
new = Image.new('RGBA', (width, height), tuple(brightest_colour))
draw = aggdraw.Draw(new)
centres = []
def is_too_close(x, y):
for centre in centres:
if math.sqrt(math.pow(centre[0] - x, 2) +
math.pow(centre[1] - y, 2)) < min_distance:
return True
return False
for i in xrange(n):
colour = tuple(colours[int(random.randint(0, len(colours) - 1))])
x = random.randint(size / 2, width - 1 - size / 2)
y = random.randint(size / 2, height - 1 - size / 2)
if is_too_close(x, y):
continue
centres.append((x, y))
brush = aggdraw.Brush(colour, opacity)
points = get_triangle_path(x, y, size / 2, size / 2)
draw.polygon(points, None, brush)
draw.flush()
brightest_colour = brightest_colour[0:3]
texture = Image.open(os.path.dirname(os.path.abspath(__file__)) + '/' +
'assets/airbrush.png')
texture = texture.convert('RGBA')
r, g, b, a = texture.split()
texture = ImageOps.grayscale(texture)
texture = ImageOps.colorize(texture, (0, 0, 0), tuple(brightest_colour))
texture = texture.convert('RGBA')
texture.putalpha(a)
r, g, b, a = new.split()
texture = texture.crop((0, 0, width, height))
texture_layer = Image.new('RGBA', (width, height), (0, 0, 0, 0))
texture_layer.paste(texture, mask=new)
new.paste(texture_layer, mask=texture_layer)
im = Image.new('RGB', (width, height), tuple(brightest_colour))
im.paste(new, mask=a)
return im
def get_seat_six():
box = (x_pad + 1 + 636, y_pad + 74, x_pad + 710, y_pad + 90)
im = ImageOps.grayscale(ImageGrab.grab(box))
# im.save(os.getcwd() + '\\seat_six__' + str(int(time.time())) + '.png', 'PNG')
a = array(im.getcolors())
a = a.sum()
print(a)
return a
def get_seat_two():
im = ImageOps.grayscale(
ImageGrab.grab(bbox=(x_pad + 129, y_pad + 61, x_pad + 129 + 59,
y_pad + 61 + 15)))
a = array(im.getcolors())
a = a.sum()
##im.save(os.getcwd() + '\\seat_two__' + str(int(time.time())) + '.png', 'PNG')
return a
def get_seat_one():
box = (x_pad + 29, y_pad + 72, x_pad + 103, y_pad + 89)
im = ImageOps.grayscale(ImageGrab.grab(box))
# im.save(os.getcwd() + '\\seat_one__' + str(int(time.time())) + '.png', 'PNG')
a = array(im.getcolors())
a = a.sum()
print(a)
return a
def grayscale_grab():
box = (x_pad, y_pad, x_pad + 640, y_pad + 480)
im = ImageOps.grayscale(ImageGrab.grab(box))
a = array(im.getcolors())
a = a.sum()
print a
# im.save(os.getcwd() + '\\Snap__' + str(int(time.time())) + '.png', 'PNG')
return a
def getGrayscale(cords):
global inc
box = (cords[0][0]+x_pad, cords[0][1] + y_pad, cords[1][0] + x_pad, cords[1][1] + y_pad)
im = ImageOps.grayscale(ImageGrab.grab(box))
#im.save(os.getcwd() + '\\full_snap__' + str(int(time.time())) + '.png', 'PNG')
a = array(im.getcolors())
a = a.sum()
return a
def continue_box():
box = (c+112,b+70,c+455,b+342)
im = ImageOps.grayscale(ImageGrab.grab(box))
a = array(im.getcolors())
a = a.sum()
print a
##im.save(os.getcwd() + '\\seat_six__' + str(int(time.time())) + '.png', 'PNG')
return a
def grab():
box = (x_pad + 70, y_pad + 150, x_pad + 250, y_pad + 151)
im = ImageOps.grayscale(ImageGrab.grab(box))
#im.save(os.getcwd() + '\\full_snap__' + str(int(time.time())) + '.png', 'PNG')
b = array(im.getcolors())
b = b.sum()
print b
return b
def get_slot3():
box = (748, 397, 762, 402)
im = ImageOps.grayscale(ImageGrab.grab(box))
a = array(im.getcolors())
a = a.sum()
print 'T1: ' + str(a)
im.save(os.getcwd() + '\\slot_three__' + str(int(time.time())) + '.png', 'PNG')
return a
def get_seat_six():
box = (c+474,b+55,c+474+55,b+55+12)
im = ImageOps.grayscale(ImageGrab.grab(box))
a = array(im.getcolors())
a = a.sum()
##print "seat 6", a
im.save(os.getcwd() + '\\seat_six__' + str(int(time.time())) + '.png', 'PNG')
return a
def get_slot4():
box = (747, 371, 762, 376)
im = ImageOps.grayscale(ImageGrab.grab(box))
a = array(im.getcolors())
a = a.sum()
print 'T2: ' + str(a)
im.save(os.getcwd() + '\\slot_four__' + str(int(time.time())) + '.png', 'PNG')
return a
def get_seat_six(): box = (X_PAD + 531, Y_PAD + 61, X_PAD + 531+63, Y_PAD + 61 + 16) im = ImageOps.grayscale(ImageGrab.grab(box)) a = array(im.getcolors()) a = a.sum() #print a #im.save(CWD + "\\seat_six__" + str(int(time.time())) + '.png', "PNG") return a
def getSeatSix():
box = (x_pad + 530, y_pad + 63, x_pad + 530 + 64, y_pad + 63 + 11)
im = ImageOps.grayscale(ImageGrab.grab(box))
a = array(im.getcolors())
a = a.sum()
print a
im.save(os.getcwd() + '\\seat_six__' + str(int(time.time())) + '.png',
'PNG')
return a
def build_mat_from_grayscale_image(path):
img = Image.open(str(path))
img = ImageOps.grayscale(img)
imgData = img.getdata()
imgTab = numpy.array(imgData)
w, h = img.size
imgMat = numpy.reshape(imgTab, (h, w))
return imgMat
def get_all_grayscale_sums(chat_bubble_coordinates):
seat_color_sums = [0, 0, 0, 0, 0, 0]
for seat in range(0, 6):
image = ImageOps.grayscale(
ImageGrab.grab(chat_bubble_coordinates[seat]))
color_sum = array(image.getcolors())
color_sum = color_sum.sum()
seat_color_sums[seat] = color_sum
return seat_color_sums
def _get_image(self,p):
"""
If necessary as indicated by the parameters, get a new image,
assign it to self._image and return True. If no new image is
needed, return False.
"""
if p.filename!=self.last_filename or self._image is None:
self.last_filename=p.filename
self._image = ImageOps.grayscale(Image.open(p.filename))
return self._image
