def symbols_in(image): symbols = [] cut = [] pixels = 0 for i in range(image.size[0]): whitespace = True for j in range(image.size[1]): if image.getpixel((i, j)) != (255, 255, 255): whitespace = False break if whitespace: if pixels > 0: cut = cut + [i] pixels = 0 else: pixels = pixels + 1 if pixels > 0: cut = cut + [i] pixels = 0 x = 0 for i in range(len(cut)): image = ImageOps.invert(image) crop = image.crop([x, 0, cut[i], image.size[1]]) image = ImageOps.invert(image) x = cut[i] symbols = symbols + [ImageOps.invert(crop)] return symbols
def draw_mask(angle,width,height,offset_init,offset_A,offset_focus,offset_B):
offset = height*offset_init/100
vectorA = offset+offset_A*height/100
focus = vectorA+offset_focus*height/100
vectorB = focus+offset_B*height/100
mask = Image.new('L', (width,height))
mask_1px = Image.new('L', (1,height))
draw_1px = ImageDraw.Draw(mask_1px)
for y in range (0,offset): # draw white zone
draw_1px.point((0,y),255)
for y in range (offset,vectorA): # draw vectorA
draw_1px.point((0,y),(vectorA-y)*(255/(vectorA-offset)))
for y in range (vectorA,focus): # draw white zone
draw_1px.point((0,y),0)
for y in range (focus,vectorB): # draw vectorB
draw_1px.point((0,y),255-(vectorB-y)*(255/(vectorB-focus)))
for y in range (vectorB,height): # draw white zone
draw_1px.point((0,y),255)
m_width,m_height = mask.size
mask_1px = mask_1px.resize((int(m_width*3),m_height), Image.ANTIALIAS)
mask_1px = ImageOps.invert(mask_1px)
mask_top = mask_1px.rotate(angle,Image.NEAREST,1)
mask_top = ImageOps.invert(mask_top)
mask.convert("RGBA")
n_width,n_height = mask_top.size
mask.paste(mask_top,(-n_width/2,-(n_height/2-height/2)))
mask.convert("L")
return mask
def process(self, _edObject=None):
"""
This is the main method of the plugin, it does the job, not the EDNA name conversions which were done in the preprocess.
"""
EDPluginExec.process(self)
EDVerbose.DEBUG("EDPluginPyarchThumbnailv10.process")
if self.inputFilename:
# Read the image using FABIO
fabioImage = openimage(self.inputFilename)
# Convert an FabioImage to a PIL image
npaImageRaw = fabioImage.data
iMinLevel = 2
iMaxLevel = 1000
npaImageRaw = numpy.minimum(npaImageRaw, iMaxLevel * numpy.ones_like(npaImageRaw))
npaImageRaw = numpy.maximum(npaImageRaw, iMinLevel * numpy.ones_like(npaImageRaw))
npaImage = scipy.ndimage.morphology.grey_dilation(npaImageRaw, size=(5, 5))
npaImageThumb = scipy.ndimage.morphology.grey_dilation(npaImageRaw, size=(10, 10))
dtype = str(npaImage.dtype)
if dtype == "uint8":
NPAImageFloat = npaImage.astype("float") / 255.0
NPAImageFloatThumb = npaImageThumb.astype("float") / 255.0
elif dtype == "uint16":
NPAImageFloat = npaImage.astype("float") / 65535.0
NPAImageFloatThumb = npaImageThumb.astype("float") / 65535.0
else: #for float or whatever
vmin = npaImage.min()
vmax = npaImage.max()
NPAImageFloat = (npaImage.astype(float) - vmin) / (vmax - vmin)
vminThumb = npaImageThumb.min()
vmaxThumb = npaImageThumb.max()
NPAImageFloatThumb = (npaImageThumb.astype(float) - vminThumb) / (vmax - vminThumb)
NPAImageInt = (255.0 * (NPAImageFloat ** 0.3)).astype("uint8")
NPAImageIntThumb = (255.0 * (NPAImageFloatThumb ** 0.3)).astype("uint8")
pilImage = Image.fromarray(NPAImageInt, 'L')
pilImageThumb = Image.fromarray(NPAImageIntThumb, 'L')
# For ISPyB we use for the moment only 1024x1024 and 256x256
pilImage.thumbnail((1024, 1024), Image.ANTIALIAS)
pilImageThumb.thumbnail((256, 256), Image.ANTIALIAS)
pilImage = ImageOps.invert(pilImage)
pilImageThumb = ImageOps.invert(pilImageThumb)
self.synchronizeOn()
if 1024 * 1024 > ImageFile.MAXBLOCK:
ImageFile.MAXBLOCK = 1024 * 1024
pilImage.save(self.strOutputPath, "JPEG", quality=50, optimize=True)
pilImageThumb.save(self.strOutputPathThumb, "JPEG", quality=85, optimize=True)
self.synchronizeOff()
def threshold(img, thresh): """Threshold an image""" pilIMG1 = Image.fromarray(img); pilInverted1 = ImageOps.invert(pilIMG1); inverted = numpy.asarray(pilInverted1); r, t = cv2.threshold(inverted, thresh, 0, type=cv.CV_THRESH_TOZERO); pilIMG2 = Image.fromarray(t); pilInverted2 = ImageOps.invert(pilIMG2); thresholded = numpy.asarray(pilInverted2); return thresholded;
def _derotationTest(self, imageName):
image = samples.getSample("algorithmTests", imageName)[0]
inverted = ImageOps.invert(image.convert("L"))
before = derotate._getAngle(inverted)
derotated = derotate.derotate(image)
invertedDerotated = ImageOps.invert(derotated)
after = derotate._getAngle(invertedDerotated)
self.assertLessEqual(abs(after), abs(before))
self.assertLessEqual(abs(after), 10.0)
def threshold(img, thresh): """Threshold an image""" pilIMG1 = Image.fromarray(img); pilInverted1 = ImageOps.invert(pilIMG1); inverted = np.asarray(pilInverted1); r, t = cv2.threshold(inverted, thresh, 0, type=cv.CV_THRESH_TOZERO); pilIMG2 = Image.fromarray(t); pilInverted2 = ImageOps.invert(pilIMG2); thresholded = np.asarray(pilInverted2); return thresholded;
def _derotationTest(self, imageName):
image = samples.getSample("algorithmTests", imageName)[0]
inverted = ImageOps.invert(image.convert("L"))
before = derotate._getAngle(inverted)
derotated = derotate.derotate(image)
invertedDerotated = ImageOps.invert(derotated)
after = derotate._getAngle(invertedDerotated)
self.assertLessEqual(abs(after), abs(before))
self.assertLessEqual(abs(after), 10.0)
def threshold(img, thresh):
"""Threshold an image"""
pilIMG1 = Image.fromarray(img)
pilInverted1 = ImageOps.invert(pilIMG1)
inverted = numpy.asarray(pilInverted1)
r, t = cv2.threshold(inverted, thresh, 0, type=cv.CV_THRESH_TOZERO)
pilIMG2 = Image.fromarray(t)
pilInverted2 = ImageOps.invert(pilIMG2)
thresholded = numpy.asarray(pilInverted2)
return thresholded
def WriteLayerIMG(ifn, z, allpoints, siz, scale, pan, colour, mode):
scx, scy = scale
panx, pany = pan
sizex, sizey = siz
img = Image.new(mode, (int(sizex), int(sizey)), colour[0])
draw = ImageDraw.Draw(img)
allpoints = ContourNesting(allpoints)
# sort into core and cavity:
cores = []
cavities = []
for cc, points in allpoints:
iscavity = cc == "cavity" or cc == True
if iscavity:
cavities.append(points)
else:
cores.append(points)
for cavity, points in allpoints:
iscavity = cavity == "cavity" or cavity == True
pts = [(x * scx + panx, y * scy + pany) for x, y in points]
if len(pts) == 1 or pts[0] != pts[-1]:
draw.line(pts, fill=colour[2])
ms = 3 # 3 pixel marker
for x, y in pts:
draw.polygon([(x - ms, y - ms), (x + ms, y - ms), (x + ms, y + ms), (x - ms, y + ms)], fill=colour[2])
else:
draw.polygon(pts, fill=(iscavity and colour[1] or colour[2]))
# -- Additions begin here --
invertedImage = ImageOps.invert(img)
if invertedImage.getbbox():
# Set image to 75% of its original size
invertedImage = invertedImage.resize((365,411))
invertedImage = ImageOps.invert(invertedImage)
img_w,img_h=invertedImage.size
background = Image.new('RGB', (608,684), (255, 255, 255))
bg_w,bg_h=background.size
offset=((bg_w-img_w)/2, (bg_h-img_h)/2)
background.paste(invertedImage,offset)
newBackground = ImageOps.invert(background)
#invertedImage = invertedImage.resize((304,342))
newBackground.save(ifn)
else:
open(ifn[:-3]+"temp","w")
def mask_q0(self, pixbuf, selection):
q0_cell_size = 8
w = selection[2]
h = selection[3]
ow = pixbuf.get_width()
oh = pixbuf.get_height()
im = Image.new("RGB", (w, h))
fullimage = Image.fromstring("RGB", (ow, oh), pixbuf.get_pixels())
temp = fullimage.crop((selection[0], selection[1], selection[0] + w, selection[1] + h))
cell_width = w / q0_cell_size
cell_height = h / q0_cell_size
for y in xrange(cell_height):
for x in xrange(cell_width):
px = q0_cell_size * x
py = q0_cell_size * y
for yy in xrange(q0_cell_size):
for xx in xrange(q0_cell_size):
im.putpixel(((px + q0_cell_size - xx - 1), (py + q0_cell_size - yy - 1)), temp.getpixel(((px + xx), (py + yy))))
im = ImageOps.invert(im)
fullimage.paste(im, (selection[0], selection[1]))
return gtk.gdk.pixbuf_new_from_data(fullimage.tostring(), gtk.gdk.COLORSPACE_RGB, False, 8, ow, oh, 3 * ow)
def _measure_photo(self, i):
'''Record and calculate various attributes of a photo'''
# open file
image = Image.open(self.photo_paths[i])
# get x & y pixel counts
width, height = image.size
self.image_size_pixels[i] = [height, width]
# find object in image: calc size in pixels
image_inverted = ImageOps.invert(image)
bbox = image_inverted.getbbox()
w = bbox[2] - bbox[0]
h = bbox[3] - bbox[1]
self.object_size_pixels[i] = [h, w]
# calc size of object in radians
is_vertical = False
if height > width:
is_vertical = True
width_frac = (w / float(width))
height_frac = (h / float(height))
if is_vertical:
width_rads = width_frac * self.fov_smaller
height_rads = height_frac * self.fov_larger
else:
width_rads = width_frac * self.fov_larger
height_rads = height_frac * self.fov_smaller
self.object_size_radians[i] = [height_rads, width_rads]
def imagetogcode(image, f):
img = ImageOps.invert(image)
width, height = img.size
f.write("; Image pixel size: "+str(width)+"x"+str(height)+"\n");
pixels = list(img.getdata())
pixels = [pixels[i * width:(i + 1) * width] for i in xrange(height)]
forward = True
def get_chunks(arr, chunk_size = 51):
chunks = [ arr[start:start+chunk_size] for start in range(0, len(arr), chunk_size)]
return chunks
for row in reversed(pixels):
first = True
if not forward:
result_row = row[::-1]
else:
result_row = row
for chunk in get_chunks(result_row):
if first:
if forward:
f.write("G7 N1 ")
else:
f.write("G7 N0 ")
first = not first
else:
f.write ("G7")
b64 = base64.b64encode("".join(chr(x) for x in chunk))
f.write("L"+str(len(b64))+" ")
f.write("D"+b64+ "\n")
forward = not forward
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 __call__(self, file_name):
file_path = download_image_to_cache(file_name, self.cache)
im = Image.open(file_path)
if im.mode != self.mode:
im = im.convert(self.mode)
if np.all(im.size != self.resize_to):
new_shape = (int(self.resize_to[0]), int(self.resize_to[1]))
im = im.resize(new_shape, Image.ANTIALIAS)
if self.mask is not None:
mask = self.mask
tmask = ImageOps.invert(mask.convert('RGBA').split()[-1])
im = Image.composite(im, mask, tmask).convert(self.mode)
if self._crop != (0, 0,) + self.resize_to:
im = im.crop(self._crop)
l, t, r, b = self._crop
assert im.size == (r - l, b - t)
imval = np.asarray(im, self.dtype)
rval = imval
if self.normalize:
rval -= rval.mean()
rval /= max(rval.std(), 1e-3)
else:
rval /= 255.0
assert rval.shape[:2] == self.resize_to
return rval
def execute(self):
import Image
import ImageOps
i = Image.open(self.target)
i = i.convert("RGB")
if getattr(self, 'brightness', None):
i = i.point(lambda p: p * self.brightness)
r, g, b = i.split()
a = {
'r': r,
'g': g,
'b': b,
'x': Image.new("L", r.size, color=0),
}.get(self.level)
if not a:
a = Image.new("L", r.size, color=self.level)
if self.level == 'x':
pxi = i.load()
pxa = a.load()
for y in xrange(a.size[1]):
for x in xrange(a.size[0]):
p = pxi[x, y]
pxa[x, y] = int((p[0] + p[1] + p[2]) / 3.0)
if getattr(self, 'invert_alpha', None):
a = ImageOps.invert(a)
i2 = Image.merge("RGBA", (r, g, b, a))
i2.save(self.target)
"""
def preprocess_image(f):
io = StringIO(f)
im = Image.open(io)
im = ImageOps.autocontrast(im)
im = brighten(im, 2.1)
im = ImageOps.grayscale(im)
im = ImageOps.invert(im)
im = im.point(lambda i: 250 if i > 1 else i)
im = ImageOps.invert(im)
im = clear_noise(im, 254, 1, 255)
io = StringIO()
im.save(io, "png")
ret = io.getvalue()
io.close()
return ret
def on_send_button_clicked(self, event):
if self.monitor is None:
img_data = self.painter.get_image_data()
#prepare an image
w, h, d = img_data.shape
img = Image.fromstring( "RGBA", ( w ,h ), img_data.tostring() )
img_gs = img.convert('L')
# thumbnail_size = (28, 28)
# img_gs.thumbnail(thumbnail_size)
img_gs_inv = ImageOps.invert(img_gs)
else:
img_data = self.monitor.get_image_data()
# img_gs_inv = 255 - img_data
img_gs_inv = img_data
img_gs_inv_thumbnail, bound_rect = utils.get_char_img_thumbnail_helper(np.asarray(img_gs_inv))
# img.show()
self.img_data = np.asarray(img_gs_inv_thumbnail).flatten().astype(np.float32) * 1./255.
if self.on_send_usr_callback is not None:
self.on_send_usr_callback(self)
#update the target canvas
self.ax_target.imshow(self.img_data.reshape((28, 28)))
self.target_canvas.draw()
return
def on_send_incomplete_button_clicked(self, event):
if self.monitor is None:
img_data = self.painter.get_image_data()
else:
img_data = self.monitor.get_image_data()
#prepare an image
w, h, d = img_data.shape
img = Image.fromstring( "RGBA", ( w ,h ), img_data.tostring() )
img_gs = img.convert('L')
# thumbnail_size = (28, 28)
# img_gs.thumbnail(thumbnail_size)
img_gs_inv = ImageOps.invert(img_gs)
img_gs_inv_thumbnail, bound_rect = utils.get_char_img_thumbnail_helper(np.asarray(img_gs_inv))
# img.show()
self.img_data = np.asarray(img_gs_inv_thumbnail).flatten().astype(np.float32) * 1./255.
#cover a fraction of the image to produce incomplete data
self.fraction_idx = (np.random.rand(2) > 0.5).astype(int)
self.img_incomplete_data = self.img_data.reshape((28, 28))
self.img_incomplete_data[14*self.fraction_idx[0]:14*(self.fraction_idx[0]+1), 14*self.fraction_idx[1]:14*(self.fraction_idx[1]+1)] = 0
self.img_incomplete_data = self.img_incomplete_data.flatten()
if self.on_send_incomplete_usr_callback is not None:
self.on_send_incomplete_usr_callback(self)
#update the target canvas
self.ax_target.imshow(self.img_data.reshape((28, 28)))
self.target_canvas.draw()
return
def gen_captcha(text, fontname, fontsize, file_name):
"""Generate a captcha image"""
# white text on a black background
bgcolor = 0x0
fgcolor = 0xffffff
# create a font object
font = ImageFont.truetype(fontname, fontsize)
# determine dimensions of the text
dim = font.getsize(text)
# create a new image significantly larger that the text
edge = max(dim[0], dim[1]) + 2 * min(dim[0], dim[1])
im = Image.new('RGB', (edge, edge), bgcolor)
d = ImageDraw.Draw(im)
x, y = im.size
# add the text to the image
d.text((x / 2 - dim[0] / 2, y / 2 - dim[1] / 2),
text,
font=font,
fill=fgcolor)
k = 2
wob = 0.09 * dim[1]
rot = 45
# Apply lots of small stirring operations, rather than a few large ones
# in order to get some uniformity of treatment, whilst
# maintaining randomness
for i in range(k):
im = wobbly_copy(im, wob, bgcolor, i * 2 + 3, rot + 0)
im = wobbly_copy(im, wob, bgcolor, i * 2 + 1, rot + 45)
im = wobbly_copy(im, wob, bgcolor, i * 2 + 2, rot + 90)
rot += 30
# now get the bounding box of the nonzero parts of the image
bbox = im.getbbox()
bord = min(dim[0], dim[1]) / 4 # a bit of a border
im = im.crop(
(bbox[0] - bord, bbox[1] - bord, bbox[2] + bord, bbox[3] + bord))
# Create noise
nblock = 4
nsize = (im.size[0] / nblock, im.size[1] / nblock)
noise = Image.new('L', nsize, bgcolor)
data = noise.load()
for x in range(nsize[0]):
for y in range(nsize[1]):
r = random.randint(0, 65)
gradient = 70 * x / nsize[0]
data[x, y] = r + gradient
# Turn speckles into blobs
noise = noise.resize(im.size, Image.BILINEAR)
# Add to the image
im = ImageMath.eval('convert(convert(a, "L") / 3 + b, "RGB")',
a=im,
b=noise)
# and turn into black on white
im = ImageOps.invert(im)
# save the image, in format determined from filename
im.save(file_name)
def showResult(result, dims, k=2):
i = Image.new("L", dims)
i.putdata(result, (255 / (k - 1)))
i = i.crop(i.getbbox())
i = ImageOps.invert(i)
i.load()
#i.show()
i.save("bs.png","PNG")
def push_face(weather):
image = Image.new('1', (EPD_WIDTH, EPD_HEIGHT), 1)
draw = ImageDraw.Draw(image)
tt_img = get_sessions()
image.paste(tt_img, (0, EPD_HEIGHT - TT_HEIGHT))
time_y = TOP_MARGIN
time_x = LEFT_MARGIN
#draw.rectangle(((LEFT_MARGIN, TOP_MARGIN), (640-256, 296)))
#draw.rectangle(((640-256, TOP_MARGIN), (640, 256)))
#draw.rectangle(((640-256, 256), (640, 296)))
draw.rectangle(((1, 296), (639, 383)))
time, day, date = get_clock_data()
time_width = EPD_WIDTH - LEFT_MARGIN - IMAGE_SIZE
time_sp_y = (EPD_HEIGHT - TT_HEIGHT) // 2
day_sp_y = time_sp_y // 2
date_sp_y = day_sp_y
time_font_size = max_font_size(TIME_FONT, time, time_width, time_sp_y)
day_font_size = max_font_size(TIME_FONT, day, time_width, day_sp_y)
date_font_size = max_font_size(TIME_FONT, date, time_width, date_sp_y)
time_tf = ImageFont.truetype(TIME_FONT, time_font_size)
day_tf = ImageFont.truetype(TIME_FONT, day_font_size)
date_tf = ImageFont.truetype(TIME_FONT, date_font_size)
time_height, time_offset = get_line_height(time, time_tf)
time_height = time_tf.getsize(time)[1]
day_height, date_offset = get_line_height(day, day_tf)
day_height = day_tf.getsize(day)[1]
day_y = time_y + time_height
date_y = day_y + day_height
draw.text((time_x, time_y), time, font=time_tf, fill=0)
draw.text((time_x, day_y), day, font=day_tf, fill=0)
draw.text((time_x, date_y), date, font=date_tf, fill=0)
weather_img = Image.open(LIB_DIR + weather.img, 'r')
image.paste(weather_img, (EPD_WIDTH - IMAGE_SIZE, TOP_MARGIN),
mask=weather_img)
weather_text = weather.condition.text + ', ' + weather.condition.temp
weather_font_size = max_font_size(WEATHER_FONT, weather_text + 'o',
IMAGE_SIZE,
EPD_HEIGHT - IMAGE_SIZE - TT_HEIGHT)
weather_tf = ImageFont.truetype(WEATHER_FONT, weather_font_size)
weather_text_width, weather_text_height = weather_tf.getsize(weather_text)
weather_text_x = EPD_WIDTH - IMAGE_SIZE + (IMAGE_SIZE -
weather_text_width) // 2
weather_text_position = (weather_text_x, IMAGE_SIZE)
draw.text(weather_text_position, weather_text, font=weather_tf, fill=0)
degree_top = (weather_text_position[0] + weather_text_width,
weather_text_position[1])
degree_bottom = (degree_top[0] + 7, degree_top[1] + 7)
degree_box = (degree_top, degree_bottom)
draw.ellipse(degree_box, fill=None, outline='black')
if weather.night:
image = image.convert('L')
image = ImageOps.invert(image)
epd.display_frame(epd.get_frame_buffer(image))
def add_image(self, image):
"""
Adds the data of a PIL image as a frame to the current movie.
"""
if self.inverted:
import ImageOps
image_inv = ImageOps.invert(image)
self._add_file(image_inv.save)
else:
self._add_file(image.save)
def get_blinds(self):
box = (39, 522, 288, 552)
time.sleep(2)
img = ImageGrab.grab(box)
img = img.convert('L')
enh = ImageEnhance.Contrast(img)
img = enh.enhance(2)
img = ImageOps.invert(img)
img.show()
print image_to_string(img)
def sketch(image, details_degree=1):
im1 = image.convert('L')
im2 = im1.copy()
im2 = ImageOps.invert(im2)
for i in xrange(details_degree):
im2 = im2.filter(ImageFilter.BLUR)
im1 = ImageMath.eval('convert(min(a * 255/ (256 - b), 255), "L")',
a=im1,
b=im2)
return im1
def sketch(image, details_degree=1):
im1 = image.convert('L')
im2 = im1.copy()
im2 = ImageOps.invert(im2)
for i in xrange(details_degree):
im2 = im2.filter(ImageFilter.BLUR)
im1 = ImageMath.eval('convert(min(a * 255/ (256 - b), 255), "L")',
a=im1,
b=im2)
return im1
def ndarray2image(data, filename):
"""
writes content of float ndarray as .png file.
normalizes content and writes uint8 picture
"""
#scale image to uint8
data = (255.0 / data.max() * (data - data.min())).astype(np.uint8)
im = Image.fromstring("L", (data.shape[1], data.shape[0]), raw.tostring())
im = ImageOps.autocontrast(im)
im = ImageOps.invert(im)
im.save(filename)
def __call__(self, img_ref):
img = img_ref.get_image()
if img.mode == '1':
img = ImageOps.grayscale(img)
elif img.mode != 'L':
return img_ref
h = img.histogram()
if sum(h[:64]) < img.size[0] * img.size[1] / 2:
return img_ref
img = ImageOps.invert(img)
return ImageRef(img)
def gen_captcha(text, fontname, fontsize, file_name):
"""Generate a captcha image"""
# white text on a black background
bgcolor = 0x0
fgcolor = 0xffffff
# create a font object
font = ImageFont.truetype(fontname,fontsize)
# determine dimensions of the text
dim = font.getsize(text)
# create a new image significantly larger that the text
edge = max(dim[0], dim[1]) + 2*min(dim[0], dim[1])
im = Image.new('RGB', (edge, edge), bgcolor)
d = ImageDraw.Draw(im)
x, y = im.size
# add the text to the image
d.text((x/2-dim[0]/2, y/2-dim[1]/2), text, font=font, fill=fgcolor)
k = 2
wob = 0.09*dim[1]
rot = 45
# Apply lots of small stirring operations, rather than a few large ones
# in order to get some uniformity of treatment, whilst
# maintaining randomness
for i in range(k):
im = wobbly_copy(im, wob, bgcolor, i*2+3, rot+0)
im = wobbly_copy(im, wob, bgcolor, i*2+1, rot+45)
im = wobbly_copy(im, wob, bgcolor, i*2+2, rot+90)
rot += 30
# now get the bounding box of the nonzero parts of the image
bbox = im.getbbox()
bord = min(dim[0], dim[1])/4 # a bit of a border
im = im.crop((bbox[0]-bord, bbox[1]-bord, bbox[2]+bord, bbox[3]+bord))
# Create noise
nblock = 4
nsize = (im.size[0] / nblock, im.size[1] / nblock)
noise = Image.new('L', nsize, bgcolor)
data = noise.load()
for x in range(nsize[0]):
for y in range(nsize[1]):
r = random.randint(0, 65)
gradient = 70 * x / nsize[0]
data[x, y] = r + gradient
# Turn speckles into blobs
noise = noise.resize(im.size, Image.BILINEAR)
# Add to the image
im = ImageMath.eval('convert(convert(a, "L") / 3 + b, "RGB")', a=im, b=noise)
# and turn into black on white
im = ImageOps.invert(im)
# save the image, in format determined from filename
im.save(file_name)
def get_sessions():
tt_img = Image.new('1', (EPD_WIDTH, TT_HEIGHT), 1)
tt_connection = sqlite3.connect(LIB_DIR + 'timetable.sqlite')
tt_connection.row_factory = sqlite3.Row
tt_cursor = tt_connection.cursor()
current_time = datetime.datetime.now()
hour = int(current_time.strftime('%H%M'))
day = current_time.strftime('%A')
session_sql = """SELECT s.session_number, s.title, s.start_time, s.end_time,
e.year_group, e.event_details, e.location
FROM sessions s, timetable_days d
LEFT JOIN events e on e.session_number = s.session_number
AND e.day = ?
WHERE s.timetable_code = d.tt_code AND d.day = ?"""
shrt = 50
lng = 78
next_session_x = 0
for row in tt_cursor.execute(session_sql, (day, day)):
start_time = datetime.datetime.strptime(row['start_time'], '%H%M')
end_time = datetime.datetime.strptime(row['end_time'], '%H%M')
title = row['title']
session_number = row['session_number']
year = row['year_group']
event = row['event_details']
location = row['location']
duration = end_time - start_time
long_session = duration.total_seconds() > 50 * 60
if long_session:
cell_width = lng
else:
cell_width = shrt
session_img = Image.new('1', (cell_width, TT_HEIGHT), 1)
session_canvas = ImageDraw.Draw(session_img)
text_y = 0
session_canvas.line((0, 0, 0, TT_HEIGHT))
text_y = write_session_text(text_y, title, cell_width - 2,
session_canvas)
if year:
text_y = write_session_text(text_y, year, cell_width,
session_canvas)
if event:
text_y = write_session_text(text_y, event, cell_width,
session_canvas)
if location:
text_y = write_session_text(text_y, location, cell_width,
session_canvas)
if int(row['start_time']) <= hour and hour <= int(row['end_time']):
session_img = session_img.convert('L')
session_img = ImageOps.invert(session_img)
tt_img.paste(session_img, (next_session_x, 0))
next_session_x = next_session_x + cell_width
return tt_img
def convert( srcimg, manul, w, h, optionString, dstname ):
name = manul.filename
srcw, srch = srcimg.size
ratiow, ratioh = w/float(srcw), h/float(srch)
roi = manul.region
if ratiow != 1 and ratioh != 1:
if ratioh > ratiow:
desth = h
destw = int( math.ceil( srcw * desth / float(srch)) )
else:
destw = w
desth = int( math.ceil( srch * destw / float(srcw)) )
srcimg = srcimg.resize( (destw,desth), Image.ANTIALIAS )
if roi:
(x0,y0), (x1,y1) = roi
x0 *= destw / float(srcw )
x1 *= destw / float(srcw )
y0 *= desth / float(srch )
y1 *= desth / float(srch )
roi = (x0,y0), (x1,y1)
srcw, srch = destw, desth
assert (srcw == w) or (srch == h)
assert (srcw >= w) and (srch >= h)
if srcw > w:
if not roi:
pad = int( (srcw - w) / 2 )
else:
(x0,y0), (x1,y1) = roi
poix = (x0+x1)/2.0
pad = min( srcw - w, max(0, int(poix - w/2)) )
srcimg = srcimg.crop( (pad,0,pad+w-1,h-1) )
elif srch > h:
if not roi:
pad = int( (srch - h) / 2 )
else:
(x0,y0), (x1,y1) = roi
poiy = (y0+y1)/2.0
pad = min( srch - h, max(0,int(poiy - h/2)) )
srcimg = srcimg.crop( (0,pad,w-1,pad+h-1) )
for option in optionString:
if option == "g":
srcimg = ImageOps.grayscale( srcimg )
elif option == "n":
srcimg = ImageOps.invert( srcimg )
elif option == "s":
sepia = 0xff, 0xf0, 0xc0
srcimg = srcimg.convert( "L" )
srcimg.putpalette( [ int( (i/3/255.0) * sepia[i%3] ) for i in range(256*3) ] )
srcimg = srcimg.convert( "RGB" )
# todo locking, write to temp and then copy
srcimg.save( dstname )
return True
def drawing(infile, outfile, blur=25, alpha=1.0):
im1 = Image.open(infile).convert("L")
im2 = im1.copy()
im2 = ImageOps.invert(im2)
for i in range(blur):
im2 = im2.filter(ImageFilter.BLUR)
width, height = im1.size
for x in range(width):
for y in range(height):
a = im1.getpixel((x, y))
b = im2.getpixel((x, y))
im1.putpixel((x, y), dodge(a, b, alpha))
im1.save(outfile)
def add_image(self, image):
"""
Adds the data of a PIL image as a frame to the current movie.
"""
if self.inverted:
try:
import ImageOps
except ImportError:
from PIL import ImageOps
image_inv = ImageOps.invert(image)
self._add_file(image_inv.save)
else:
self._add_file(image.save)
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();
s = max([bbox[2]-bbox[0], bbox[3]-bbox[1]])
center = [(bbox[2]+bbox[0])/2, (bbox[3]+bbox[1])/2]
bbox = [center[0]-s/2, center[1]-s/2, center[0]+s/2, center[1]+s/2]
if bbox:
if im.mode == 'RGBA':
r,g,b,a = im.split()
im = Image.merge('RGB', (r,g,b))
im = ImageOps.invert(im)
crop = im.crop(bbox)
return ImageOps.invert(crop)
else: return im
def _transform_img(img_base64):
img = img_base64.decode("base64")
img = Image.open(StringIO.StringIO(img)).convert('L')
img = ImageOps.invert(img)
img_data = img_to_img_data(img)
img = img.crop(_find_bounds(img_data))
# img.thumbnail((IMG_SIZE-2, IMG_SIZE-2), PIL.Image.NEAREST)
# img_data = img_to_img_data(img)
# img_data = resize(img_data, IMG_SIZE)
img = img.resize((IMG_SIZE, IMG_SIZE))
img_data = img_to_img_data(img)
# return Image.fromarray(img_data), img_data
return img, img_data
def get_line_ccs(im):
high_im = imageutils.binary(im, HIGH_THRESH)
high_im = ImageOps.invert(high_im)
#high_im.save("high_im.pgm")
high_cc_im, high_ccs = ld.find_ccs(high_im)
#print "Num ccs in high: ", len(high_ccs)
#map(lambda cc: cc.display(), high_ccs)
high_ccs = filter(lambda cc: cc_size(cc, high_cc_im.size), high_ccs)
#print "Num ccs in high after filtering: ", len(high_ccs)
#map(lambda cc: cc.display(), high_ccs)
cc_points = map(lambda cc: cc.coords[0], high_ccs)
low_im = imageutils.binary(im, LOW_THRESH)
low_im = ImageOps.invert(low_im)
#low_im.save("low_im.pgm")
low_cc_im, low_ccs = ld.find_ccs(low_im)
#print "Num ccs in low: ", len(low_ccs)
#map(lambda cc: cc.display(), low_ccs)
low_ccs = filter(lambda cc: cc_contains_any(cc, cc_points), low_ccs)
#print "Num ccs in low after filtering: ", len(low_ccs)
#map(lambda cc: cc.display(), low_ccs)
return low_ccs
def conn_comp(outname):
'''
Returns the number of connected components. Has to invert the file first since
we want the number of black components (assumes white components is always 1)
then uses scipy library to get number of disconnected components.
'''
#first invert the image
im = Image.open(outname)
inverted = io.invert(im)
inverted.save('inverted.ppm')
image = ndimage.imread('inverted.ppm')
a, num_comp = ndimage.measurements.label(image)
return num_comp
def process(self, _edObject=None):
EDPluginExec.process(self)
imageFileName = os.path.basename(self.dataInput.image.path.value)
# Default format
strSuffix = "jpg"
strPILFormat = "JPEG"
# Check if format is provided
if self.dataInput.format is not None:
strFormat = self.dataInput.format.value
if strFormat.lower() == "png":
strSuffix = "png"
strPILFormat = "PNG"
# The following code has been adapted from EDPluginExecThumbnail written by J.Kieffer
fabioImage = fabio.openimage.openimage(self.dataInput.image.path.value)
numpyImage = fabioImage.data
dtype = numpyImage.dtype
sortedArray = numpyImage.flatten()
sortedArray.sort()
numpyImage = numpy.maximum(
numpyImage,
int(self.minLevel) * numpy.ones_like(numpyImage))
maxLevel = sortedArray[int(
round(float(self.maxLevel) * sortedArray.size / 100.0))]
numpyImage = numpy.minimum(numpyImage,
maxLevel * numpy.ones_like(numpyImage))
numpyImage = scipy.ndimage.morphology.grey_dilation(
numpyImage, (self.dilatation, self.dilatation))
mumpyImageFloat = (numpyImage.astype(numpy.float32)) / float(maxLevel)
numpyImageInt = (mumpyImageFloat * 255.0).astype(numpy.uint8)
pilOutputImage = ImageOps.invert(Image.fromarray(numpyImageInt, 'L'))
if self.dataInput.height is not None and self.dataInput.width is not None:
pilOutputImage = pilOutputImage.resize(
(self.dataInput.width.value, self.dataInput.height.value),
Image.ANTIALIAS)
if self.dataInput.outputPath is None:
outputPath = os.path.join(
self.getWorkingDirectory(),
os.path.splitext(imageFileName)[0] + "." + strSuffix)
else:
outputPath = self.dataInput.outputPath.path.value
self.DEBUG("Output thumbnail path: %s" % outputPath)
self.width, self.height = pilOutputImage.size
if self.width * self.height > ImageFile.MAXBLOCK:
ImageFile.MAXBLOCK = self.width * self.height
pilOutputImage.save(outputPath,
strPILFormat,
quality=85,
optimize=True)
self.dataOutput.thumbnail = XSDataFile(XSDataString(outputPath))
def gen_captcha(text, fontname, fontsize, file_name):
"""Generate a captcha image"""
# white text on a black background
bgcolor = 0x0
fgcolor = 0xffffff
# create a font object
font = ImageFont.truetype(fontname, fontsize)
# determine dimensions of the text
dim = font.getsize(text)
# create a new image significantly larger that the text
edge = max(dim[0], dim[1]) + 2 * min(dim[0], dim[1])
im = Image.new('RGB', (edge, edge), bgcolor)
d = ImageDraw.Draw(im)
x, y = im.size
# add the text to the image
d.text((x / 2 - dim[0] / 2, y / 2 - dim[1] / 2),
text,
font=font,
fill=fgcolor)
k = 3
wob = 0.20 * dim[1] / k
rot = 45
# Apply lots of small stirring operations, rather than a few large ones
# in order to get some uniformity of treatment, whilst
# maintaining randomness
for i in range(k):
# im = wobbly_copy(im, wob, bgcolor, i*2+3, rot+0)
# im = wobbly_copy(im, wob, bgcolor, i*2+1, rot+45)
# im = wobbly_copy(im, wob, bgcolor, i*2+2, rot+90)
im = wobbly_copy(im, wob, bgcolor, i, rot + 0)
im = wobbly_copy(im, wob, bgcolor, i, rot + 45)
im = wobbly_copy(im, wob, bgcolor, i, rot + 90)
rot += 30
# now get the bounding box of the nonzero parts of the image
bbox = im.getbbox()
bord = min(dim[0], dim[1]) / 4 # a bit of a border
im = im.crop(
(bbox[0] - bord, bbox[1] - bord, bbox[2] + bord, bbox[3] + bord))
# and turn into black on white
im = ImageOps.invert(im)
# save the image, in format determined from filename
im.save(file_name)
def paint_lines(picture, coords, direction):
width, height = picture.size
outimg = Image.new('L', (width, height))
outpixels = outimg.load()
v="vertical"
h="horizontal"
print "current coords: ", coords
for coord in coords:
if direction==v:
max_line = height
elif direction==h:
max_line = width
for i in xrange(max_line):
if direction==v:
outpixels[coord,i] = 255
elif direction==h:
#print "fail i: {0}\tfail coord: {1}".format(i, coord)
outpixels[i,coord] = 255
print "coords: ", coords
return Image.blend(ImageOps.invert(outimg).convert("RGB"),picture.convert("RGB"),0.2)
def neg_cb(self, action):
if self.selection is not None and self.selection[4] is False:
w = self.selection[2]
h = self.selection[3]
ow = self.image.get_width()
oh = self.image.get_height()
im = Image.new("RGB", (w, h))
fullimage = Image.fromstring("RGB", (ow, oh),
self.image.get_pixels())
temp = fullimage.crop(
(self.selection[0], self.selection[1], self.selection[0] + w,
self.selection[1] + h))
im = ImageOps.invert(temp)
fullimage.paste(im, (self.selection[0], self.selection[1]))
self.image = gtk.gdk.pixbuf_new_from_data(fullimage.tostring(),
gtk.gdk.COLORSPACE_RGB,
False, 8, ow, oh, ow * 3)
self.invalidate()
def readNumber( cls, frame, cord, invert=False, minval=200, save=False, zoom=2, zmethod=Image.BICUBIC ):
image = ImageOps.grayscale( frame.crop( cord ) )
image = image.convert( 'RGB' )
if invert:
image = ImageOps.invert( image )
image = ImageOps.autocontrast( image )
pixdata = image.load()
for y in xrange( image.size[1] ):
for x in xrange( image.size[0] ):
pix = pixdata[x, y]
if pix[0] > minval and pix[1] > minval and pix[2] > minval:
pixdata[x, y] = ( 255, 255, 255 )
image = image.resize( ( ( cord[2] - cord[0] ) * zoom, ( cord[3] - cord[1] ) * zoom ), zmethod )
image = image.convert( 'RGB' )
if save:
image.save( '%s\\tmp\snapshot__%d.png' % ( os.getcwd(), int( time.time() ) ), 'PNG' )
return image_to_string( image ).strip()
def add_reflection(im, opacity=0.8):
""" Returns the supplied PIL Image (im) with a reflection effect
bgcolor The background color of the reflection gradient
amount The height of the reflection as a percentage of the orignal image
opacity The initial opacity of the reflection gradient
Originally written for the Photologue image management system for Django
and Based on the original concept by Bernd Schlapsi
"""
reflection = im.copy().transpose(Image.FLIP_TOP_BOTTOM)
background = Image.new('RGBA', im.size)
start = int(255 - 255 * opacity)
steps = int(255)
increment = (255 - start) / float(steps)
mask = Image.new('L', (1, 255))
for y in range(255):
if y < steps:
val = int(y * increment + start)
else:
val = 255
mask.putpixel((0, y), val)
alpha_mask = mask.resize(im.size)
reflection = Image.composite(background, reflection, alpha_mask)
invert_im = im.convert('RGB')
real_pos = invert_im.getbbox()
if real_pos[1] == 0:
invert_im = ImageOps.invert(invert_im)
real_pos = invert_im.getbbox()
if real_pos is None:
return im
reflection_height = im.size[1]
reflection = reflection.crop((0, 0, im.size[0], reflection_height))
composite = Image.new('RGBA', (im.size[0], im.size[1] + reflection_height))
reflection_y = real_pos[3] - real_pos[1]
composite.paste(im, (0, 0), im)
composite.paste(reflection, (0, reflection_y), reflection)
return composite
def imagetogcode(image, f):
img = ImageOps.invert(image)
width, height = img.size
f.write("; Image pixel size: " + str(width) + "x" + str(height) + "\n")
pixels = list(img.getdata())
pixels = [pixels[i * width:(i + 1) * width] for i in xrange(height)]
forward = True
def get_chunks(arr, chunk_size=51):
chunks = [
arr[start:start + chunk_size]
for start in range(0, len(arr), chunk_size)
]
return chunks
for row in reversed(pixels):
first = True
if not forward:
result_row = row[::-1]
else:
result_row = row
for chunk in get_chunks(result_row):
if first:
if forward:
f.write("G7 N1 ")
else:
f.write("G7 N0 ")
first = not first
else:
f.write("G7")
b64 = base64.b64encode("".join(chr(x) for x in chunk))
f.write("L" + str(len(b64)) + " ")
f.write("D" + b64 + "\n")
forward = not forward
def convert_image_to_sketch(image):
im1 = image.convert("L")
im2 = im1.copy()
im2 = ImageOps.invert(im2)
blur = 3
for i in range(blur):
im2 = im2.filter(ImageFilter.BLUR)
alpha = 1
width, height = im1.size
for x in range(width):
for y in range(height):
a = im1.getpixel((x, y))
b = im2.getpixel((x, y))
im1.putpixel((x, y), dodge(a, b, alpha))
im1 = im1.convert("RGB")
return im1
def paste(destination, source, box=(0, 0), mask=None, force=False):
""""Pastes the source image into the destination image while using an
alpha channel if available.
:param destination: destination image
:type destination: PIL image object
:param source: source image
:type source: PIL image object
:param box:
The box argument is either a 2-tuple giving the upper left corner,
a 4-tuple defining the left, upper, right, and lower pixel coordinate,
or None (same as (0, 0)). If a 4-tuple is given, the size of the
pasted image must match the size of the region.
:type box: tuple
:param mask: mask or None
:type mask: bool or PIL image object
:param force:
With mask: Force the invert alpha paste or not.
Without mask:
- If ``True`` it will overwrite the alpha channel of the destination
with the alpha channel of the source image. So in that case the
pixels of the destination layer will be abandonned and replaced
by exactly the same pictures of the destination image. This is mostly
what you need if you paste on a transparant canvas.
- If ``False`` this will use a mask when the image has an alpha
channel. In this case pixels of the destination image will appear
through where the source image is transparent.
:type force: bool
"""
# Paste on top
if source == mask:
if has_alpha(source):
# invert_alpha = the transparant pixels of the destination
if has_alpha(destination) and (destination.size == source.size
or force):
invert_alpha = ImageOps.invert(get_alpha(destination))
if invert_alpha.size != source.size:
# if sizes are not the same be careful!
# check the results visually
if len(box) == 2:
w, h = source.size
box = (box[0], box[1], box[0] + w, box[1] + h)
invert_alpha = invert_alpha.crop(box)
else:
invert_alpha = None
# we don't want composite of the two alpha channels
source_without_alpha = remove_alpha(source)
# paste on top of the opaque destination pixels
destination.paste(source_without_alpha, box, source)
if invert_alpha != None:
# the alpha channel is ok now, so save it
destination_alpha = get_alpha(destination)
# paste on top of the transparant destination pixels
# the transparant pixels of the destination should
# be filled with the color information from the source
destination.paste(source_without_alpha, box, invert_alpha)
# restore the correct alpha channel
destination.putalpha(destination_alpha)
else:
destination.paste(source, box)
elif mask:
destination.paste(source, box, mask)
else:
destination.paste(source, box)
if force and has_alpha(source):
destination_alpha = get_alpha(destination)
source_alpha = get_alpha(source)
destination_alpha.paste(source_alpha, box)
destination.putalpha(destination_alpha)
def process(self, _edObject=None):
"""
This is the main method of the plugin, it does the job, not the EDNA name conversions which were done in the preprocess.
"""
EDPluginExec.process(self)
EDVerbose.DEBUG("EDPluginExecThumbnailv10.process")
# try:
# except Exception:
# edfImage = EDF(self.inputFilename)
# self.npaImage = edfImage.GetData(0)
# Read the image using FABIO
isRGB = False
pilOutputImage = None
if self.inputFilename is not None:
try:
fabioImage = openimage(self.inputFilename)
self.npaImage = fabioImage.data
except Exception:
pilInputImage = Image.open(self.inputFilename)
x, y = pilInputImage.size
ImageFile.MAXBLOCK = x * y
if pilInputImage.mode == "1":
self.npaImage = numpy.asarray(pilInputImage).astype(
"uint8")
isRGB = False
elif pilInputImage.mode == "F":
self.npaImage = numpy.asarray(pilInputImage)
isRGB = False
elif pilInputImage.mode == "L":
self.npaImage = numpy.asarray(pilInputImage)
isRGB = False
elif pilInputImage.mode == "P":
self.npaImage = numpy.asarray(pilInputImage.convert("RGB"))
isRGB = True
elif pilInputImage.mode == "RGB":
self.npaImage = numpy.asarray(pilInputImage)
isRGB = True
elif pilInputImage.mode == "CMJK":
self.npaImage = numpy.asarray(pilInputImage.convert("RGB"))
isRGB = True
dtype = self.npaImage.dtype
NPAImageFloat = None
# crop border
if len(self.cropBorders) > 0:
if len(self.cropBorders) == 1:
crop0 = self.cropBorders[0]
crop1 = self.cropBorders[0]
else:
crop0 = self.cropBorders[0]
crop1 = self.cropBorders[1]
if isRGB:
self.npaImage = self.npaImage[crop0:-crop0, crop1:crop1, :]
else:
self.npaImage = self.npaImage[crop0:-crop0, crop1:crop1]
# Set maxima and minima
if (self.minLevelUnit is not None) or (self.maxLevelUnit is not None):
sortedArray = self.npaImage.flatten()
sortedArray.sort()
if self.minLevel is not None:
self.normalize = True
if isRGB:
EDVerbose.warning(
"It is not allowed to set Min with RGB data")
else:
if self.minLevelUnit in ["%", "percent"]:
self.minLevel = sortedArray[int(
round(float(self.minLevel) * sortedArray.size /
100.0))]
if isinstance(self.npaImage[0, 0], int):
self.npaImage = numpy.maximum(
self.npaImage,
int(self.minLevel) * numpy.ones_like(self.npaImage))
else:
self.npaImage = numpy.maximum(
self.npaImage,
self.minLevel * numpy.ones_like(self.npaImage))
if self.maxLevel is not None:
self.normalize = True
if isRGB:
EDVerbose.warning(
"It is not allowed to set Max with RGB data")
else:
if self.maxLevelUnit in ["%", "percent"]:
self.maxLevel = sortedArray[int(
round(float(self.maxLevel) * sortedArray.size /
100.0))]
if isinstance(self.npaImage[0, 0], int):
self.npaImage = numpy.minimum(
self.npaImage,
int(self.maxLevel) * numpy.ones_like(self.npaImage))
else:
self.npaImage = numpy.minimum(
self.npaImage,
self.maxLevel * numpy.ones_like(self.npaImage))
# Scipy filters come here:
if len(self.gaussianBlur) > 0:
if len(self.gaussianBlur) == 1:
kernel = (self.gaussianBlur[0], self.gaussianBlur[0])
else:
kernel = (self.gaussianBlur[0], self.gaussianBlur[1])
if isRGB:
kernel = (kernel[0], kernel[1], 0)
self.npaImage = scipy.ndimage.gaussian_filter(
self.npaImage, kernel)
if len(self.dilatation) > 0:
if len(self.dilatation) == 1:
kernel = (self.dilatation[0], self.dilatation[0])
else:
kernel = (self.dilatation[0], self.dilatation[1])
if isRGB:
kernel = (kernel[0], kernel[1], 0)
self.npaImage = scipy.ndimage.morphology.grey_dilation(
self.npaImage, kernel)
#Normalization ; equalization
if (self.normalize is True) or (self.equalize is True):
if isRGB is True:
self.npaImage = numpy.asarray(
ImageOps.equalize(Image.fromarray(self.npaImage)))
else:
EDVerbose.DEBUG("EDPluginExecThumbnailv10: Normalization")
vmin = self.npaImage.min()
vmax = self.npaImage.max()
NPAImageFloat = (self.npaImage.astype(numpy.float32) -
float(vmin)) / (float(vmax) - float(vmin))
if (self.equalize == True):
nbr_bins = 64
NPAImageFloatFlat = NPAImageFloat.flatten()
imhist, bins = numpy.histogram(
NPAImageFloatFlat, nbr_bins,
normed=True) #get image histogram
cdf = imhist.cumsum() #cumulative distribution function
ncdf = cdf / cdf[
-1] #normalized cumulative distribution function
# print ncdf
NPAImageFloat2Flat = numpy.interp(NPAImageFloatFlat, bins,
[0] + ncdf.tolist())
NPAImageFloat = NPAImageFloat2Flat.reshape(
NPAImageFloat.shape)
EDVerbose.DEBUG("Equalize: min= %f, max= %f" %
(NPAImageFloat.min(), NPAImageFloat.max()))
#Gamma and logarithm scale
if ((self.log is True) or (self.gamma != 1)) and (
NPAImageFloat is None): # then we need the array in float
if dtype == numpy.uint8:
NPAImageFloat = self.npaImage.astype(numpy.float32) / 255.0
elif dtype == numpy.uint16:
NPAImageFloat = self.npaImage.astype(numpy.float32) / 65535.0
else:
NPAImageFloat = self.npaImage.astype(numpy.float32)
if self.log is True:
NPAImageFloat = numpy.log(1 - NPAImageFloat.min() + NPAImageFloat)
vmin = NPAImageFloat.min()
vmax = NPAImageFloat.max()
NPAImageFloat = (NPAImageFloat - vmin) / (vmax - vmin)
if self.gamma != 1:
if dtype not in [numpy.uint8, numpy.uint16]:
vmin = NPAImageFloat.min()
vmax = NPAImageFloat.max()
NPAImageFloat = (NPAImageFloat - vmin) / (vmax - vmin)
NPAImageInt = (255.0 * (NPAImageFloat**self.gamma)).astype("uint8")
else: #if (self.gamma == 1):
if NPAImageFloat is None:
if dtype == numpy.uint8:
NPAImageInt = self.npaImage
elif dtype == numpy.uint16:
NPAImageInt = (self.npaImage / 256).astype(numpy.uint8)
else: #for float or a signed integer
vmin = self.npaImage.min()
vmax = self.npaImage.max()
NPAImageInt = (
(self.npaImage.astype(numpy.float32) - vmin) /
(vmax - vmin) * 255.0).astype(numpy.uint8)
else:
vmin = NPAImageFloat.min()
vmax = NPAImageFloat.max()
EDVerbose.DEBUG(
"EDPluginExecThumbnailv10: NPAImageFloat => NPAImageInt min=%s max =%s"
% (vmin, vmax))
NPAImageInt = ((NPAImageFloat - vmin) * 255.0 /
(vmax - vmin)).astype(numpy.uint8)
#COnversion back to PIL mode
if isRGB is True:
pilOutputImage = Image.fromarray(NPAImageInt, 'RGB')
else:
pilOutputImage = Image.fromarray(NPAImageInt, 'L')
if (self.autocontrast is not None):
pilOutputImage = ImageOps.autocontrast(pilOutputImage,
self.autocontrast)
if (self.width is not None) or (self.height is not None):
if (self.width > 0) and (self.height > 0):
if self.keepRatio is True:
# PIL takes care of the ratio
pilOutputImage.thumbnail((self.width, self.height),
Image.ANTIALIAS)
else:
pilOutputImage = pilOutputImage.resize(
(self.width, self.height), Image.ANTIALIAS)
else:
if self.width is None:
pilOutputImage.thumbnail((self.height, self.height),
Image.ANTIALIAS)
elif self.height is None:
pilOutputImage.thumbnail((self.width, self.width),
Image.ANTIALIAS)
if self.invert == True:
pilOutputImage = ImageOps.invert(pilOutputImage)
if self.colorize == True:
pilOutputImage.putpalette(EDPluginExecThumbnailv10.getPalette())
pilOutputImage = pilOutputImage.convert("RGB")
self.synchronizeOn()
if self.format == "jpg":
self.width, self.height = pilOutputImage.size
if self.width * self.height > ImageFile.MAXBLOCK:
ImageFile.MAXBLOCK = self.width * self.height
try:
pilOutputImage.save(self.output,
"JPEG",
quality=85,
optimize=True)
except TypeError:
pilOutputImage.save(self.output)
else:
pilOutputImage.save(self.output)
self.synchronizeOff()
if allow_ML:
raise('The selected portrait photo does not contain a depth map.')
else:
print('The selected portrait photo does not contain a depth map.')
quit()
# If the selected photo does not contain a depth map, let's infer it using coreML
except Exception as e:
# Hardcoded resolution for the Pydnet model
chosen_pic_resized = chosen_pic.get_image(original = False).resize((640, 384))
with io.BytesIO() as bts:
chosen_pic_resized.save(bts, format = 'PNG')
chosen_pic_depth = CoreML(bts).to_png()
chosen_pic_depth_stream = io.BytesIO(chosen_pic_depth)
chosen_pic_depth_image = Image.open(chosen_pic_depth_stream)
chosen_pic_depth_image = chosen_pic_depth_image.resize((int(chosen_pic.get_ui_image().size[0]), int(chosen_pic.get_ui_image().size[1])), Image.BICUBIC)
chosen_pic_depth_image = ImageOps.invert(chosen_pic_depth_image)
# chosen_pic_depth_image.show()
arr = numpy.array(chosen_pic_depth_image).astype(int)
# This part takes the depth map and normalizes its values to the range of (0, 180). You can experiment with the value, 255 is the ceiling.
chosen_pic_depth_image_array = (120*(arr - numpy.min(arr))/numpy.ptp(arr)).astype(int)
chosen_pic_depth_image = Image.fromarray(numpy.uint8(chosen_pic_depth_image_array))
# chosen_pic_depth_image = chosen_pic_depth_image.convert('P', palette = Image.ADAPTIVE, colors = 2)
# chosen_pic_depth_image.show()
# Making the images smaller for faster processing.
chosen_pic_image.thumbnail((350, 350), Image.ANTIALIAS)
chosen_pic_depth_image.thumbnail((350, 350), Image.ANTIALIAS)
# When the colormap mode is enabled, we use the colormapped depth data as a texture.
chosen_pic_photo_image_buffer = io.BytesIO()
def process(self, _edObject=None):
"""
This is the main method of the plugin, it does the job, not the EDNA name conversions which were done in the preprocess.
"""
EDPluginExec.process(self)
EDVerbose.DEBUG("EDPluginPyarchThumbnailv10.process")
if self.inputFilename:
# Read the image using FABIO
fabioImage = openimage(self.inputFilename)
# Convert an FabioImage to a PIL image
npaImageRaw = fabioImage.data
iMinLevel = 2
iMaxLevel = 1000
npaImageRaw = numpy.minimum(
npaImageRaw, iMaxLevel * numpy.ones_like(npaImageRaw))
npaImageRaw = numpy.maximum(
npaImageRaw, iMinLevel * numpy.ones_like(npaImageRaw))
npaImage = scipy.ndimage.morphology.grey_dilation(npaImageRaw,
size=(5, 5))
npaImageThumb = scipy.ndimage.morphology.grey_dilation(npaImageRaw,
size=(10,
10))
dtype = str(npaImage.dtype)
if dtype == "uint8":
NPAImageFloat = npaImage.astype("float") / 255.0
NPAImageFloatThumb = npaImageThumb.astype("float") / 255.0
elif dtype == "uint16":
NPAImageFloat = npaImage.astype("float") / 65535.0
NPAImageFloatThumb = npaImageThumb.astype("float") / 65535.0
else: #for float or whatever
vmin = npaImage.min()
vmax = npaImage.max()
NPAImageFloat = (npaImage.astype(float) - vmin) / (vmax - vmin)
vminThumb = npaImageThumb.min()
vmaxThumb = npaImageThumb.max()
NPAImageFloatThumb = (npaImageThumb.astype(float) -
vminThumb) / (vmax - vminThumb)
NPAImageInt = (255.0 * (NPAImageFloat**0.3)).astype("uint8")
NPAImageIntThumb = (255.0 *
(NPAImageFloatThumb**0.3)).astype("uint8")
pilImage = Image.fromarray(NPAImageInt, 'L')
pilImageThumb = Image.fromarray(NPAImageIntThumb, 'L')
# For ISPyB we use for the moment only 1024x1024 and 256x256
pilImage.thumbnail((1024, 1024), Image.ANTIALIAS)
pilImageThumb.thumbnail((256, 256), Image.ANTIALIAS)
pilImage = ImageOps.invert(pilImage)
pilImageThumb = ImageOps.invert(pilImageThumb)
self.synchronizeOn()
if 1024 * 1024 > ImageFile.MAXBLOCK:
ImageFile.MAXBLOCK = 1024 * 1024
pilImage.save(self.strOutputPath,
"JPEG",
quality=50,
optimize=True)
pilImageThumb.save(self.strOutputPathThumb,
"JPEG",
quality=85,
optimize=True)
self.synchronizeOff()
def imagetogcode(image, f):
img = ImageOps.invert(image)
width, height = img.size
f.write("; Image pixel size: " + str(width) + "x" + str(height) + "\n")
f.write("M649 S11 B2 D0 R0.0846 F6000\nG28\nG0 X70 Y45 F6000\n")
pixels = list(img.getdata())
pixels = [pixels[i * width:(i + 1) * width] for i in xrange(height)]
forward = True
# def get_chunks(arr, chunk_size = 51):
def get_chunks(arr, chunk_size=51):
chunks = [
arr[start:start + chunk_size]
for start in range(0, len(arr), chunk_size)
]
return chunks
# return the last pixel that holds data.
def last_in_list(arr):
end = 0
for i in range(len(arr)):
if (arr[i] > 0):
end = i
return end
# return the last pixel that holds data.
def first_in_list(arr):
end = 0
for i in range(len(arr)):
if (arr[i] == 0):
end = i
if (arr[i] > 0):
break
return end
first = True
row = pixels[::-1]
previousRight = 99999999999
previousLeft = 0
firstRow = True
for index, rowData in enumerate(row):
print "Line " + str(index + 1) + " ="
#print rowData
splitRight = 0
splitLeft = 0
if (index + 1 < len(row)):
# Determine where to split the lines.
##################################################
#If the left most pixel of the next row is earlier than the current row, then extend.
if (first_in_list(row[index + 1]) > first_in_list(rowData)):
splitLeft = first_in_list(rowData)
else:
splitLeft = first_in_list(row[index + 1])
#If the end pixel of the next line is later than the current line, extend.
if (last_in_list(row[index + 1]) > last_in_list(rowData)):
splitRight = last_in_list(row[index + 1])
else:
splitRight = last_in_list(rowData)
print "Prior Left cut = " + str(
splitLeft) + " Right Cut == " + str(splitRight)
else:
splitLeft = first_in_list(rowData)
splitRight = last_in_list(rowData)
#Positive direction
if forward:
print "Forward!"
#Split the right side.
###########################################
#Don't split more than the start of the last row as we print in reverse for alternate lines
splitLeft = previousLeft
previousRight = splitRight
#Negative direction
else:
print "Backward!"
#Split the left side.
###########################################
#Don't split more than the end of the last row as we print in reverse for alternate lines
splitRight = previousRight
previousLeft = splitLeft
#Exception to the rule : Don't split the left of the first row.
if (firstRow):
splitLeft = (previousLeft)
firstRow = False
print "After : Left cut = " + str(splitLeft) + " Right Cut == " + str(
splitRight)
row2 = rowData[(splitLeft + 1):(splitRight + 1)]
print row2
#if(index == 5):
# raise Exception('End')
if not forward:
result_row = row2[::-1]
else:
result_row = row2
for chunk in get_chunks(result_row, 51):
if first:
if forward:
f.write("\nG7 $1 ")
# f.write("G7 $1\nG7 ")
else:
f.write("\nG7 $0 ")
# f.write("G7 $0\nG7 ")
first = not first
else:
f.write("G7 ")
b64 = base64.b64encode("".join(chr(y) for y in chunk))
f.write("L" + str(len(b64)) + " ")
f.write("D" + b64 + "\n")
forward = not forward
first = not first
f.write("M5 \n")
def decorated(image, *a, **kw):
image = ImageOps.invert(image.convert("L"))
applied = f(image, *a, **kw)
return ImageOps.invert(applied)
return result
if __name__ == "__main__":
results = []
for file in input_files:
# path = file
im = Image.open(file)
im = ImageOps.autocontrast(im)
im = ImageOps.autocontrast(im)
im = ImageOps.autocontrast(im)
im = ImageOps.autocontrast(im)
im = brighten(im, 2.1)
im = ImageOps.grayscale(im)
im = ImageOps.invert(im)
im = im.point(lambda i: 250 if i > 1 else i)
im = ImageOps.invert(im)
im = clear_noise(im, 254, 1, 255)
# im = im.convert("L")
# im = polarize(im, 250)
# im = clear_noise(im, 4, 1)
# im = contrast(im, 2.0)
path = tempfile.mktemp(dir="/tmp/mem/ems/") + ".png"
im.save(path, "png")
result = run_tesseract(path)
result = post_process(result)
results.append(result)
# further zoom on object to match scaling of archive images
finderScale = idcScale / finderRatio
w = img.size[0] * finderScale
h = img.size[1] * finderScale
scale = (int(w), int(h))
img.resize(scale)
# rotate the image according to the data, keep transparent background
rot = img.rotate(-float(orientat), expand=1)
img = Image.new("RGBA", rot.size, (255, 255, 255, 0))
img.paste(rot, (0, 0), rot)
# invert the full value scale and enable it as the alpha band
alpha = img.convert("L")
alpha = ImageOps.invert(alpha)
img.putalpha(alpha)
# turn the image to a yummy turquoise color
img.paste((0, 133, 134), (0, 0), img)
# save output file if non-existent
if infile != outfile:
try:
img.save(outfile)
except IOError:
print "Cannot convert: " + infile
iter += -1
# output success
print "You have successfully converted " + str(iter) + " files."
#text = r'$\sqrt{2}$'
#text = r'$\sqrt[3]{x}$'
box = parser.parse(text, fonts, 12, 72)
width, height, descent = renderer.render(box)
#svg.write()
scale = 4.
svg.set('width', scale*width)
svg.set('height', scale*height)
svg.set('transform', 'translate(0,%g) scale(%g)' % (height*scale - descent*scale,scale))
show(svg, svg.width, svg.height)
'''
import Image, ImageOps
parser = Parser()
renderer = ImageBackend()
fonts = BakomaFonts()
#text = r'$\alpha > \beta$'
#text = r'$\alpha_i > \beta_i$'
text = r'$\sum_{i=0}^\infty x_i$'
box = parser.parse(text, fonts, 64, 72)
buffer = renderer.render(box)
img = Image.fromstring('L', (buffer.width, buffer.height),
buffer.tobytes())
img = ImageOps.invert(img)
img.save('test.png')
for digit in range(0, 10):
# Draw the digit on a large canvas so PIL doesn't crop it.
scratch_canvas_image = Image.new("RGB", LARGE_SCRATCH_CANVAS_DIMENSIONS)
draw = ImageDraw.Draw(scratch_canvas_image)
draw.text((0,0), str(digit), font=font)
# Discard all the padding
cropped_digit_image = scratch_canvas_image.crop(scratch_canvas_image.getbbox())
# Center the digit within the final image tile and save it
digit_width, digit_height = cropped_digit_image.size
tile_image = Image.new("RGB", FINAL_TILE_CANVAS_DIMENSIONS)
tile_image.paste(cropped_digit_image, ((TILE_WIDTH_PIXELS-digit_width)/2, (TILE_HEIGHT_PIXELS-digit_height)/2))
tile_image = ImageOps.invert(tile_image)
tile_image.save(OUTPUT_IMAGE_FILEPATH_TEMPLATE % digit)
meta_data_entries.append(META_DATA_TEMPLATE % (digit, digit))
# Display the meta data which needs to be included in `resource_map.json`.
print ",\n".join(meta_data_entries)
def operation(self, img):
return ImageOps.invert(img)
def getBoxImage(self, image):
invert_im = ImageOps.invert(image)
return invert_im.getbbox()
def cropBound(id):
print 'cropBound', id
maxBoundary = [1000, 1000, 0, 0]
for k in range(0, 8): #attack
im = Image.open('ss' + str(id) + 'a' + str(k) + '.png')
#需要使用两种技术分别 处理 图片的左右和上下空白
#直接getbbox 做灰度图 之后 getbbox
#nim = im.convert('L')
#nim = ImageOps.invert(nim)
#nim = nim.crop([1, 0]+list(nim.size))
box = list(im.getbbox())
size = im.size
if box[2] == size[0] and box[3] == size[1]:
print "notBox", id
nim = im.convert('L')
nim = ImageOps.invert(nim)
nim = nim.crop([1, 0] + list(nim.size))
box = list(nim.getbbox())
print box, size
midX = im.size[0] / 2
difx = max(abs(box[0] - midX), abs(box[2] - midX))
box[0] = midX - difx
box[2] = midX + difx
if box[0] < maxBoundary[0]:
maxBoundary[0] = box[0]
if box[1] < maxBoundary[1]:
maxBoundary[1] = box[1]
if box[2] > maxBoundary[2]:
maxBoundary[2] = box[2]
if box[3] > maxBoundary[3]:
maxBoundary[3] = box[3]
print id, 'a', maxBoundary
res['a%d' % (id)] = maxBoundary
for k in range(0, 8):
im = Image.open('ss' + str(id) + 'a' + str(k) + '.png')
nim = im.crop(maxBoundary)
nim.save('ss' + str(id) + 'a' + str(k) + '.png')
maxBoundary = [1000, 1000, 0, 0]
for k in range(0, 7): #move
im = Image.open('ss' + str(id) + 'm' + str(k) + '.png')
#nim = im.convert('L')
#nim = ImageOps.invert(nim)
#nim = nim.crop([1, 0]+list(nim.size))
box = list(im.getbbox())
size = im.size
if box[2] == size[0] and box[3] == size[1]:
print "notBox", id
nim = im.convert('L')
nim = ImageOps.invert(nim)
nim = nim.crop([1, 0] + list(nim.size))
box = list(nim.getbbox())
print box, size
midX = im.size[0] / 2
difx = max(abs(box[0] - midX), abs(box[2] - midX))
box[0] = midX - difx
box[2] = midX + difx
if box[0] < maxBoundary[0]:
maxBoundary[0] = box[0]
if box[1] < maxBoundary[1]:
maxBoundary[1] = box[1]
if box[2] > maxBoundary[2]:
maxBoundary[2] = box[2]
if box[3] > maxBoundary[3]:
maxBoundary[3] = box[3]
print id, 'm', maxBoundary
res['m%d' % (id)] = maxBoundary
for k in range(0, 7):
im = Image.open('ss' + str(id) + 'm' + str(k) + '.png')
nim = im.crop(maxBoundary)
nim.save('ss' + str(id) + 'm' + str(k) + '.png')
