def extract_label(labelfile):
accession = image_to_string(iopen(labelfile))
accession = " ".join(accession.split()) # normalize spaces
accession = "".join(x for x in accession if x in string.printable)
if not accession:
accession = "none"
return accession
def convert_background(pngfile, new_background=(37, 90, 223)):
'''Replace the background color with the specified background color, default is blue
'''
_name, _ext = op.splitext(op.basename(pngfile))
_name += '_bgxform'
newfile = op.join(op.dirname(pngfile), _name + _ext)
if not new_background:
new_background = (37, 90, 223)
meanr = 115
meang = 150
meanb = 135
img = iopen(pngfile)
pixels = list(img.getdata())
h, w = img.size
# Get Standard Deviation of RGB
rgbArray = []
for x in range(255):
rgbArray.append(x)
stdRGB = np.std(rgbArray)
# Change Background Color
for i in range(len(pixels)):
r, g, b = pixels[i]
if (r >= (meanr - stdRGB) and r <= (meanr + stdRGB)):
if (g >= (meang - stdRGB) and g <= (meang + stdRGB)):
if (b >= (meanb - stdRGB) and b <= (meanb + stdRGB)):
pixels[i] = new_background
img.putdata(pixels)
img.save(newfile)
return newfile
def extract_label(labelfile):
accession = image_to_string(iopen(labelfile))
accession = " ".join(accession.split()) # normalize spaces
accession = "".join(x for x in accession if x in string.printable)
if not accession:
accession = "none"
return accession
def load_texture(self, filename):
"""
Loads the texture from a file
"""
texture_file = iopen(filename) # Opens the image file
texture_size = texture_file.size
texture_data = texture_file.tostring()
return self.create_texture(texture_data, texture_size)
def getImageSize(img):
""" determine the dimensions for the given image file """
if hasPIL:
try:
return iopen(img).size
except IOError:
return 0, 0
else:
data = img.read(32)
return getImageInfo(data)[1:]
def getImageSize(img):
""" determine the dimensions for the given image file """
if hasPIL:
try:
return iopen(img).size
except IOError:
return 0, 0
else:
data = img.read(32)
return getImageInfo(data)[1:]
def load_to_mem(self, data_path):
print('Loading testing data into memory')
data = {}
idx = 0
for alpha_path in listdir(data_path):
for char_path in listdir(join(data_path, alpha_path)):
data[idx] = []
for sample_path in listdir(
join(data_path, alpha_path, char_path)):
filepath = join(data_path, alpha_path, char_path,
sample_path)
data[idx].append(iopen(filepath).convert('L'))
idx += 1
print('Test data in memory')
return data, idx
def load_to_mem(self, data_path):
print('Loading training data into memory')
data = {}
degrees = [0, 90, 180, 270]
idx = 0
for degree in degrees:
for alpha_path in listdir(data_path):
for char_path in listdir(join(data_path, alpha_path)):
data[idx] = []
for sample_path in listdir(
join(data_path, alpha_path, char_path)):
filepath = join(data_path, alpha_path, char_path,
sample_path)
data[idx].append(
iopen(filepath).rotate(degree).convert('L'))
idx += 1
print('Dataset in memory')
return data, idx
def convert_background(pngfile, new_background):
"""Replace the background color with the specified background color, default is blue"""
if new_background:
_name, _ext = op.splitext(op.basename(pngfile))
_name += "_bgxform"
newfile = op.join(op.dirname(pngfile), _name + _ext)
img = iopen(pngfile)
pixels = list(img.getdata())
h, w = img.size
# Get Standard Deviation of RGB
rgbArray = []
for x in range(255):
rgbArray.append(x)
stdRGB = np.std(rgbArray) * 0.8
# Get average color
obcolor = [None, None, None]
pixel_values = []
for t in range(3):
pixel_color = img.getdata(band=t)
for pixel in pixel_color:
if pixel > (stdRGB):
pixel_values.append(pixel)
obcolor[t] = sum(pixel_values) / len(pixel_values)
# Get background color using average color and standard deviation
for t in range(3):
pixel_color = img.getdata(band=t)
seed_pixel_values = []
for i in pixel_color:
if (i > (obcolor[t] - stdRGB)) and (i < (obcolor[t] + stdRGB)):
seed_pixel_values.append(i)
obcolor[t] = sum(seed_pixel_values) / len(seed_pixel_values)
# Selection of colors based on option parser
nbcolor = [None, None, None]
if new_background == "INVERSE":
nbcolor = [None, None, None]
for t in range(3):
nbcolor[t] = 255 - obcolor[t]
elif new_background == "red":
nbcolor = [255, 0, 0]
elif new_background == "green":
nbcolor = [0, 255, 0]
elif new_background == "blue":
nbcolor = [0, 0, 255]
elif new_background == "yellow":
nbcolor = [255, 255, 0]
elif new_background == "purple":
nbcolor = [255, 0, 255]
elif new_background == "orange":
nbcolor = [255, 165, 0]
# Change Background Color
obcolor = tuple(obcolor)
nbcolor = tuple(nbcolor)
for i in range(len(pixels)):
r, g, b = pixels[i]
if r >= (obcolor[0] - stdRGB) and r <= (obcolor[0] + stdRGB):
if g >= (obcolor[1] - stdRGB) and g <= (obcolor[1] + stdRGB):
if b >= (obcolor[2] - stdRGB) and b <= (obcolor[2] +
stdRGB):
pixels[i] = nbcolor
img.putdata(pixels)
img.save(newfile, "PNG")
return newfile
return pngfile
def test_paletted_image_transparent(self):
img = new("P", (256, 256), 0)
img.save("test1.png", "PNG", transparency="\x00")
img = iopen("test1.png", "r")
assert img_has_transparency(img)
from numpy import zeros, ones, sin, cos, uint8, pi
from sys import argv
from tqdm import tqdm
from png import Writer
try: from PIL.Image import open as iopen
except ImportError: from Image import open as iopen
class DoublePendulum():
def __init__(self, thetas): self.t, self.td, self.l, self.m = thetas, zeros(thetas.shape), ones(thetas.shape), ones(thetas.shape)
def step(self):
self.td[:, 0] += (-10 * (2 * self.m[:, 0] + self.m[:, 1]) * sin(self.t[:, 0]) - self.m[:, 1] * 10 * sin(self.t[:, 0] - 2 * self.t[:, 1]) - 2 * sin(self.t[:, 0] - self.t[:, 1]) * self.m[:, 1] * (self.td[:, 1] ** 2 * self.l[:, 1] + self.td[:, 0] ** 2 * self.l[:, 0] * cos(self.t[:, 0] - self.t[:, 1]))) / (2000 * self.l[:, 0] * (2 * self.m[:, 0] + self.m[:, 1] * (1 - cos(2 * (self.t[:, 0] - self.t[:, 1])))))
self.td[:, 1] += (2 * sin(self.t[:, 0] - self.t[:, 1]) * (self.td[:, 0] ** 2 * self.l[:, 0] * (self.m[:, 0] + self.m[:, 1]) + 10 * (self.m[:, 0] + self.m[:, 1]) * cos(self.t[:, 0]) + self.td[:, 1] ** 2 * self.l[:, 1] * self.m[:, 1] * cos(self.t[:, 0] - self.t[:, 1]))) / (2000 * self.l[:, 1] * (2 * self.m[:, 0] + self.m[:, 1] * (1 - cos(2 * (self.t[:, 0] - self.t[:, 1])))))
self.t += self.td / 2000
color = lambda x, y: (127 * cos(x / 4 - y / 4), 127 * (cos(x / 4 - y / 4) - sin(x / 4 + y / 4)), 127 * (sin(x / 4 - y / 4) + cos(x / 4 + y / 4)))
thetas = ones((893025, 2))
for i in range(893025): thetas[i, 0], thetas[i, 1] = pi * (2 * (i % 945) / 945 - 1), pi * (2 * (i // 945) / 945 - 1)
p, frames, FRAMES = DoublePendulum(thetas), [], int(argv[1])
for frame in tqdm(range(FRAMES)):
fractal, file, writer = uint8([[a for i in range(945) for a in color(p.t[j * 945 + i, 0], p.t[j * 945 + i, 1])] for j in range(945)]), open(f'frames/frame{frame}.png', 'wb+'), Writer(945, 945, greyscale = False)
writer.write(file, fractal)
frames += [iopen(file)]
for _ in range(33): p.step()
frames[0].save('output.gif', format = 'GIF', append_images = frames[1:], save_all = True, duration = FRAMES / 60)
