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imgpro.py
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imgpro.py
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from PIL import Image
import os
from skimage.color.adapt_rgb import adapt_rgb, each_channel, hsv_value
from skimage import filters
from skimage.color import rgb2gray
from skimage import feature
from skimage import io
import numpy as np
import matplotlib.pyplot as plt
from skimage.exposure import rescale_intensity
from scipy import ndimage as ndi
import math
from skimage.filters import gaussian
from skimage.segmentation import active_contour
from scipy import misc
from skimage.morphology import skeletonize
path = "/Users/yircheng/Documents/Yi/ad_proj/data/img/"
out_path = "/Users/yircheng/Documents/Yi/ad_proj/out/"
def as_gray(image_filter, image, *args, **kwargs):
gray_image = rgb2gray(image)
return image_filter(gray_image, *args, **kwargs)
@adapt_rgb(as_gray)
def original_gray(image):
return image
@adapt_rgb(as_gray)
def skeleton_gray(image):
return skeletonize(image)
@adapt_rgb(as_gray)
def canny_gray(image,p):
return feature.canny(image,sigma=p)
@adapt_rgb(as_gray)
def canny_gray2(image):
return feature.canny(image,sigma=3)
@adapt_rgb(as_gray)
def sobel_gray(image):
return filters.sobel(image)
@adapt_rgb(as_gray)
def roberts_gray(image):
return filters.roberts(image)
@adapt_rgb(each_channel)
def sobel_each(image):
return filters.sobel(image)
@adapt_rgb(hsv_value)
def sobel_hsv(image):
return filters.sobel(image)
@adapt_rgb(each_channel)
def roberts_each(image):
return filters.roberts(image)
@adapt_rgb(hsv_value)
def roberts_hsv(image):
return filters.roberts(image)
def toprint(image,name):
#fig = plt.figure(figsize=(14, 7))
#ax = fig.add_subplot(111, adjustable='box-forced',axisbg='r')
fig = plt.figure()
ax = fig.add_subplot(111)
ax.imshow(image, cmap=plt.cm.gray)
ax.axis('off')
# ax.set_title('original', fontsize=20)
fig.tight_layout()
fig.savefig(out_path + name)
plt.show()
def reduce():
cutfile = open('reduced_data', 'w')
#print(im.getpixel((1,1)))
#print len(temp[1]), len(temp)
T_size = (80,20)
L_size = (35,65)
R_size = (35,65)
testbox = (1, 1, 2, 2)
T_box = (1, 1, 1400, 350)
L_box = (1, 350, 350, 1000)
R_box = (1050, 350, 1400, 1000)
for file in os.listdir(path):
im = Image.open(path + file)
cutfile.write(file.split(".")[0])
# print(im.format, im.size, im.mode)
######TOP REGION######
region = im.crop(T_box)
region.thumbnail(T_size)
# region.save(out_path + file.split(".")[0] + "_t.png")
region.show()
imarray = list(region.getdata())
for item in imarray:
cutfile.write(" " + str(item[0]) + " " + str(item[1]) + " " + str(item[2]))
######LEFT REGION######
region = im.crop(L_box)
region.thumbnail(L_size)
# region.save(out_path + file.split(".")[0] + "_l.png")
# region.show()
imarray = list(region.getdata())
for items in imarray:
cutfile.write(" " + str(item[0]) + " " + str(item[1]) + " " + str(item[2]))
######RIGHT REGION######
region = im.crop(R_box)
region.thumbnail(R_size)
# region.save(out_path + file.split(".")[0] + "_r.png")
# region.show()
imarray = list(region.getdata())
for items in imarray:
cutfile.write(" " + str(item[0]) + " " + str(item[1]) + " " + str(item[2]))
cutfile.write('\n')
cutfile.close()
cutfile = open('reduced_data', 'r')
for line in cutfile:
print len(line.split(" "))
cutfile.close()
def edge():
#plt.switch_backend('MacOSX')
image = io.imread(path + "bibme0.png")
print type(image)
print image.shape
# edge_roberts = roberts(image)
# edge_sobel = sobel(image)
fig = plt.figure(figsize=(14, 7))
ax_each = fig.add_subplot(121, adjustable='box-forced')
ax_hsv = fig.add_subplot(122, sharex=ax_each, sharey=ax_each,
adjustable='box-forced')
# We use 1 - sobel_each(image)
# but this will not work if image is not normalized
ax_each.imshow(rescale_intensity(1 - sobel_gray(image)), cmap=plt.cm.gray)
#ax_each.imshow(sobel_each(image))
ax_each.set_xticks([]), ax_each.set_yticks([])
ax_each.set_title("Sobel filter computed\n on individual RGB channels")
# We use 1 - sobel_hsv(image) but this will not work if image is not normalized
ax_hsv.imshow(rescale_intensity(1 - sobel_gray(image)), cmap=plt.cm.gray)
ax_hsv.set_xticks([]), ax_hsv.set_yticks([])
ax_hsv.set_title("Sobel filter computed\n on (V)alue converted image (HSV)")
fig.savefig(out_path + 'sobel_gray.png')
plt.show()
def edge_canny():
image = io.imread(path + "bibme0.png")
edges1 = rescale_intensity(1 - canny_gray(image))
edges2 = rescale_intensity(1 - canny_gray2(image))
fig, (ax1, ax2) = plt.subplots(nrows=1, ncols=2, figsize=(14, 7),
sharex=True, sharey=True)
ax1.imshow(edges1, cmap=plt.cm.gray)
ax1.axis('off')
ax1.set_title('Canny filter, $\sigma=1$', fontsize=20)
ax2.imshow(edges2, cmap=plt.cm.gray)
ax2.axis('off')
ax2.set_title('Canny filter, $\sigma=3$', fontsize=20)
fig.tight_layout()
fig.savefig(out_path + 'canny_gray.png')
plt.show()
def skeleton():
from skimage.morphology import skeletonize
image = io.imread(path + "bibme0.png")
gray_image = rgb2gray(image)
skeleton = skeletonize(gray_image)
toprint(skeleton,"bibme0_skeleton.png")
def rotate90():
import matplotlib.pyplot as plt
from scipy.ndimage.interpolation import rotate
import scipy.misc
image = io.imread(out_path + 'bibme0_contours.png')
rotated_image = rotate(image, -90, reshape=True)
toprint(rotated_image,"bibme0_contours.png")
def contour():
from skimage.filters import gaussian
from skimage.segmentation import active_contour
import scipy
from skimage import measure
from skimage import img_as_float
image = io.imread(path + "bibme0.png")
image = rgb2gray(image)
#image = img_as_float(image)
#print image
##### OPTION 1
contours = measure.find_contours(image,0.9)
#print size(contours)
#toprint(contours,'bibme0_contours.png')
fig, ax = plt.subplots()
#ax.imshow(contours, interpolation='nearest', cmap=plt.cm.gray)
for n, contour in enumerate(contours):
ax.plot(contour[:,0], contour[:,1], linewidth=0.5)
#print len(contours)
ax.axis('image')
ax.set_xticks([])
ax.set_yticks([])
fig.savefig(out_path + 'bibme0_contours.png')
#plt.show()
rotate90()
##### OPTION 2
#s = np.linspace(0, 2*np.pi, 400)
#x = 220 + 100*np.cos(s)
#y = 100 + 100*np.sin(s)
#init = np.array([x, y]).T
#snake = active_contour(gaussian(image, 3),init, alpha=0.015, beta=10, gamma=0.001)
#fig = plt.figure(figsize=(7, 7))
#ax = fig.add_subplot(111)
#plt.gray()
#ax.imshow(image)
#ax.plot(init[:, 0], init[:, 1], '--r', lw=3)
#ax.plot(snake[:, 0], snake[:, 1], '-b', lw=3)
#ax.set_xticks([]), ax.set_yticks([])
#ax.axis([0, image.shape[1], image.shape[0], 0])
#fig.savefig(out_path + 'bibme0_contour.png')
#plt.show()
def togray():
im = Image.open(path + 'bibme0.png')
gray_im = rgb2gray(np.array(im))
toprint(gray_im,"gray_testim.png")
def test():
im = Image.open(path + 'bibme0.png')
misc.imsave('sample_original.png',im) # uses the Image module (PIL)
# misc.imsave('sample_skeleton.png',1-skeleton_gray(np.array(im))) # uses the Image module (PIL)
# import matplotlib.pyplot as plt
# plt.imshow(im)
# plt.show()
if __name__=="__main__":
# edge()
# edge_canny()
# reduce()
# skeleton()
# contour()
# togray()
test()