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integral.py
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integral.py
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import cv2
import numpy as np
from PIL import Image
from skimage.transform.integral import integral_image, integrate
from random import randint
def is_white_patch(cur_patch,white_percentage):
''' Basic is_white check: checks if the extracted patch is white
and returns True if so
input:
cur_patch, patch to check
white_percentage, white portion threshold
output:
True if percentage of white> white portion threshold
False otherwise
'''
#good buttt slowww
# half black and half white patches are still kept. not a good thing.
#print 'into is_white'
is_white = True
total_white = float(cur_patch.shape[0] *cur_patch.shape[1] * cur_patch.shape[2] * 255)
if (cur_patch.sum()/total_white)>white_percentage:
return is_white
else:
return not is_white
def patch_sampling_using_integral(slide,slide_level,mask,patch_size,patch_num):
"""
patch sampling on whole slide image
input:
slide = OpenSlide Object
slide_level = level of mask
mask = mask image ( 0-1 int type nd-array)
patch_size = size of patch scala integer n
patch_num = the number of output patches
output:
list of patches(RGB Image), list of patch point (starting from left top)
"""
patch_list = [] # patches
patch_point = [] # patch locations
# taking the nonzero points in the mask
x_l,y_l = mask.nonzero()
#slide_level=7
if len(x_l) > patch_size/slide.level_downsamples[slide_level]*2:
level_patch_size = int(patch_size/slide.level_downsamples[slide_level])
print 'DEBUGGG: ', slide_level
# computing the actual level of resolution
# applying the nonzero mask as a dot product
x_ws = (np.round(x_l*slide.level_downsamples[slide_level])).astype(int)
y_ws = (np.round(y_l*slide.level_downsamples[slide_level])).astype(int)
cnt = 0 # patch counter
nt_cnt = 1 # not taken counter
white_threshold = .3
#white_threshold = 1.0
while(cnt < patch_num) :
# sampling from random distribution
p_idx = randint(0,len(x_l)-1)
# picking the random point in the mask
level_point_x,level_point_y = x_l[p_idx], y_l[p_idx]
if (level_point_y < 50) or (level_point_x < 250): ##new add to check
continue
# check the boundary to make patch
check_bound = np.resize(np.array([level_point_x+level_patch_size,level_point_y+level_patch_size]),(2,))
if check_bound[0] > mask.shape[0] or check_bound[1] > mask.shape[1]:
continue
# make patch from mask image
level_patch_mask = mask[int(level_point_x):int(level_point_x+level_patch_size),int(level_point_y):int(level_point_y+level_patch_size)]
# apply integral
ii_map = integral_image(level_patch_mask)
ii_sum = integrate(ii_map,(0,0),(level_patch_size-1,level_patch_size-1))
area_percent = float(ii_sum)/(level_patch_size**2)
# checking if the total area of the patch covers at least 80% of
# the annotation region
if area_percent<0.6:
continue
if cnt > patch_num*10+1000:
print "There is no more patches to extract in this slide"
print "mask region is too small"
print "final number of patches : ",len(patch_list)
break
patch=slide.read_region((y_ws[p_idx],x_ws[p_idx]),0,(patch_size,patch_size))
patch = np.array(patch)
#print '[integral] np.sum(patch): ', np.sum(patch)
if np.sum(patch)==0:
print('[integral] AaAaAH its zeroo!!')
continue
white_mask = patch[:,:,0:3] > 200
if float(np.sum(white_mask))/(patch_size**2*3) <= white_threshold :
#if True:
if np.sum(patch)>0:
# adding the patch to the patches list
patch_list.append(cv2.cvtColor(patch,cv2.COLOR_RGBA2BGR))
# adding the patch location to the list
patch_point.append((x_l[p_idx],y_l[p_idx]))
cnt += 1 # increasing patch counter
else:
print 'This is a black patch!'
else:
nt_cnt += 1
#print 'white_mask sum: ', np.sum(white_mask)
#print 'white ratio: ', float(np.sum(white_mask))/(patch_size**2*3)
#print 'Rejected location: {0},{1}'.format(x_l[p_idx],y_l[p_idx])
if nt_cnt %1000 == 0:
if white_threshold < .7:
white_threshold += .05
nt_cnt = 1
print 'Increasing white_threshold of 0.05: ', white_threshold
else:
print 'No more patches to extract that have more than 30 percent of not white content'
break
def_pl=[]
def_pp=[]
for i in range(len(patch_list)):
if (np.sum(patch_list[i])>0) and (np.mean(patch_list[i])>90):
def_pl.append(patch_list[i])
def_pp.append(patch_point[i])
return def_pl, def_pp
def tumor_patch_sampling_using_centerwin(slide,slide_level,mask,patch_size,patch_num):
"""
tumor patch sampling using center window
plz input the only tumor mask
it will malfunctioned if you input normal mask or tissue mask
input parameters are same as patch_sampling_using_integral
"""
patch_list = []
patch_point = []
window_size = int(32/ slide.level_downsamples[slide_level])
x_l,y_l = mask.nonzero()
if len(x_l) > patch_size*2:
level_patch_size = int(patch_size/slide.level_downsamples[slide_level])
x_ws = (np.round(x_l*slide.level_downsamples[slide_level])).astype(int)
y_ws = (np.round(y_l*slide.level_downsamples[slide_level])).astype(int)
cnt=0
while(len(patch_list) < patch_num) :
# loop cnt
cnt+=1
#random Pick point in mask
p_idx = randint(0,len(x_l)-1)
#Get the point in mask
level_point_x,level_point_y = x_l[p_idx], y_l[p_idx]
#Check boundary to make patch
check_bound = np.resize(np.array([level_point_x+level_patch_size,level_point_y+level_patch_size]),(2,))
if check_bound[0] > mask.shape[0] or check_bound[1] > mask.shape[1]:
continue
#make patch from mask image
level_patch_mask = mask[int(level_point_x):int(level_point_x+level_patch_size),int(level_point_y):int(level_point_y+level_patch_size)]
'''Biggest difference is here'''
#apply center window (32x32)
cntr_x= (level_patch_size/2)-1
cntr_y= (level_patch_size/2)-1
win_x = cntr_x-window_size/2
win_y = cntr_y-window_size/2
t_window = level_patch_mask[win_x:(win_x+window_size),win_y:(win_y+window_size)]
#print level_patch_mask.shape
#print win_x
#print win_y
#apply integral to window
ii_map = integral_image(t_window)
#print t_window.shape
ii_sum = integrate(ii_map,(0,0),(window_size-1,window_size-1))
area_percent = float(ii_sum)/(window_size**2)
# print "integral_area: ",area_percent
# print "loop count: ",cnt
if area_percent <1.0:
continue
if cnt > patch_num*10+1000:
print "There is no moare patches to extract in this slide"
print "mask region is too small"
print "final number of patches : ",len(patch_list)
break
#patch,point is appended the list
#print "region percent: ",area_percent
patch_point.append((x_l[p_idx],y_l[p_idx]))
patch=slide.read_region((y_ws[p_idx],x_ws[p_idx]),0,(patch_size,patch_size))
patch =np.array(patch)
patch_list.append(cv2.cvtColor(patch,cv2.COLOR_RGBA2BGR))
return patch_list, patch_point