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thorax.py
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from copy import copy
import numpy as np
import matplotlib.pyplot as plt
from skimage.filters import gaussian
from skimage.segmentation import active_contour
import cv2
from glob import glob
import os
import threading
GAP = 50;
def subtask(img, init, total_thorax, idx):
snake = active_contour(gaussian(img, 3, preserve_range=False),
init, alpha=0.09, beta=0.1, gamma=0.001, w_edge=1)
snake = np.array(snake, dtype=np.int32);
tmp = copy(snake);
snake[:,0] = tmp[:, 1];
snake[:,1] = tmp[:, 0];
tmp = np.zeros(shape=img.shape, dtype=np.uint8);
thorax_region = cv2.fillPoly(tmp, [snake], color = (255,255,255));
total_thorax[idx] = thorax_region;
# fig, ax = plt.subplots(figsize=(7, 7))
# ax.imshow(img, cmap=plt.cm.gray)
# ax.plot(init[:, 1], init[:, 0], '--r', lw=3)
# ax.plot(snake[:, 1], snake[:, 0], '-b', lw=3)
# ax.set_xticks([]), ax.set_yticks([])
# ax.axis([0, img.shape[1], img.shape[0], 0])
# plt.show()
return thorax_region
def segment_thorax(img):
#img = cv2.imread(img_path, cv2.IMREAD_GRAYSCALE);
img = cv2.resize(img, (1024,1024));
h,w = img.shape;
segment_thorax = np.ones(shape=img.shape, dtype=np.uint8);
cols_sum = np.sum(img, axis = 0);
rows_sum = np.sum(img, axis = 1);
cols_sum = np.where(cols_sum > 0, 1, 0);
cols_sum = cols_sum.tolist();
if 1 not in cols_sum:
return img;
x_start = cols_sum.index(1);
x_end = len(cols_sum) - 1 - cols_sum[::-1].index(1);
rows_sum = np.where(rows_sum > 0, 1, 0);
rows_sum = rows_sum.tolist();
y_start = rows_sum.index(1);
y_end = len(rows_sum) - 1 - rows_sum[::-1].index(1);
x_start -= GAP;
x_end += GAP;
y_start -= GAP;
y_end += GAP;
#union on beta=0.05 and 0.1
#union on alpha=0.015 and 0.09
x_length = (x_end - x_start);
y_length = (y_end - y_start);
val_range = [(0,0), (-x_length/4, -y_length/4), (-x_length/4, y_length/4), (x_length/4, -y_length/4), (x_length/4, y_length/4)];
total_thorax = [None]*5;
first = True;
threads = list();
#for idx,v in enumerate(val_range):
#img = cv2.line(img, (x_start, y_start), (x_start, y_end), (255, 255, 255), 2);
# cv2.imshow('img', img);
# cv2.waitKey();
s = np.linspace(x_start, x_end, 250);
r = [y_start]*len(s);
points_top = np.array([r,s]).T;
s = np.linspace(x_end, x_start,250);
r = [y_end]*len(s);
points_down = np.array([r,s]).T;
s = np.linspace(y_end, y_start, 250);
r = [x_start]*len(s);
points_left = np.array([s,r]).T;
s = np.linspace(y_start, y_end, 250);
r = [x_end]*len(s);
points_right = np.array([s,r]).T;
init = np.concatenate([points_top, points_right, points_down, points_left], axis = 0);
ret_thorax = subtask(img, init, total_thorax, 0);
# b = cv2.addWeighted(img, 0.5, ret_thorax, 0.5, 0.0);
# cv2.imshow('r', b);
# cv2.waitKey();
# c = x_start + x_length/2 + v[0] + x_length/2*np.cos(s)
# r = y_start + y_length/2 + v[1] + y_length/2*np.sin(s)
# init = np.array([r, c]).T
#x = threading.Thread(target=subtask, args=(img, init, total_thorax, idx));
#threads.append(x);
#x.start();
# for t in threads:
# t.join();
# img_thresh = img==0;
# img = np.repeat(np.expand_dims(img, axis = 2), 3, axis = 2);
# img = np.where(img > [0,0,0], [255,0,0],[0,0,0]).astype("uint8");
# img[img_thresh] = [255,255,255]
# fig, ax = plt.subplots(figsize=(7, 7))
# ax.imshow(img, cmap=plt.cm.gray)
# ax.plot(total_thorax[0][:, 0], total_thorax[0][:, 1], '-b', lw=3)
# plt.show();
# ret_thorax = total_thorax[0];
# for i in range(1,5):
# ret_thorax = cv2.bitwise_or(total_thorax[i], ret_thorax);
#cv2.imshow('t', ret_thorax);
#cv2.waitKey();
return ret_thorax;
if __name__ == "__main__":
img_list = glob("ribs\\*.png");
#img_list = reversed(img_list);
for img_name in img_list:
file_name = os.path.basename(img_name);
file_name = file_name[:file_name.rfind('_')] + ".jpeg";
#original_img = cv2.imread(os.path.sep.join(['ribs', file_name]), cv2.IMREAD_GRAYSCALE);
#original_img = cv2.resize(original_img, (IMG_WDITH, IMG_HEIGHT));
img = cv2.imread(img_name, cv2.IMREAD_GRAYSCALE);
img = cv2.resize(img, (1024,1024));
h,w = img.shape;
cols_sum = np.sum(img, axis = 0);
rows_sum = np.sum(img, axis = 1);
cols_sum = np.where(cols_sum > 0, 1, 0);
cols_sum = cols_sum.tolist();
x_start = cols_sum.index(1);
x_end = len(cols_sum) - 1 - cols_sum[::-1].index(1);
rows_sum = np.where(rows_sum > 0, 1, 0);
rows_sum = rows_sum.tolist();
y_start = rows_sum.index(1);
y_end = len(rows_sum) - 1 - rows_sum[::-1].index(1);
x_start -= GAP;
x_end += GAP;
y_start -= GAP;
y_end += GAP;
#union on beta=0.05 and 0.1
#union on alpha=0.015 and 0.09
x_length = (x_end - x_start);
y_length = (y_end - y_start);
range = [(0,0), (-x_length/4, -y_length/4), (-x_length/4, y_length/4), (x_length/4, -y_length/4), (x_length/4, y_length/4)];
snks = [];
total_thorax = None;
first = True;
for v in range:
s = np.linspace(0, 2*np.pi, 1000)
c = x_start + x_length/2 + v[0] + x_length/2*np.cos(s)
r = y_start + y_length/2 + v[1] + y_length/2*np.sin(s)
init = np.array([r, c]).T
temp_shape = np.zeros(shape = img.shape, dtype=np.uint8);
snake = active_contour(gaussian(img, 3, preserve_range=False),
init, alpha=0.09, beta=0.1, gamma=0.001, w_edge=15)
snake = np.array(snake, dtype=np.int32);
snks.append(snake);
tmp = copy(snake);
snake[:,0] = tmp[:, 1];
snake[:,1] = tmp[:, 0];
tmp = np.zeros(shape=img.shape, dtype=np.uint8);
contours = np.array([[50,50], [50,150], [150,150], [150,50]])
thorax_region = cv2.fillPoly(tmp, [snake], color = (255,255,255));
if first is True:
total_thorax = thorax_region;
first = False;
else:
total_thorax = cv2.bitwise_or(total_thorax, thorax_region);
print("added new thorax...");
#focused_thorax = np.where(total_thorax == 255, original_img, 0);
betas = [0.05, 0.1];
for b in betas:
s = np.linspace(0, 2*np.pi, 1000)
c = x_start + x_length/2 + x_length/2*np.cos(s)
r = y_start + y_length/2 + y_length/2*np.sin(s)
init = np.array([r, c]).T
temp_shape = np.zeros(shape = img.shape, dtype=np.uint8);
snake = active_contour(gaussian(img, 3, preserve_range=False),
init, alpha=0.015, beta=b, gamma=0.001, w_edge=15)
snake = np.array(snake, dtype=np.int32);
snks.append(snake);
tmp = copy(snake);
snake[:,0] = tmp[:, 1];
snake[:,1] = tmp[:, 0];
tmp = np.zeros(shape=img.shape, dtype=np.uint8);
contours = np.array([[50,50], [50,150], [150,150], [150,50]])
thorax_region = cv2.fillPoly(tmp, [snake], color = (255,255,255));
total_thorax = cv2.bitwise_or(total_thorax, thorax_region);
print("added new thorax...");
#focused_thorax = np.where(total_thorax == 255, original_img, 0);
#cv2.imwrite("res\\" + file_name + "_o.jpeg", original_img);
#cv2.imwrite("res\\" + file_name + "_t.jpeg", focused_thorax);
#cv2.imshow('t', focused_thorax);
#cv2.imshow('tr', total_thorax);
# cv2.imshow('treg', thorax_region);
#cv2.waitKey();
fig, ax = plt.subplots(figsize=(7, 7))
ax.imshow(img, cmap=plt.cm.gray)
#ax.plot(init[:, 1], init[:, 0], '--r', lw=1)
#for idx,s in enumerate(snks):
ax.plot(snks[0][:, 0], snks[0][:, 1], lw=1);
ax.set_xticks([]), ax.set_yticks([])
ax.axis([0, img.shape[1], img.shape[0], 0])
plt.show()
plt.savefig('p.png');