def get_keyPoints(self):
local_threshold = float(self.params['local_threshold'])
_device = int(self.params['device'])
symmetry = float(self.params['symmetry'])
targetDir = str(self.params['targetDir'])
cellsize = int(self.params['cellsize'])
ccl = str(self.params['ccl'])
print("[get_keyPoints] device: {}, verbose: {}".format(
_device, self.verbose))
for file in self.files:
img = imreadTif(file)
binary = threshold_loader(img,
stride=32,
grid_size=32,
color_channel=4095,
thres=local_threshold,
device=_device,
FLAG="matrix")
cells = ccl_map(binary, ccl, cellsize, device=_device)
binary, cells = symmetry_mapping(cells, thres=symmetry)
pos = center_cell(cells)
img_out = imreadTif(file)
if (self.verbose == True):
img = img_out.astype('uint16')
img = gray2rgb(img)
img = rescale_intensity(img)
for point in pos:
img = drawMarker(img, point)
_path = targetDir + "/" + file.replace("tif", "png")
imwrite(img, _path)
imwrite(binary, _path.replace(".png", "_mapping.jpeg"))
yield file, cells, pos, img_out
else:
yield file, cells, pos, img_out
def analyze(img, checkPath, targetPath, device):
stride = 5
pos_x = np.arange(0, 2048, stride)
pos_y = np.arange(0, 2048, stride)
vx, vy = np.meshgrid(pos_x, pos_y)
pos = np.stack([vx, vy]).reshape((2, -1)).transpose([1, 0])
PRED, pos = inference(img, pos, checkPath, device, size=31)
op = operation(device=device)
INDEX = op.where(PRED > 0)
print("finished where")
pos = pos[INDEX]
pos = pos.ndarray().get()
img = rescale_intensity(img.astype('uint8'))
img = drawRedPoints(img, pos, half_size=2)
imwrite(img, targetPath)
img = imreadTif(path)
pos = doubleLayer_analyze(img)
pos = pos.cpu()
_pos = []
half_size = 15
for x in range(-1 * half_size, half_size, 5):
for y in range(-1 * half_size, half_size, 5):
_pos.append(pos + np.array([x, y]))
pos = np.concatenate(_pos, axis=0)
print(pos.shape)
img = rescale_intensity(img.astype('uint8'))
img = drawRedPoints(img, pos, half_size=2)
imwrite(img, "./log/result.png")
# if __name__ == '__main__':
# from CV.ImageIO import center_cell, imreadTif, imshow_plt, plt, gray2rgb, drawMarker, drawRedPoints, imwrite, rescale_intensity
# import os, re
# from timeit import default_timer as timer
# path = "../../../../DATA/CELL/10.tif"
# # path = "/media/processed/Dec_2017/CST-20171211-01/changhai12.11/DATA/"
# # path = path+list(filter(lambda x: re.search("tif", x), os.listdir(path)))[0]
# print(path)
# # checkPath = "./log/params/size_61/25.pkl"
def get_points(self, half_size=80, extra=0):
local_threshold = float(self.params['local_threshold'])
_device = int(self.params['device'])
symmetry = float(self.params['symmetry'])
# targetDir = str(self.params['targetDir'])
cellsize = int(self.params['cellsize'])
ccl = str(self.params['ccl'])
print("[get_insider] device: {}, verbose: {}".format(
_device, self.verbose))
for file in self.files:
img = imreadTif(file)
binary = threshold_loader(img,
stride=32,
grid_size=32,
color_channel=4095,
thres=local_threshold,
device=_device,
FLAG="matrix")
cells = ccl_map(binary, ccl, cellsize, device=_device)
binary, cells = symmetry_mapping(cells, thres=symmetry)
pos = center_cell(cells)
img_bound = [0, 2048]
mapping = np.zeros((2048, 2048))
num = len(cells) + extra
img_out = imreadTif(file)
for cell in cells:
_bound, _ = boundary(cell=cell, _range=None)
if (_bound[0] - half_size >= img_bound[0]):
_bound[0] = _bound[0] - half_size
else:
_bound[0] = img_bound[0]
if (_bound[2] - half_size >= img_bound[0]):
_bound[2] = _bound[2] - half_size
else:
_bound[2] = img_bound[0]
if (_bound[1] + half_size <= img_bound[1]):
_bound[1] = _bound[1] + half_size
else:
_bound[1] = img_bound[1]
if (_bound[3] - half_size <= img_bound[1]):
_bound[3] = _bound[3] + half_size
else:
_bound[3] = img_bound[1]
mapping[_bound[0]:_bound[1], _bound[2]:_bound[3]] = 1
mapping[0:half_size, :] = 1
mapping[img_bound[1] - half_size:img_bound[1], :] = 1
mapping[:, 0:half_size] = 1
mapping[:, img_bound[1] - half_size:img_bound[1]] = 1
pts = np.array(np.where(mapping == 0)).transpose()
if (pts.shape[0] >= num):
index = np.random.choice(pts.shape[0], num)
choice = pts[index]
else:
choice = np.zeros((0, 2))
if (len(pos) > 0):
if (self.verbose == True):
img = img_out.copy()
img = rescale_intensity(img.astype('uint8'))
mask_true = drawMarkers(np.array(pos), 10, 2)
mask_false = drawMarkers(choice, 10, 2)
img = np.stack([img, img, img], axis=2)
index = list(np.where(mask_true == 1))
index.append(
(np.ones(index[0].shape[0]) * 2).astype('int32'))
# img[index] = 55535
img[index] = 255
index = list(np.where(mask_false == 1))
index.append(
(np.ones(index[0].shape[0]) * 1).astype('int32'))
# img[index] = 55535
img[index] = 255
_path = self.targetDir + "/" + os.path.basename(
file).replace("tif", "png")
print("[verbose]: ", _path)
imwrite(img, _path)
yield file, cells, pos, choice, img_out
else:
yield file, cells, pos, choice, img_out