def manual_segmentation(self, idx):
"""
:param idx: {int} -- the index of the .broct file
:return: None
"""
for data in scans("../../data/oct_volume_calibration/" +
self.serial_num + "/config" + str(idx) + ".broct"):
volume = data['volume']
# volume = volume[:, :, 85:]
volume = volume[:, :, :]
volume_raw = np.array(volume, copy=True)
for i in tqdm(range(volume.shape[0])):
volume_raw[i] = volume_raw[i][::-1, :]
pcd_s = self.pointcloud_process(volume_raw)
pcd_s.paint_uniform_color([1, 0.706, 0])
draw_geometries_with_editing([pcd_s])
def intensity_projection(self, index, brightest_pix):
"""
:param index: {int} -- the index of the .broct file
:param brightest_pix: {int} -- the brightest pixel value
:return: thres_map: {numpy.array} -- the intensity projection threshold map
:return: volume: {numpy.array} -- the OCT volume
:return: brightest_pix: {int} -- the brightest pixel value
"""
for data in scans("../../data/oct_volume_calibration/" +
self.serial_num + "/config" + str(index) + ".broct"):
volume = data['volume']
for i in tqdm(range(volume.shape[0])):
volume[i] = volume[i][::-1, :]
volume_copy = np.copy(volume)
volume = pcd_y_clip(volume, self.clip_threshold_y[index - 1])
volume_sum = np.max(volume, axis=1)
volume_sum -= volume_sum.min()
if index == 1:
brightest_pix = volume_sum.max()
volume_sum = np.array(volume_sum *
(100 / (brightest_pix - volume_sum.min())),
dtype=np.uint8)
# ### DEBUG ###
cv.namedWindow('component', cv.WINDOW_NORMAL)
cv.imshow('component', volume_sum)
cv.waitKey(10)
thres_map = cv.threshold(volume_sum, self.map_thres, 255,
cv.THRESH_BINARY)[1]
if index == 6:
thres_map = cv.morphologyEx(thres_map, cv.MORPH_CLOSE,
np.ones((3, 3)))
else:
thres_map = cv.morphologyEx(thres_map, cv.MORPH_CLOSE,
np.ones((5, 5)))
if self.clip_threshold_xz[index - 1][1] == -1:
thres_map[:, :self.clip_threshold_xz[index - 1][0]] = 0
else:
thres_map[:, self.clip_threshold_xz[index - 1][0]:] = 0
if self.clip_threshold_xz[index - 1][2] != 0:
thres_map[self.clip_threshold_xz[index - 1][2]:, :] = 0
volume_copy[:, :self.clip_threshold_y[index - 1][0] + 1, :] = 0
return thres_map, volume_copy, brightest_pix
def save_ideal_png(ideal_cscan, serial_num):
"""
:param ideal_cscan: {int} -- the index of the ideal C-scan
:param serial_num: {string} -- the serial number of needle insertion
:return: None
"""
for data in scans(
"../../data/suture_experiment/suture_result_broct_files/AMAL_wound/"
+ serial_num + "_wound.broct"):
volume = data['volume']
bscan = volume[ideal_cscan - 1]
bscan = bscan[::-1, :]
bscan = (bscan - 54) / (100 - 54)
bscan = np.clip(bscan, 0, 1)
bscan = (255 * bscan).astype(np.uint8)
os.makedirs(
"../../data/suture_experiment/suture_result_broct_files/AMAL_png/"
+ serial_num + "/",
exist_ok=True)
imageio.imwrite(
'../../data/suture_experiment/suture_result_broct_files/AMAL_png/'
+ serial_num + '/bscan.png',
bscan,
format='png')
import numpy
import cv2
import matplotlib
matplotlib.use('Qt5Agg')
from matplotlib import pyplot
from PyBROCT.io.reader import scans
from PyBROCT.render.cuda import CudaRenderer
from PyBROCT.render.cpu import CpuRenderer
from PyBROCT.matrix_util import perspective, lookat, rotx, roty, rotz, translate, scale, ortho
path = r"C:\Users\Mark\Downloads\eye.broct"
data = next(scans(path))[1]
vol = data['volume']
# vol = numpy.swapaxes(vol, 0, 2).copy()
print(vol.shape)
vol[:, 1000:, :] = 0
vol[:, :50, :] = 0
# vol = vol[:, ::10, :]
# vol = numpy.flip(vol, axis=1)
# vol[50:150, :, :] = 0
# vol[:, :, 300:500] = 0
# pyplot.imshow(vol[0, :400, :], aspect='auto')
# pyplot.show()
# raise SystemExit
group.add_argument('--xscan',
nargs='?',
type=int,
help='cross B-scan index to dump')
group.add_argument('--scan-all',
action='store_true',
help='dump all B-scans')
group.add_argument('--mip', action='store_true', help='dump a MIP')
args = parser.parse_args()
chunks = max(1, args.average)
for path in args.path:
for path in glob(path):
for (vidx, vol) in scans(path, skip=args.volume, count=args.count):
data = vol['volume']
if args.svp:
print(path, vidx, 'SVP', end=' ')
svp = numpy.mean(data, axis=1)
svp = _postprocess(args, svp)
out = '{}_{:03d}_svp.png'.format(
os.path.splitext(path)[0], vidx)
dpi = (1e3 * vol['xlength'] / svp.shape[0],
1e3 * vol['zlength'] / svp.shape[1])
imwrite(out, svp, dpi=dpi)
print('->', out)
elif args.mip:
import numpy
import imageio
import os
from PyBROCT.io.reader import scans
if __name__ == '__main__':
serial_num = '200305O'
for data in scans(
"../../data/suture_experiment/suture_result_broct_files/suture/" +
serial_num + "_suture.broct"):
volume = data['volume']
idx = 222
for bscan in volume[222:256]:
bscan = bscan[::-1, :]
# white and black levels
bscan = (bscan - 54) / (100 - 54)
bscan = numpy.clip(bscan, 0, 1)
bscan = (255 * bscan).astype(numpy.uint8)
os.makedirs("../../data/suture_experiment/png_data/" + serial_num +
"/",
exist_ok=True)
imageio.imwrite('../../data/suture_experiment/png_data/' +
serial_num + '/' + str(idx) + '_bscan.png',
bscan,
format='png')
idx += 1