def full_process():
SRC_DATA = opt.source
print('Preprocessing starts........ ', end="")
patients = [
os.path.join(SRC_DATA, name) for name in os.listdir(SRC_DATA)
if os.path.isdir(os.path.join(SRC_DATA, name))
]
patient = patients[1]
name_idx = len(SRC_DATA)
image = read_images_masks(patient)
#Predicting and cutting bounding box
for slice in range(image.shape[0]):
plt.imsave(bbox_saving_path + "/hi" + str(slice) + ".jpg",
image[slice],
cmap="gray")
with HiddenPrints():
result = detect("/home/seenia/allen/Final/processing/sampleP",
"/home/seenia/allen/Final/demo/best.pt")
minxP, minyP, maxxP, maxyP = 1000, 1000, 0, 0
for i in result:
if (len(i) == 4):
minxP, minyP, maxxP, maxyP = min(minxP, int(i[0])), min(
minyP, int(i[1])), max(maxxP,
int(i[2])), max(maxyP, int(i[3]))
#Saving npy
image = image[:, minyP - 5:maxyP + 5, minxP - 5:maxxP + 5]
saving_name = processed_path + patient[name_idx:] + "image.npy"
np.save(saving_name, image)
print('Preprocessing Finished')
#Prediction
print('Prediction starts........ ', end="")
predict_mask(saving_name, opt.weights)
print('Prediction Finished')
#Saving results
print('Saving results starts........ ', end="")
rtstruct = RTStructBuilder.create_new(dicom_series_path=opt.source)
names = ['Lung_L', 'Lung_R', 'Heart', 'SpinalCord', 'Esophagus']
colour = [[197, 165, 145], [197, 165, 145], [127, 150, 88],
[253, 135, 192], [85, 188, 255]]
with HiddenPrints():
for organ, clr in zip(names, colour):
result = np.load(result_path + organ + ".npy")
result = result > 0
result = result.transpose(1, 2, 0)
#if(arr.count(organ[0].lower())>0):
rtstruct.add_roi(mask=result, color=clr, name=organ)
print('Saving results Finished')
rtstruct.save(opt.dest + 'final')
#removing all unwanted files
stream1 = os.popen(
'rm -r /home/seenia/allen/Final/processing/sampleP/*.jpg')
stream2 = os.popen(
'rm -r /home/seenia/allen/Final/processing/dataProcessed/*.npy')
stream3 = os.popen(
'rm -r /home/seenia/allen/Final/processing/resultsP/*.npy')
def convert_nifti(dcm_path,
mask_input,
output_file,
color_map=cm.get_cmap("rainbow")):
"""Convert a set of masks to a DICOM RTStruct object.
This function now utilises the rt-utils package: https://github.com/qurit/rt-utils
We keep this function in here for compatibility
Args:
dcm_path (str|pathlib.Path): Path to the reference DICOM series
mask_input (dict|list): A dictionary containing the name as key and image as value. Or a
list of string with comma separated name and mask paths (name,path)
output_file (str|pathlib.Path): The path to the file to write the RTStruct
color_map (matplotlib.colors.Colormap, optional): Colormap to use for output. Defaults to
cm.get_cmap("rainbow").
"""
logger.info("Will convert the following Nifti masks to RTStruct:")
masks = {} # Dict stores key value pairs for masks
if isinstance(mask_input, dict):
# Dict was already passed in
masks = mask_input
else:
# Otherwise convert list of comma separated masks
for mask in mask_input:
mask_parts = mask.split(",")
masks[mask_parts[0]] = mask_parts[1]
if not isinstance(dcm_path, Path):
dcm_path = Path(dcm_path)
dcm_series_path = None
if dcm_path.is_file():
dcm_series_path = dcm_path.parent
else:
dcm_series_path = dcm_path
rtstruct = RTStructBuilder.create_new(
dicom_series_path=str(dcm_series_path))
for mask_name in masks:
# Use a hash of the name to get the color from the supplied color map
color = color_map(hash(mask_name) % 256)
color = color[:3]
color = [int(c * 255) for c in color]
mask = masks[mask_name]
if not isinstance(mask, sitk.Image):
mask = sitk.ReadImage(str(mask))
bool_arr = sitk.GetArrayFromImage(mask) != 0
bool_arr = np.transpose(bool_arr, (1, 2, 0))
rtstruct.add_roi(mask=bool_arr, color=color, name=mask_name)
rtstruct.save(str(output_file))
def new_rtstruct() -> RTStruct:
path = get_and_test_series_path()
rtstruct = RTStructBuilder.create_new(path)
return rtstruct
def test_create_from_empty_series_dir():
empty_dir_path = os.path.join(os.path.dirname(__file__), "empty")
assert os.path.exists(empty_dir_path)
with pytest.raises(Exception):
RTStructBuilder.create_new(empty_dir_path)
def new_rtstruct() -> RTStruct:
rtstruct = RTStructBuilder.create_new(get_series_path())
return rtstruct
type=str,
default=
'/home/seenia/allen/Final/demo/Unet_3D_DiceLoss_epochs_40_trainsize_45_loss_dice_trainloss_4.214956012864312',
help='path to model weights')
parser.add_argument('--source',
type=str,
default='/home/seenia/allen/Final/demo/data/',
help='path to dicom series')
parser.add_argument('--dest',
type=str,
default='/home/seenia/allen/Final/',
help='path to destination')
opt = parser.parse_args()
flag = 0
if (path.exists(opt.weights) & path.exists(opt.source)
& path.exists(opt.dest)):
try:
demo = RTStructBuilder.create_new(dicom_series_path=opt.source)
flag = 1
except:
print("No DICOM series found in input path")
else:
print("Weights File exists:" + str(path.exists(opt.weights)))
print("Source File exists:" + str(path.exists(opt.source)))
print("Destination File exists:" + str(path.exists(opt.dest)))
if (flag == 1):
full_process()
def get_rtstruct(dirname) -> RTStruct:
path = get_and_test_series_path(dirname)
rtstruct = RTStructBuilder.create_new(path)
return rtstruct