def run(args):
logging.info("Loading and initializing bone pipeline dynamically")
input_dir = args.input
output_path = args.output
pipeline_module = load_pipeline_dynamically(plid)
pipeline_module.run(input_dir, output_path, [1])
logging.info("Done.")
def generate(entries, plid, ar_view):
output_path = entries["Output File"].get()
segment_type = list(entries["seg_types"].curselection())
segment_type = [s + 1 for s in segment_type]
quiet = entries["silence_log"].get()
if plid != "brain_segmentation":
input_dir = entries["Input"].get()
else:
flair_dir = entries["Flair Input"].get()
t1_dir = entries["T1 Input"].get()
ir_dir = entries["IR Input"].get()
input_dir = [flair_dir, t1_dir, ir_dir]
if ((plid == "brain_segmentation" and "" in input_dir) or input_dir == ""
or output_path == "" or not segment_type):
messagebox.showerror(
"Error",
"Please ensure input/s, an output path, and segmentation type is inputted",
)
else:
logging.basicConfig(
level=logging.ERROR if quiet else logging.INFO,
format="%(asctime)s - %(module)s:%(levelname)s - %(message)s",
datefmt="%d-%b-%y %H:%M:%S",
)
logging.info("Loading and initializing pipeline dynamically")
pipeline_module = load_pipeline_dynamically(plid)
if ar_view:
pipeline_module.run(input_dir, output_path, segment_type, False)
holo_registration_wrapper.start_viewer(output_path, plid)
else:
pipeline_module.run(input_dir, output_path, segment_type)
logging.info("Done.")
def run(args):
logging.info("Loading and initializing abdominal pipeline dynamically")
input_dir = args.input
output_path = args.output
segment_type = args.type
pipeline_module = load_pipeline_dynamically(plid)
pipeline_module.run(input_dir, output_path, segment_type)
logging.info("Done.")
def openViewer():
plid = "glb_importer"
file_selected = filedialog.askopenfilename(filetypes=(("glb file",
"*.glb"),
("All files", "*")))
if file_selected != "":
pipeline_module = load_pipeline_dynamically(plid)
pipeline_module.run(file_selected)
def run(args):
logging.info("Loading and initializing bone pipeline dynamically")
flair_input_directory = args.flair_input
t1_input_directory = args.t1_input
ir_input_directory = args.ir_input
output_path = args.output
segment_type = args.type
pipeline_module = load_pipeline_dynamically(plid)
pipeline_module.run(
[flair_input_directory, t1_input_directory, ir_input_directory],
output_path,
segment_type,
)
logging.info("Done.")
def run(args):
logging.info("Loading and initializing mesh viewer dynamically")
input_file = args.input_file
pipeline_module = load_pipeline_dynamically(plid)
pipeline_module.run(input_file)
logging.info("Done.")