python ctypes

UII

python使用ctypes调用需要注意numpy里面有order的区别，当order为'C'时是按照C的方式排列数据，但其默认为'F'，所以使用的时候需要转换，完整调用的例子：

# coding=utf-8
import ctypes
import _ctypes
import numpy as np
import platform
from md.image3d.python.image3d import Image3d
from md.utils.python.find_dll import find_dll
# dynamic library
lib = None
# function pointer dictionary
fun_dict = {}
def __get_library_path():
  dll_file = find_dll('py_centerline_snake', __file__, package_name='md_cardiac')
  if dll_file is None:
    raise OSError('dll not found')
  return dll_file
def __load_c_functions():
  global lib, fun_dict
  lib = ctypes.cdll.LoadLibrary(__get_library_path())
  lib.py_refine_centerline_by_snake.argtypes = [
    np.ctypeslib.ndpointer(
      dtype=ctypes.c_double,
      ndim=2,
      flags='C_CONTIGUOUS'
    ),
    ctypes.c_int32,
    ctypes.c_double,
    ctypes.c_double,
    ctypes.c_double,
    ctypes.c_double,
    ctypes.c_int32,
    ctypes.c_void_p,
    ctypes.c_char,
    np.ctypeslib.ndpointer(
      dtype=ctypes.c_int32,
      ndim=1,
      flags='C_CONTIGUOUS'
    ),
    np.ctypeslib.ndpointer(
      dtype=ctypes.c_double,
      ndim=1,
      flags='C_CONTIGUOUS'
    ),
    ctypes.c_bool,
    ctypes.c_double,
    np.ctypeslib.ndpointer(
      dtype=np.float64,
      ndim=2,
      flags='C_CONTIGUOUS'
    )
  ]
  lib.py_refine_centerline_by_snake.restype = None
  fun_dict['py_refine_centerline_by_snake'] = lib.py_refine_centerline_by_snake
def unload():
  global lib, fun_dict
  try:
    while lib is not None:
      if platform.system() == 'Windows':
        _ctypes.FreeLibrary(lib._handle)
      else:
        _ctypes.dlclose(lib._handle)
  except:
    lib = None
    fun_dict = {}
def load():
  unload()
  __load_c_functions()
# load dynamic library
load()
def load_c_functions_if_necesary():
  if len(fun_dict) == 0:
    print('[info] py_refine_centerline_by_snake dll reloaded')
    __load_c_functions()
def call_func(func_name, *args):
  load_c_functions_if_necesary()
  if len(args) == 0:
    return fun_dict[func_name]()
  else:
    return fun_dict[func_name](*args)
def refine_centerline_by_snake(
  centerline,
  mask,
  multi_label=True,
  label=1,
  alpha=0.2 * 0.6,
  beta=0.5 * 0.6,
  gamma=5.0 * 0.6,
  omega=0.15,
  iters=10,
  cross_section_size=[51, 51],
  cross_section_spacing=[0.2, 0.2],
  max_refinement_distance_in_mm=0.5
):
  assert isinstance(mask, Image3d), 'mask must be an Image3d object'
  centerline = np.array(centerline, order='C', dtype=np.float)
  assert centerline.shape[1] == 3
  cross_section_size = np.array(cross_section_size, dtype=np.int32, order='C')
  assert cross_section_size.shape[0] == 2
  cross_section_spacing = np.array(cross_section_spacing, dtype=np.float, order='C')
  assert cross_section_spacing.shape[0] == 2
  refined_centerline = np.zeros_like(centerline, order='C', dtype=np.float)
  call_func(
    'py_refine_centerline_by_snake', 
    np.ascontiguousarray(centerline),
    ctypes.c_int32(centerline.shape[0]),
    ctypes.c_double(alpha),
    ctypes.c_double(beta),
    ctypes.c_double(gamma),
    ctypes.c_double(omega),
    ctypes.c_int32(iters),
    mask.ptr,
    ctypes.c_char(label),
    cross_section_size,
    cross_section_spacing,
    ctypes.c_bool(multi_label),
    ctypes.c_double(max_refinement_distance_in_mm),
    refined_centerline
  )
  return refined_centerline
if __name__ == "__main__":
  import pandas as pd
  import numpy as np
  import md.image3d.python.image3d_io as cio
  path_centerline = '/raid/disk/CTA_Cardiac/94_lesion_train/'\
    '02_centerline_annotation/0.3mm/AI01_0001_01_L_diast_best_0.50mm/'\
      'SCPR_RCA.csv'
  path_mask = '/raid/disk/CTA_Cardiac/02_mask/01_multi_mask_refine/multi_mask/'\
    'AI01_0001_01_L_diast_best_0.50mm.mhd'
  df = pd.read_csv(path_centerline)
  centerline = np.array(df[['3d_x', '3d_y', '3d_z']].values)
  mask = cio.read_image(path_mask, dtype=np.uint8)
  refined_centerline = refine_centerline_by_snake(centerline, mask)
  print(refined_centerline)