Python转Cython编译错误：assert len(cubemap.shape)==3报错

将Python代码转为Cython以提升性能时，编译阶段在assert len(cubemap.shape) == 3语句处报错，错误提示为Cannot convert 'npy_intp *' to Python object。

完整Cython代码 #

import numpy
from . import utils

cimport numpy
cimport cython

cdef bytes mode_bilinear = b'bilinear'
cdef bytes mode_nearest = b'nearest'
cdef bytes cube_format_horizon = b'horizon'
cdef bytes cube_format_list = b'list'
cdef bytes cube_format_dict = b'dict'
cdef bytes cube_format_dice = b'dice'

@cython.boundscheck(False)
@cython.wraparound(False)
def c2e(numpy.ndarray[numpy.float64_t, ndim=3] cubemap, int h, int w, bytes mode=mode_bilinear, bytes cube_format=cube_format_dice):
    cdef int order

    if mode == mode_bilinear:
        order = 1
    elif mode == mode_nearest:
        order = 0
    else:
        raise NotImplementedError('unknown mode')

    if cube_format == cube_format_horizon:
        pass
    elif cube_format == cube_format_list:
        cubemap = utils.cube_list2h(cubemap)
    elif cube_format == cube_format_dict:
        cubemap = utils.cube_dict2h(cubemap)
    elif cube_format == cube_format_dice:
        cubemap = utils.cube_dice2h(cubemap)
    else:
        raise NotImplementedError('unknown cube_format')

    assert len(cubemap.shape) == 3
    assert cubemap.shape[0] * 6 == cubemap.shape[1]
    assert w % 8 == 0
    cdef int face_w = cubemap.shape[0]

    cdef numpy.ndarray[numpy.float64_t, ndim=2] uv = utils.equirect_uvgrid(h, w)
    cdef numpy.ndarray[numpy.float64_t, ndim=2] u = uv[:, 0]
    cdef numpy.ndarray[numpy.float64_t, ndim=2] v = uv[:, 1]
    cdef numpy.ndarray[numpy.float64_t, ndim=3] cube_faces = numpy.stack(numpy.split(cubemap, 6, 1), 0)

    # Get face id to each pixel: 0F 1R 2B 3L 4U 5D
    cdef numpy.ndarray[numpy.int32_t, ndim=2] tp = utils.equirect_facetype(h, w)
    cdef numpy.ndarray[numpy.float64_t, ndim=2] coor_x = numpy.zeros((h, w))
    cdef numpy.ndarray[numpy.float64_t, ndim=2] coor_y = numpy.zeros((h, w))

    for i in range(4):
        mask = (tp == i)
        coor_x[mask] = 0.5 * numpy.tan(u[mask] - numpy.pi * i / 2)
        coor_y[mask] = -0.5 * numpy.tan(v[mask]) / numpy.cos(u[mask] - numpy.pi * i / 2)

    mask = (tp == 4)
    cdef numpy.ndarray[numpy.float64_t, ndim=2] c = 0.5 * numpy.tan(numpy.pi / 2 - v[mask])
    coor_x[mask] = c * numpy.sin(u[mask])
    coor_y[mask] = c * numpy.cos(u[mask])

    mask = (tp == 5)
    c = 0.5 * numpy.tan(numpy.pi / 2 - numpy.abs(v[mask]))
    coor_x[mask] = c * numpy.sin(u[mask])
    coor_y[mask] = -c * numpy.cos(u[mask])

    # Final renormalize
    coor_x = (numpy.clip(coor_x, -0.5, 0.5) + 0.5) * face_w
    coor_y = (numpy.clip(coor_y, -0.5, 0.5) + 0.5) * face_w

    cdef numpy.ndarray[numpy.float64_t, ndim=3] equirec = numpy.stack([
        utils.sample_cubefaces(cube_faces[..., i], tp, coor_y, coor_x, order=order)
        for i in range(cube_faces.shape[2])
    ], axis=-1)

    return equirec

编译错误信息 #

Compiling utils.pyx because it changed.
Compiling c2e.pyx because it changed.
[1/2] Cythonizing c2e.pyx
C:\Users\Ju-Bei\AppData\Local\Programs\Python\Python311\Lib\site-packages\Cython\Compiler\Main.py:384: FutureWarning: Cython directive 'language_level' not set, using '3str' for now (Py3). This has changed from earlier releases! File: C:\Users\Ju-Bei\Documents\Hyper Render 360\Hyper 360 Convert\fullcython\c2e.pyx
  tree = Parsing.p_module(s, pxd, full_module_name)

Error compiling Cython file:
------------------------------------------------------------
...
    elif cube_format == cube_format_dice:
        cubemap = utils.cube_dice2h(cubemap)
    else:
        raise NotImplementedError('unknown cube_format')    

    assert len(cubemap.shape) == 3
                      ^
------------------------------------------------------------

c2e.pyx:37:22: Cannot convert 'npy_intp *' to Python object 
Traceback (most recent call last):
  File "C:\Users\Ju-Bei\Documents\Hyper Render 360\Hyper 360 Convert\fullcython\setup.py", line 5, in <module>
    ext_modules = cythonize([
                  ^^^^^^^^^^^
  File "C:\Users\Ju-Bei\AppData\Local\Programs\Python\Python311\Lib\site-packages\Cython\Build\Dependencies.py", line 1134, in cythonize    
    cythonize_one(*args)
  File "C:\Users\Ju-Bei\AppData\Local\Programs\Python\Python311\Lib\site-packages\Cython\Build\Dependencies.py", line 1301, in cythonize_one
    raise CompileError(None, pyx_file)
Cython.Compiler.Errors.CompileError: c2e.pyx

错误原因 #

函数参数cubemap最初被声明为静态类型的numpy.ndarray[numpy.float64_t, ndim=3]，但当通过utils.cube_list2h等函数重新赋值后，Cython会丢失其静态类型信息，将它视为普通Python对象。此时访问cubemap.shape返回的是C语言层面的npy_intp*指针，而非Python的tuple对象，因此无法直接用len()函数处理。

修改方法 #

有两种简洁的修复方式：

方式一：使用ndim属性替代len(cubemap.shape)

ndim是numpy数组的Python属性，Cython能正确识别并处理，直接用它检查维度数量：

# 替换原assert语句
assert cubemap.ndim == 3
assert cubemap.shape[0] * 6 == cubemap.shape[1]

方式二：将shape转换为Python tuple

通过numpy.shape()函数将数组的shape转为Python tuple，再用len()检查：

# 替换原assert语句
assert len(numpy.shape(cubemap)) == 3
assert cubemap.shape[0] * 6 == cubemap.shape[1]

修改后的关键代码片段 #

if cube_format == cube_format_horizon:
        pass
    elif cube_format == cube_format_list:
        cubemap = utils.cube_list2h(cubemap)
    elif cube_format == cube_format_dict:
        cubemap = utils.cube_dict2h(cubemap)
    elif cube_format == cube_format_dice:
        cubemap = utils.cube_dice2h(cubemap)
    else:
        raise NotImplementedError('unknown cube_format')

    # 修改后的assert语句
    assert cubemap.ndim == 3
    assert cubemap.shape[0] * 6 == cubemap.shape[1]
    assert w % 8 == 0
    cdef int face_w = cubemap.shape[0]

内容的提问来源于stack exchange，提问作者Gabriel Garcia