将浮点数与数组中的值进行比较时，“类型错误：只有整数标量数组才能转换为标量索引”

如何解决将浮点数与数组中的值进行比较时，“类型错误：只有整数标量数组才能转换为标量索引”

当我尝试运行以下非最大值抑制函数时，我在将 -22.5 与 Gmat[i,j] 进行比较的行中收到错误：

我使用 np.all 和 np.any 作为 and 和 or 会给出一个错误，称为“ValueError：具有多个元素的数组的真值是不明确的。使用 a.any() 或 a.all()'

def non_max_suppression(Gmag,Gmat):
   nms_img = np.zeros(Gmag.shape)
   for i in range (1,int(Gmag.shape[0])-1):
       for j in range (1,int(Gmag.shape[1])-1):
           if np.any(
                   np.all(
                       Gmat[i,j] >=
                       -22.5,Gmat[i,j] <=
                       22.5),#doesnt go past here,this is where the error occurs
                   np.all(Gmat[i,j] <= -157.5,j] >= 157.5)
           ):
               if np.logical_and(Gmag[i,j] > Gmag[i,j+1],Gmag[i,j-1]):
                   nms_img[i,j] = Gmag[i,j]
               else:
                   nms_img[i,j] = 0

           if np.logical_or(
                   np.logical_and(Gmat[i,j] >= 22.5,j] <= 67.5),np.logical_and(Gmat[i,j] <= -112.5,j] >= -157.5)
           ):
               if np.logical_and(Gmag[i,j] > Gmag[i+1,j],j] > Gmag[i-1,j] >= 67.5,j] <= 112.5),j] <= -67.5,j] >= -112.5)
           ):
               if np.logical_and(Gmag[i,j]):
                   nms_img[i,j] >= 112.5,j] <= 157.5),j] <= -22.5,j] >= -67.5)
           ):
               if np.logical_and(Gmag[i,j+1]):
                   nms_img[i,j] = 0
   return nms_img

Gmag 和 Gmat 的值分别如下：

 Mag = {ndarray: (262,393,3)} [[[0. 0. 0.],[0. 0. 0.],...,[0. 0. 0.]],[[0. 0. 0.],[0. 0. 0.]]
 min = {float64} 0.0
 max = {float64} 1.7116336200484585
 shape = {tuple: 3} (262,3)
 dtype = {dtype: 0} float64
 size = {int} 308898
 array = {ndarrayItemsContainer} <pydevd_plugins.extensions.types.pydevd_plugin_numpy_types.ndarrayItemsContainer object at 0x00000275D41FAC08>

 Gmat = {ndarray: (262,[0. 0. 0.]]
 min = {float64} -135.0
 max = {float64} 45.0
 shape = {tuple: 3} (262,3)
 dtype = {dtype: 0} float64
 size = {int} 308898
 array = {ndarrayItemsContainer} <pydevd_plugins.extensions.types.pydevd_plugin_numpy_types.ndarrayItemsContainer object at 0x00000275D46BE048>

完整的错误：

TypeError                                 Traceback (most recent call last)

<ipython-input-104-991cd7244b0e> in <module>
      1 #============================ 10 Apply Non-Maximum Suppression
----> 2 img_NMS = non_max_suppression(Mag,Gmat)
      3 img_NMS = normalize(img_NMS)
      4 
      5 plt.imshow(img_NMS,cmap = plt.get_cmap('gray'))

<ipython-input-103-2ec719b48bd0> in non_max_suppression(Gmag,Gmat)
      9                         -22.5,10                         Gmat[i,j] <=
---> 11                         22.5),12                     np.all(Gmat[i,j] >= 157.5)
     13             ):

<__array_function__ internals> in all(*args,**kwargs)

c:\users\user\appdata\local\programs\python\python37\lib\site-packages\numpy\core\fromnumeric.py in all(a,axis,out,keepdims)
   2409 
   2410     
-> 2411     return _wrapreduction(a,np.logical_and,'all',None,keepdims=keepdims)
   2412 
   2413 

c:\users\user\appdata\local\programs\python\python37\lib\site-packages\numpy\core\fromnumeric.py in _wrapreduction(obj,ufunc,method,dtype,**kwargs)
     85                 return reduction(axis=axis,out=out,**passkwargs)
     86 
---> 87     return ufunc.reduce(obj,**passkwargs)
     88 
     89 

TypeError: only integer scalar arrays can be converted to a scalar index

解决方法

Gmag 本来应该是一个 2d 数组，但它却是一个 3d 数组。

将 Gmag 转换为二维数组并使用 numpy.logical_and 和 numpy.logical_or 而不是 numpy.any 和 numpy.all 解决了问题。