Cupy - TypeError: Unsupported type <type 'numpy.ndarray'>-CodePudding

I want to try cupy for image exposure fusion process because we use a lot of numpy in algorithms. The following code parts shows the functions and lines that causes errors.

image_stack is a list of images that have different exposures. The code for creating image_stack is:

def load_images(path, mode='color'):
    """
   FUNCTION: load_images
        Call to load images colored or grayscale and stack them. 
     INPUTS:
        path = location of image
        mode = 'grayscale' or 'colored'
    OUTPUTS:
        read data file
    """

    image_stack = []; i = 0
    for filename in os.listdir(path):
        print("Loading... /"   filename   "...as Image_stack[" str(i) "]")
        if mode == 'color':
            image = cv2.imread(os.path.join(path, filename), cv2.IMREAD_COLOR)
        else: #mode == 'gray':
            image = cv2.imread(os.path.join(path, filename), cv2.IMREAD_GRAYSCALE)
        image_stack.append(cv2.resize(image,(864,576), interpolation = cv2.INTER_AREA))
        #image_stack.append(image)
        i  = 1
    print("\n")
    return image_stack

The function below supposed to calculate scalar weight map based on mathematical approach. I directly changed import numpy as np to import cupy as np. However, I faced an issue from this function.

def scalar_weight_map(image_stack, weights=[1,1,1]):

"""
 FUNCTION: scalar_weight_map
    Call to forcefully "AND"-combine all quality measures defined 
 INPUTS:
    image_measures = stack of quality measures computed for image i 
    image_measures[contrast, saturation, exposedness]
    weights = weight for each quality measure : weights[wc, ws, we]
 OUTPUTS:
    scalar_weight_map for particular image
"""

H = np.shape(image_stack[0])[0]; 
W = np.shape(image_stack[0])[1]; 
D = len(image_stack);
Wijk = np.zeros((H,W,D), dtype='float64')
wc = weights[0]
ws = weights[1]
we = weights[2]
print("Computing Weight Maps from Measures using: C=%1.1d, S=%1.1d, E=%1.1d" %(wc,ws,we))

epsilon = 0.000005
for i in range(D):
    C  = contrast(image_stack[i])
    S  = saturation(image_stack[i])
    E  = exposedness(image_stack[i])
    Wijk[:,:,i] = (np.power(C,wc)*np.power(S,ws)*np.power(E,we))   epsilon
normalizer = np.sum(Wijk,2)

for i in range(D):
    Wijk[:,:,i] = np.divide(Wijk[:,:,i], normalizer)
print(" *Done");print("\n")

return Wijk.astype('float64')

And the lambda function that causes error from the below function:

def exposedness(image, sigma=0.2):
    """
   FUNCTION: exposedness
        Call to compute third quality measure - exposure using a gaussian curve
     INPUTS:
        image = input image (colored)
        sigma = gaussian curve parameter
    OUTPUTS:
        exposedness measure
    """

    image = cv2.normalize(image, None, alpha=0.0, beta=1.0, norm_type=cv2.NORM_MINMAX, dtype=cv2.CV_64F)
    gauss_curve = lambda i : np.exp(-((i-0.5)**2) / (2*sigma*sigma))
    R_gauss_curve = gauss_curve(image[:,:,2])
    G_gauss_curve = gauss_curve(image[:,:,1])
    B_gauss_curve = gauss_curve(image[:,:,0])
    E = R_gauss_curve * G_gauss_curve * B_gauss_curve
    return E.astype('float64')

The error I faced:

Traceback (most recent call last):
  File "C:\Users\ar\Desktop\Ab\exposure_\exposure_fusion-master\Main.py", line 36, in <module>
    weight_map      = ef.scalar_weight_map(image_stack, weights = [1,1,1])
  File "C:\Users\ar\Desktop\Ab\exposure_\exposure_fusion-master\exposureFusion_.py", line 202, in scalar_weight_map
    E  = exposedness(image_stack[i])
  File "C:\Users\ar\Desktop\Ab\exposure_\exposure_fusion-master\exposureFusion_.py", line 163, in exposedness
    R_gauss_curve = gauss_curve(image[:,:,2])
  File "C:\Users\ar\Desktop\Ab\exposure_\exposure_fusion-master\exposureFusion_.py", line 162, in <lambda>
    gauss_curve = lambda i : np.exp(-((i-0.5)**2) / (2*sigma*sigma))
  File "cupy\_core\_kernel.pyx", line 1222, in cupy._core._kernel.ufunc.__call__
  File "cupy\_core\_kernel.pyx", line 138, in cupy._core._kernel._preprocess_args
  File "cupy\_core\_kernel.pyx", line 124, in cupy._core._kernel._preprocess_arg
TypeError: Unsupported type <class 'numpy.ndarray'>

I would be grateful for any help. Thanks in advance!

CodePudding user response：

This is because you are passing numpy.ndarray (data on CPU memory) to CuPy. CuPy only accepts cupy.ndarray (data on GPU memory), so you need to convert image to cupy.ndarray before using gauss_curve.