Question

我正在使用python为我的计算摄影课做作业。该方法需要str2，我不知道该怎么做。我试过numpy.int64，但它给了我一个未定义的全局名称。我不知道该怎么做。我得到的错误是numpy.astype(int64)。

ValueError: Error - x_locs values have type <type 'numpy.ndarray'>. Expected value type is <type 'numpy.int64'>

这是测试方法的代码，如果有帮助的话。

def getYXLocations(image, intensity_value):
    """ This function gets the Y, X locations of an image at a certain intensity
    value.

    It's easy to describe how to do this visually. Imagine you have a grayscale
    image that is 4x4.
    my_image = [ [ 17, 200,  48,  10],
                 [ 98, 151,  41, 182],
                 [128, 190,  98, 209],
                 [249,  27, 129, 182]]

    Now assume I ask you to return getYXLocations(my_image, 98)

    You have to return the y and x locations of where 98 appears, so in this
    case, 98 appears at 1, 0 and at 2, 2, so your function should return
    y_locs = [1, 2] and x_locs = [0, 2].

    Hint: There is a numpy function that will essentially allow you to do this
    efficiently & succintly. May be worth looking into ;).

    The less efficient but equally valid way of doing this:
    1. Iterate through the rows (y) and columns (x) of the image.
    2. if image[y, x] == intensity_value, append y to y_locs and x to x_locs.
    3. return y_locs, x_locs.

    Args:
        image (numpy.ndarray): Input grayscale image.
        intensity_value (numpy.uint8): Assume a value from 0->255.

    Returns:
        y_locs (numpy.ndarray): Array containing integer values for the y
                                locations of input intensity. Type np.int64.
        x_locs (numpy.ndarray): Array containing integer values for the x
                                locations of input intensity. Type np.int64.
    """
    # WRITE YOUR CODE HERE.

    # dim of the image
    dim = image.shape

    # axis
    xax = dim[1]
    yax = dim[0]

    count = 0
    # loopings for count
    for x in range (0, xax):
        for y in range (0, yax):
            if image[x][y] == intensity_value:
                count = count + 1

    # creates x loc and y loc
    x_locs = np.empty([1, count], dtype=np.int64)
    y_locs = np.empty([1, count], dtype=np.int64)

    # loops for location
    place = 0
    for x in range (0, xax):
        for y in range (0, yax):
            if image[x][y] == intensity_value:
                x_locs[0][place] = x
                y_locs[0][place] = y
                place = place + 1

    print np.array_str(x_locs)
    print np.array_str(y_locs)

    # x_locs = x_locs.astype(int64)
    # y_locs = y_locs.astype(int64)

    return x_locs, y_locs
    # END OF FUNCTION

Answer 1

我认为这个问题来自于此检查 -

if type(x_locs[0]) != type(x_ans[0]):
        raise ValueError(
            ("Error - x_locs values have type {}." +
             " Expected value type is {}.").format(type(x_locs[0]),
                                                   type(x_ans[0])))

正如您在test_answers中看到的那样，x_ans[0]的类型为np.int64，因为x_ans是一维数组。

但是当你在另一个函数中创建x_locs时，你将它创建为一个2D数组，形状为（1,10），因此当你访问x_locs[0]时，你得到一个阵列。

可能适合您的一些解决方案 -

您正在定义x_locs和y_locs，其中只有一个数组（其中有count个元素），也许您应该将它们定义为1D数组而不是2D数组（我可以看到，在你的测试函数中，你在假设它们是一维数组的情况下进行了大量的测试，但实际上并非如此）。要将它们更改为1D数组，请将以下行更改为 -
```
x_locs = np.empty([count], dtype=np.int64)
y_locs = np.empty([count], dtype=np.int64)
```
请注意，在您尝试访问阵列后，您应该使用x_locs[place]，而不是x_locs[0][place]。
另一种解决方案是纠正您的测试逻辑，将x_locs和y_locs作为2D数组处理，而不是一维数组。

数据类型是numpy.ndarray，但预计numpy.int64

1 个答案: