What Does Col[: ,: , Y, X, :, :] Mean in Numpy

I am learning to write Convolution Neural Network with python, numpy.

I'm quite frustrated about the line

col[:, :, y, x, :, :] = images[:, :, y:y_bound:stride[0], x:x_bound:stride[1]]

I don't understand what's mean of both sides of '=', and why there are different ',' number beteen left and right side.

Full code

[comes from ]

def image_to_column(images, filter_shape, stride, padding):
    """Rearrange image blocks into columns.

    Parameters
    ----------

    filter_shape : tuple(height, width)
    images : np.array, shape (n_images, n_channels, height, width)
    padding: tuple(height, width)
    stride : tuple (height, width)

    """
    n_images, n_channels, height, width = images.shape
    f_height, f_width = filter_shape
    out_height, out_width = convoltuion_shape(height, width, (f_height, f_width), stride, padding)
    images = np.pad(images, ((0, 0), (0, 0), padding, padding), mode='constant')

    col = np.zeros((n_images, n_channels, f_height, f_width, out_height, out_width))
    for y in range(f_height):
        y_bound = y + stride[0] * out_height
        for x in range(f_width):
            x_bound = x + stride[1] * out_width
            col[:, :, y, x, :, :] = images[:, :, y:y_bound:stride[0], x:x_bound:stride[1]]

    col = col.transpose(0, 4, 5, 1, 2, 3).reshape(n_images * out_height * out_width, -1)
    return col

Thank you very much !