我需要一个Gabor变换函数

以下是一个可以实现 Gabor 变换的函数：

import numpy as np
import cv2

def gabor_transform(img, ksize, sigma, theta, lambd, gamma, psi):
    """
    Applies a Gabor filter to an image.

    Args:
        img (ndarray): Input image.
        ksize (tuple): Kernel size (width, height).
        sigma (float): Standard deviation of the Gaussian envelope.
        theta (float): Orientation of the Gabor filter in radians.
        lambd (float): Wavelength of the sinusoidal factor.
        gamma (float): Spatial aspect ratio.
        psi (float): Phase offset.

    Returns:
        ndarray: Filtered image.
    """
    ksize_half = int(ksize[0] / 2)

    # Generate kernel
    x, y = np.meshgrid(np.arange(-ksize_half, ksize_half + 1), np.arange(-ksize_half, ksize_half + 1))
    x_theta = x * np.cos(theta) + y * np.sin(theta)
    y_theta = -x * np.sin(theta) + y * np.cos(theta)
    kernel = np.exp(-0.5 * (x_theta ** 2 + gamma ** 2 * y_theta ** 2) / sigma ** 2) * np.cos(2 * np.pi * x_theta / lambd + psi)

    # Normalize kernel
    kernel = kernel - np.mean(kernel)
    kernel = kernel / np.std(kernel)

    # Apply filter
    filtered_img = cv2.filter2D(img, cv2.CV_32F, kernel)

    return filtered_img

你可以根据需要调整输入参数来进行滤波。