import numpy as np import cv2 def PSO_Gabor(func, x0, bounds, niters=100, nparticles=20, w=0.5, c1=1, c2=1): nparams = len(bounds) x = np.zeros((nparticles, nparams)) v = np.zeros_like(x) pbest = np.zeros_like(x) fitness = np.zeros(nparticles) gbest = np.zeros(nparams) gbest_fitness = np.inf for i in range(nparticles): x[i,:] = x0 + np.random.uniform(-1, 1, size=nparams) v[i,:] = np.random.uniform(-1, 1, size=nparams) pbest[i,:] = x[i,:] fitness[i] = func(x[i,:]) if fitness[i] < gbest_fitness: gbest_fitness = fitness[i] gbest = x[i,:] for _ in range(niters): for i in range(nparticles): v[i,:] = w*v[i,:] + c1*np.random.uniform(0,1,size=nparams)*(pbest[i,:] - x[i,:]) + c2*np.random.uniform(0,1,size=nparams)*(gbest - x[i,:]) x[i,:] = np.clip(x[i,:] + v[i,:], bounds[:,0], bounds[:,1]) fitness[i] = func(x[i,:]) if fitness[i] < pbest[i]: pbest[i,:] = x[i,:] if fitness[i] < gbest_fitness: gbest_fitness = fitness[i] gbest = x[i,:] return gbest def gabor_kernel(size, sigma, theta, lambd, gamma): """生成Gabor核""" kernel = cv2.getGaborKernel((size, size), sigma, theta, lambd, gamma, 0, ktype=cv2.CV_32F) return kernel def func(image, kernel): """使用Gabor核进行变换""" transformed = cv2.filter2D(image, cv2.CV_8UC3, kernel) return transformed image = cv2.imread('G:/python/python.wenjian/images/lw2.jpg', 0) best_params = PSO_Gabor(func, image, (image,2), niters=100, nparticles=20, w=0.5, c1=1, c2=1) print(gabor_kernel)这段代码哪里有问题

这段代码中存在一个问题，即在 PSO_Gabor 函数中的 x[i,:] = x0 np.random.uniform(-1, 1, size=nparams) 这行代码中，x0 后面应该加上加号，即应该是 x[i,:] = x0 + np.random.uniform(-1, 1, size=nparams)，否则代码将无法运行。