python语言的最佳缝合算法代码。

最佳缝合算法（Best Seam Carving）是一种图像处理算法，用于调整图像的大小，同时最小化对图像内容的影响。下面是Python语言的最佳缝合算法代码：

import numpy as np
import cv2

def calc_energy(img):
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    sobel_x = cv2.Sobel(gray, cv2.CV_64F, 1, 0, ksize=3)
    sobel_y = cv2.Sobel(gray, cv2.CV_64F, 0, 1, ksize=3)
    return np.abs(sobel_x) + np.abs(sobel_y)

def find_seam(img, energy):
    rows, cols = img.shape[:2]
    dp = np.zeros((rows, cols))
    dp[0] = energy[0]
    for i in range(1, rows):
        for j in range(cols):
            if j == 0:
                dp[i][j] = energy[i][j] + min(dp[i-1][j], dp[i-1][j+1])
            elif j == cols - 1:
                dp[i][j] = energy[i][j] + min(dp[i-1][j], dp[i-1][j-1])
            else:
                dp[i][j] = energy[i][j] + min(dp[i-1][j-1], dp[i-1][j], dp[i-1][j+1])
    seam = []
    j = np.argmin(dp[-1])
    seam.append((rows-1, j))
    for i in range(rows-2, -1, -1):
        if j == 0:
            j = np.argmin(dp[i][j:j+2])
        elif j == cols - 1:
            j = np.argmin(dp[i][j-1:j+1]) + j - 1
        else:
            j = np.argmin(dp[i][j-1:j+2]) + j - 1
        seam.append((i, j))
    return seam[::-1]

def remove_seam(img, seam):
    rows, cols = img.shape[:2]
    mask = np.ones((rows, cols-1), dtype=np.bool)
    for row, col in seam:
        mask[row, :col] &= False
        mask[row, col:-1] = mask[row, col+1:]
    return img[mask].reshape((rows, cols-1, 3))

def resize(img, width, height):
    for i in range(img.shape[0] - height):
        energy = calc_energy(img)
        seam = find_seam(img, energy)
        img = remove_seam(img, seam)
    img = cv2.transpose(img)
    for i in range(img.shape[0] - width):
        energy = calc_energy(img)
        seam = find_seam(img, energy)
        img = remove_seam(img, seam)
    img = cv2.transpose(img)
    img = cv2.resize(img, (width, height))
    return img

其中，`calc_energy`函数用于计算图像的能量矩阵，`find_seam`函数用于找到最佳缝合线，`remove_seam`函数用于删除最佳缝合线，`resize`函数用于调整图像的大小。