代码实现最佳缝合线算法

最佳缝合线算法（Seam Carving）是一种图像处理算法，用于在保持图像宽高比的情况下，缩小或扩大图像的大小。

以下是实现最佳缝合线算法的代码：

1. 计算能量值

import numpy as np
import cv2

def energy(image):
    gray = cv2.cvtColor(image, 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)

2. 计算最小能量路径

def find_seam(image):
    e = energy(image)
    m = np.zeros_like(e)
    m[0] = e[0]
    for i in range(1, m.shape[0]):
        for j in range(m.shape[1]):
            if j == 0:
                m[i][j] = e[i][j] + min(m[i-1][j], m[i-1][j+1])
            elif j == m.shape[1]-1:
                m[i][j] = e[i][j] + min(m[i-1][j], m[i-1][j-1])
            else:
                m[i][j] = e[i][j] + min(m[i-1][j-1], m[i-1][j], m[i-1][j+1])
    seam = []
    j = np.argmin(m[-1])
    seam.append((len(e)-1, j))
    for i in reversed(range(len(e)-1)):
        if j == 0:
            j = np.argmin(m[i][j:j+2])
        elif j == m.shape[1]-1:
            j = np.argmin(m[i][j-1:j+1]) + j - 1
        else:
            j = np.argmin(m[i][j-1:j+2]) + j - 1
        seam.append((i, j))
    return seam[::-1]

3. 删除最小能量路径

def remove_seam(image, seam):
    h, w = image.shape[:2]
    mask = np.ones((h, w), dtype=np.bool)
    for i, j in seam:
        mask[i, j] = False
    return image[mask].reshape((h, w-1, 3))

4. 缩小图像

def resize(image, size):
    h, w = image.shape[:2]
    dy, dx = h - size[1], w - size[0]
    if dx > 0:
        for i in range(dx):
            seam = find_seam(image)
            image = remove_seam(image, seam)
    if dy > 0:
        image = np.rot90(image, 1, (0, 1))
        for i in range(dy):
            seam = find_seam(image)
            image = remove_seam(image, seam)
        image = np.rot90(image, 3, (0, 1))
    return image

上述代码实现了最佳缝合线算法，可以通过调用 `resize` 函数对图片进行缩放。