OpenCV上的图割

import cv2
import numpy as np

# 读取图像
image = cv2.imread('input.jpg')
height, width = image.shape[:2]

# 创建图
g = cv2.cuda_Graph()
nodes = g.createNodes(height * width)

# 添加边
for y in range(height):
    for x in range(width):
        if x < width - 1:
            g.addEdge(nodes[y * width + x], nodes[y * width + x + 1], 1.0, 1.0)
        if y < height - 1:
            g.addEdge(nodes[y * width + x], nodes[(y + 1) * width + x], 1.0, 1.0)

# 设置源点和汇点
source = g.createNode()
sink = g.createNode()
g.addNode(source)
g.addNode(sink)

# 添加源点到前景节点的边
for y in range(height):
    for x in range(width):
        if image[y, x, 0] > 128:  # 假设前景像素的蓝色通道值大于128
            g.addEdge(source, nodes[y * width + x], 1.0, 0.0)

# 添加背景节点到汇点的边
for y in range(height):
    for x in range(width):
        if image[y, x, 0] <= 128:  # 假设背景像素的蓝色通道值小于等于128
            g.addEdge(nodes[y * width + x], sink, 0.0, 1.0)

# 运行图割算法
g.flow(1000, 1000)

# 获取分割结果
result = np.zeros((height, width), dtype=np.uint8)
for y in range(height):
    for x in range(width):
        result[y, x] = 255 if g.getFlow(nodes[y * width + x]) > 0 else 0

# 显示结果
cv2.imshow('Segmentation Result', result)
cv2.waitKey(0)
cv2.destroyAllWindows()