opencv GrabCut 算法进行交互式前景提取

前后景分割

import cv2
import numpy as np
from matplotlib import pyplot as plt


def cv_show(neme, img):
    # cv2.namedWindow(neme, cv2.WINDOW_NORMAL)
    cv2.imshow(neme, img)
    cv2.waitKey(0)
    cv2.destroyAllWindows()


# 矩形框 前后景分割
img = cv2.imread('1.jpg')
mask = np.zeros(img.shape[:2], np.uint8)
bgdModel = np.zeros((1, 65), np.float64)
fgdModel = np.zeros((1, 65), np.float64)
rect = (50, 50, 450, 290)
# 参数：图像、掩膜图像、（前景矩形x y w h）
# 算法内部使用的数组. 你只需要创建两个大小为 (1,65)，数据类型为 np.float64 的数组。
# 算法迭代次数
# 可以设置为 cv2.GC_INIT_WITH_RECT 或 cv2.GC_INIT_WITH_MASK，也可以联合使用。这是用来确定我们进行修改的方式，矩形模式或者掩模模式。
cv2.grabCut(img, mask, rect, bgdModel, fgdModel, 5, cv2.GC_INIT_WITH_RECT)
mask2 = np.where((mask == 2) | (mask == 0), 0, 1).astype('uint8')
img = img * mask2[:, :, np.newaxis]

# cv_show("s", img)
plt.imshow(img), plt.colorbar(), plt.show()

注意：这里的掩膜是要事先处理好的

# 掩膜 前后景分割
# 掩膜图像 二值图
newmask = cv2.imread('1_1.jpg', 0)
# whereever it is marked white (sure foreground), change mask=1
# whereever it is marked black (sure background), change mask=0
mask[newmask == 0] = 0
mask[newmask == 255] = 1
mask, bgdModel, fgdModel = cv2.grabCut(img, mask, None, bgdModel, fgdModel, 5, cv2.GC_INIT_WITH_MASK)
mask = np.where((mask == 2) | (mask == 0), 0, 1).astype('uint8')
img = img * mask[:, :, np.newaxis]
plt.imshow(img), plt.colorbar(), plt.show()

手动前后景分割

# -*- coding:utf-8 -*-

'''
  Python: 3.8
  opencv 4.5.5

  在图上用鼠标左键和右键标记前景和后景即可.
  如果需要重新标记图像,关闭程序重新运行.
  By Ynxf http://www.zhouws.com
'''

import cv2
import numpy as np
import time

img_src = 'fen_.jpg'

drawing = False
mode = False


class GrabCut:
    def __init__(self, t_img):
        self.img = t_img
        self.img_raw = img.copy()
        self.img_width = img.shape[0]
        self.img_height = img.shape[1]
        self.scale_size = 640 * self.img_width // self.img_height
        if self.img_width > 640:
            self.img = cv2.resize(self.img, (640, self.scale_size), interpolation=cv2.INTER_AREA)
        self.img_show = self.img.copy()
        self.img_gc = self.img.copy()
        self.img_gc = cv2.GaussianBlur(self.img_gc, (3, 3), 0)
        self.lb_up = False
        self.rb_up = False
        self.lb_down = False
        self.rb_down = False
        self.mask = np.full(self.img.shape[:2], 2, dtype=np.uint8)
        self.firt_choose = True


# 鼠标的回调函数
def mouse_event2(event, x, y, flags, param):
    global drawing, last_point, start_point
    # 左键按下：开始画图
    if event == cv2.EVENT_LBUTTONDOWN:
        drawing = True
        last_point = (x, y)
        start_point = last_point
        param.lb_down = True
        print('mouse lb down')
    elif event == cv2.EVENT_RBUTTONDOWN:
        drawing = True
        last_point = (x, y)
        start_point = last_point
        param.rb_down = True
        print('mouse rb down')
    # 鼠标移动，画图
    elif event == cv2.EVENT_MOUSEMOVE:
        if drawing:
            if param.lb_down:
                cv2.line(param.img_show, last_point, (x, y), (0, 0, 255), 2, -1)
                cv2.rectangle(param.mask, last_point, (x, y), 1, -1, 4)
            else:
                cv2.line(param.img_show, last_point, (x, y), (255, 0, 0), 2, -1)
                cv2.rectangle(param.mask, last_point, (x, y), 0, -1, 4)
            last_point = (x, y)
    # 左键释放：结束画图
    elif event == cv2.EVENT_LBUTTONUP:
        drawing = False
        param.lb_up = True
        param.lb_down = False
        cv2.line(param.img_show, last_point, (x, y), (0, 0, 255), 2, -1)
        if param.firt_choose:
            param.firt_choose = False
        cv2.rectangle(param.mask, last_point, (x, y), 1, -1, 4)
        print('mouse lb up')
    elif event == cv2.EVENT_RBUTTONUP:
        drawing = False
        param.rb_up = True
        param.rb_down = False
        cv2.line(param.img_show, last_point, (x, y), (255, 0, 0), 2, -1)
        if param.firt_choose:
            param.firt_choose = False
            param.mask = np.full(param.img.shape[:2], 3, dtype=np.uint8)
        cv2.rectangle(param.mask, last_point, (x, y), 0, -1, 4)
        print('mouse rb up')


if __name__ == '__main__':
    img = cv2.imread(img_src)
    if img is None:
        print('error: 图像为空')
    g_img = GrabCut(img)

    cv2.namedWindow('image')
    # 定义鼠标的回调函数
    cv2.setMouseCallback('image', mouse_event2, g_img)
    while (True):
        cv2.imshow('image', g_img.img_show)
        if g_img.lb_up or g_img.rb_up:
            g_img.lb_up = False
            g_img.rb_up = False
            start = time.process_time()
            bgdModel = np.zeros((1, 65), np.float64)
            fgdModel = np.zeros((1, 65), np.float64)

            rect = (1, 1, g_img.img.shape[1], g_img.img.shape[0])
            print(g_img.mask)
            mask = g_img.mask
            g_img.img_gc = g_img.img.copy()
            cv2.grabCut(g_img.img_gc, mask, rect, bgdModel, fgdModel, 5, cv2.GC_INIT_WITH_MASK)
            elapsed = (time.process_time() - start)
            mask2 = np.where((mask == 2) | (mask == 0), 0, 1).astype('uint8')  # 0和2做背景
            g_img.img_gc = g_img.img_gc * mask2[:, :, np.newaxis]  # 使用蒙板来获取前景区域
            cv2.imshow('result', g_img.img_gc)

            print("Time used:", elapsed)

        # 按下ESC键退出
        if cv2.waitKey(20) == 27:
            break