【py】提取掩膜的矩形区域

import cv2
import numpy as np
import matplotlib.pyplot as plt
image = cv2.imread('1.png')

img = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
ret, thresh = cv2.threshold(img, 230, 255, cv2.THRESH_BINARY_INV)
contours, hierarchy = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)

for c in contours:
    # 找到边界坐标
    x, y, w, h = cv2.boundingRect(c)  # 计算点集最外面的矩形边界
    if x==0 and y==0 and w==img.shape[1] and h==img.shape[0]:
        continue
    # cv2.rectangle(image, (x, y), (x+w, y+h), (0, 255, 0), 5)

    # # 找面积最小的矩形
    # rect = cv2.minAreaRect(c)
    # # 得到最小矩形的坐标
    # box = cv2.boxPoints(rect)
    # # 标准化坐标到整数
    # box = np.int0(box)
    # # 画出边界
    # cv2.drawContours(image, [box], 0, (0, 0, 255), 5)
img1=image[y:y+h,x:x+w]
plt.imshow(img1)
plt.axis('off')
cv2.imwrite("img_1.jpg", img1)

# 绘制 loss 曲线
# train_loss = [0.5, 0.4, 0.3, 0.2, 0.1]
# plt.plot(train_loss, label='train loss')
# plt.legend()
# plt.xlabel('Epoch')# plt.ylabel('Loss')
# plt.show()