import cv2
import numpy as np
def get_leave_areas(image):
img = cv2.imread(image)
GrayImage = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
ret, threshed_img = cv2.threshold(GrayImage, 160, 255,cv2.THRESH_BINARY) # 二值化, 阈值偏高
image, contours, hierarchy = cv2.findContours(threshed_img, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE) # 注意OpenCV3中, findContours的返回参数成了三个
small_areas = [i for i in contours if cv2.contourArea(i) < 200] # 去除小面积的(通常为干扰)
cv2.fillPoly(threshed_img, small_areas, 255)
# 统计
area_pixel = 0
for i in np.array(threshed_img).flatten():
if i == 0:
area_pixel += 1
area_inch = area_pixel / (96 * 96) # 除以dpi, 算出实际生活中的面积
return area_inch
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