研究生课题需要所以写了一个:
import numpy as np from PIL import Image import skimage.io #把图片二值化 def binaryzation(pic_id, new_id): img = Image.open(pic_id) img = img.convert("L") imgs = skimage.io.imread(pic_id) ttt = 1.4 * np.mean(imgs) WHITE, BLACK = 255, 0 img = img.point(lambda x: WHITE if x > ttt else BLACK) img = img.convert('1') img.save(new_id) #计算菌斑面积占比 def zone_cal(new_id): imgs = skimage.io.imread(new_id) a = imgs.tolist() b = w = 0 for j in a: for l in j: if l <= 125: b += 1 else: w += 1 fungi_percent = w / (w + b) return fungi_percent #print(fungi_percent, w, b) before = after = 0 for x in range(1, 4): binaryzation('d:/p/hx-'+str(x)+'.jpg', 'd:/p/hx-'+str(x)+'2值.jpg') before += zone_cal('d:/p/hx-'+str(x)+'2值.jpg') for x in range(4, 7): binaryzation('d:/p/hx-'+str(x)+'.jpg', 'd:/p/hx-'+str(x)+'2值.jpg') after += zone_cal('d:/p/hx-'+str(x)+'2值.jpg') before /= 3 after /= 3 print(before, after)
'''
0.27155324073124204 0.11879577511345958
'''
网上用matlab做的比较多,原理也很清楚,就不多说了。没有处理噪声,细节也损失的比较多。