2025年UMN数据集拆分获取

科技前沿 • 2025-03-03 23:05 • 阅读 26

大家好，我是讯享网，很高兴认识大家。

数据集为黄斑水肿分割数据，包含700+张，29个黄斑水肿受试者的眼底图像，及两组专家手动标定图像。
数据集地址：http://people.ece.umn.edu/users/parhi/.DATA/OCT/DME/
UMNDataset.mat
在这里插入图片描述
讯享网

处理UMNDataset.mat，转换成图片

#仅处理UMNDataset.mat import cv2 import scipy.io as scio import os folder = r'I:/02OCT/OCTdataset/UMN' #此文件夹下只有UMNDataset.mat一个文件 I:/02OCT/OCTdataset/UMN/UMNDataset.mat path = os.listdir(folder) srcdst = 'I:/02OCT/OCTdataset/UMNDataset/srcimg/' m1dst = 'I:/02OCT/OCTdataset/UMNDataset/manual1/' m2dst = 'I:/02OCT/OCTdataset/UMNDataset/manual2/' for each_mat in path: print(each_mat) first_name, second_name = os.path.splitext(each_mat) print('mat名',first_name) # 拆分.mat文件的前后缀名字，注意是路径 each_mat = os.path.join(folder, each_mat) array_struct = scio.loadmat(each_mat) img_data = array_struct['AllSubjects']# 原图像 row_len_out = len(img_data[0]) row_len_inner = img_data[0][0].shape[2] print(row_len_inner) for i in range(row_len_out): for j in range(row_len_inner): cv2.imwrite(srcdst + 'img' + str(i) +'index'+str(j)+ '.jpg', img_data[0][i][:, :, j]) manual1_data = array_struct['ManualFluid1'] # 标注1 row_len_out = len(manual1_data[0]) row_len_inner = manual1_data[0][0].shape[2] print(row_len_inner) for i in range(row_len_out): for j in range(row_len_inner): cv2.imwrite(m1dst + 'img' + str(i) + 'index' + str(j) + '.jpg', manual1_data[0][i][:, :, j]) manual2_data = array_struct['ManualFluid2'] # 标注2 row_len_out = len(manual2_data[0]) row_len_inner = manual2_data[0][0].shape[2] print(row_len_inner) for i in range(row_len_out): for j in range(row_len_inner): cv2.imwrite(m2dst + 'img' + str(i) + 'index' + str(j) + '.jpg', manual2_data[0][i][:, :, j])

讯享网

上面获取到的原图像可以正常显示，但是手动标记图像不能正常显示。再进行一次转换

讯享网#转换[0,1] -> [0,255] 手动标记获取 import cv2, os m1dst = 'I:/02OCT/OCTdataset/UMNDataset/manual1/' m2dst = 'I:/02OCT/OCTdataset/UMNDataset/manual2/' #print(os.listdir(r'/Users/hjy/Desktop/blues')) def changeImg(gray): H, W = gray.shape for i in range(0, W): for j in range(0, H): if gray[j, i] != 0: gray[j, i] = 255 return gray list = os.listdir(m1dst) for i in list: print(i) img1 = cv2.imread(m1dst+i,0) img2 = cv2.imread(m2dst+i,0) img1 = changeImg(img1) img2 = changeImg(img2) cv2.imwrite(m1dst+i,img1) cv2.imwrite(m2dst+i,img2)

2025年UMN数据集拆分获取

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