Question

我目前正在尝试将图像从 .mat 文件转换为从该网站-BrainTumorDataset下载的 .jpg 文件。目录中包含的所有文件都是 .mat 文件，现在我想通过python转换所有 .jpg 格式的文件以创建一个项目（使用Deep进行脑肿瘤分类神经网络）通过CNN。我在google中搜索，但后来从那里什么也没得到，只有一些有关如何在python中加载.mat文件的主题，但这也无济于事。我在StackOverflow中找到了一个answer，但这不适用于该数据集，答案是要在python中加载.mat图像，但我想在中转换 .mat 图像.jpg 格式。

Answer 1

我设法转换了一张图像，使用循环转换了全部图像。

请阅读评论。

import matplotlib.pyplot as plt
import numpy as np
import h5py
from PIL import Image

#reading v 7.3 mat file in python
#https://stackoverflow.com/questions/17316880/reading-v-7-3-mat-file-in-python

filepath = '1.mat';
f = h5py.File(filepath, 'r') #Open mat file for reading

#In MATLAB the data is arranged as follows:
#cjdata is a MATLAB struct
#cjdata.image is a matrix of type int16

#Before update: read only image data.   
####################################################################
#Read cjdata struct, get image member and convert numpy ndarray of type float
#image = np.array(f['cjdata'].get('image')).astype(np.float64) #In MATLAB: image = cjdata.image
#f.close()
####################################################################

#Update: Read all elements of cjdata struct
####################################################################
#Read cjdata struct
cjdata = f['cjdata'] #<HDF5 group "/cjdata" (5 members)>

# In MATLAB cjdata = 
# struct with fields:
#   label: 1
#   PID: '100360'
#   image: [512×512 int16]
#   tumorBorder: [38×1 double]
#   tumorMask: [512×512 logical]

#get image member and convert numpy ndarray of type float
image = np.array(cjdata.get('image')).astype(np.float64) #In MATLAB: image = cjdata.image

label = cjdata.get('label')[0,0] #Use [0,0] indexing in order to convert lable to scalar

PID = cjdata.get('PID') # <HDF5 dataset "PID": shape (6, 1), type "<u2">
PID = ''.join(chr(c) for c in PID) #Convert to string https://stackoverflow.com/questions/12036304/loading-hdf5-matlab-strings-into-python

tumorBorder = np.array(cjdata.get('tumorBorder'))[0] #Use [0] indexing - convert from 2D array to 1D array.

tumorMask = np.array(cjdata.get('tumorMask'))

f.close()
####################################################################

#Convert image to uint8 (before saving as jpeg - jpeg doesn't support int16 format).
#Use simple linear conversion: subtract minimum, and divide by range.
#Note: the conversion is not optimal - you should find a better way.
#Multiply by 255 to set values in uint8 range [0, 255], and covert to type uint8.
hi = np.max(image)
lo = np.min(image)
image = (((image - lo)/(hi-lo))*255).astype(np.uint8)

#Save as jpeg
#https://stackoverflow.com/questions/902761/saving-a-numpy-array-as-an-image
im = Image.fromarray(image)
im.save("1.jpg")

#Display image for testing
imgplot = plt.imshow(image)
plt.show()

注意：
每个mat文件都包含一个名为cjdata的结构。
cjdata结构的字段：

cjdata = 

struct with fields:

      label: 1
        PID: '100360'
      image: [512×512 int16]
tumorBorder: [38×1 double]
  tumorMask: [512×512 logical]

将图像转换为jpeg时，您正在丢失信息...

Answer 2

在这里，您可以使用循环来转换所有图像。

from os import path
import os
from matplotlib import pyplot as plt
import numpy as np
import h5py
from PIL import Image
import re
import sys
from glob import glob


dir_path = path.dirname(path.abspath(__file__))
path_to_mat_files = path.join(dir_path, "*.mat")
found_files = glob(path_to_mat_files, recursive=True)
total_files = 0


def convert_to_png(file: str, number: int):
    global total_files
    if path.exists(file):
        print(file, "already exist\nSkipping...")
    else:
        h5_file = h5py.File(file, 'r')
        png = file[:-3] + "png"
        cjdata = h5_file['cjdata']
        image = np.array(cjdata.get('image')).astype(np.float64)
        label = cjdata.get('label')[0,0]
        PID = cjdata.get('PID')
        PID = ''.join(chr(c) for c in PID)
        tumorBorder = np.array(cjdata.get('tumorBorder'))[0]
        tumorMask = np.array(cjdata.get('tumorMask'))
        h5_file.close()
        hi = np.max(image)
        lo = np.min(image)
        image = (((image - lo)/(hi-lo))*255).astype(np.uint8)
        im = Image.fromarray(image)
        im.save(png)
        os.system(f"mv {png} {dir_path}\\png_images")#make sure folder png_images exist
        total_files += 1
        print("saving", png, "File No: ", number)
        
for file in found_files:
    if "cvind.mat" in file:
        continue
    convert_to_png(file, total_files)
print("Finished converting all files: ", total_files)

通过python

2 个答案: