SavePath=%DEFAULT_CPY_DIR%\E:\Yakuza 0\Yakuza 0\

很抱歉，根据提供的引用内容，我无法回答你关于SavePath=%DEFAULT_CPY_DIR%\E:\Yakuza 0\Yakuza 0\的问题。这些引用内容主要是关于TensorFlow中的模型保存和恢复的函数和方法，与SavePath=%DEFAULT_CPY_DIR%\E:\Yakuza 0\Yakuza 0\无关。请提供更多相关信息或者明确你的问题，我将尽力回答。

相关问题

将代码中的import cv2模块替换掉，import os import numpy as np import nibabel as nib import imageio import cv2 def read_niifile(niifilepath): # 读取niifile文件 img = nib.load(niifilepath) # 提取niifile文件 img_fdata = img.get_fdata(dtype='float32') return img_fdata def save_fig(niifilepath, savepath, num, name): # 保存为图片 name = name.split('-')[1] filepath_seg = niifilepath + "segmentation\\" + "segmentation-" + name filepath_vol = niifilepath + "volume\\" + "volume-" +name savepath_seg = savepath + "segmentation\\" savepath_vol = savepath + "volume\\" if not os.path.exists(savepath_seg): os.makedirs(savepath_seg) if not os.path.exists(savepath_vol): os.makedirs(savepath_vol) fdata_vol = read_niifile(filepath_vol) fdata_seg = read_niifile(filepath_seg) (x, y, z) = fdata_seg.shape total = x * y for k in range(z): silce_seg = fdata_seg[:, :, k] # 三个位置表示三个不同角度的切片 if silce_seg.max() == 0: continue else: silce_seg = (silce_seg-silce_seg.min())/(silce_seg.max() - silce_seg.min())*255 silce_seg = cv2.threshold(silce_seg, 1, 255, cv2.THRESH_BINARY)[1] if (np.sum(silce_seg == 255) / total) > 0.015: silce_vol = fdata_vol[:, :, k] silce_vol = (silce_vol - silce_vol.min()) / (silce_vol.max() - silce_vol.min()) * 255 imageio.imwrite(os.path.join(savepath_seg, '{}.png'.format(num)), silce_seg) imageio.imwrite(os.path.join(savepath_vol, '{}.png'.format(num)), silce_vol) num += 1 # 将切片信息保存为png格式 return num if __name__ == '__main__': path= 'E:\\dataset\\LiTS17\\' savepath = 'E:\\dataset\\LiTS17\\2d\\' filenames = os.listdir(path + "segmentation") num = 0 for filename in filenames: num = save_fig(path, savepath, num, filename)

替后的代码如下：

import os
import numpy as np
import nibabel as nib
import imageio

def read_niifile(niifilepath):  # 读取niifile文件
    img = nib.load(niifilepath)  # 提取niifile文件
    img_fdata = img.get_fdata(dtype='float32')
    return img_fdata

def save_fig(niifilepath, savepath, num, name):  # 保存为图片
    name = name.split('-')[1]
    filepath_seg = niifilepath + "segmentation\\" + "segmentation-" + name
    filepath_vol = niifilepath + "volume\\" + "volume-" +name
    savepath_seg = savepath + "segmentation\\"
    savepath_vol = savepath + "volume\\"
    
    if not os.path.exists(savepath_seg):
        os.makedirs(savepath_seg)
    if not os.path.exists(savepath_vol):
        os.makedirs(savepath_vol)
        
    fdata_vol = read_niifile(filepath_vol)
    fdata_seg = read_niifile(filepath_seg)
    (x, y, z) = fdata_seg.shape
    total = x * y
    
    for k in range(z):
        silce_seg = fdata_seg[:, :, k]  # 三个位置表示三个不同角度的切片
        if silce_seg.max() == 0:
            continue
        else:
            silce_seg = (silce_seg-silce_seg.min())/(silce_seg.max() - silce_seg.min())*255
            silce_seg  = cv2.threshold(silce_seg, 1, 255, cv2.THRESH_BINARY)[1]
            
            if  (np.sum(silce_seg == 255) / total) > 0.015:
                silce_vol = fdata_vol[:, :, k]
                silce_vol = (silce_vol - silce_vol.min()) / (silce_vol.max() - silce_vol.min()) * 255
                
                imageio.imwrite(os.path.join(savepath_seg, '{}.png'.format(num)), silce_seg)
                imageio.imwrite(os.path.join(savepath_vol, '{}.png'.format(num)), silce_vol)
                num += 1
    
    # 将切片信息保存为png格式
    return num

if __name__ == '__main__':
    path= 'E:\\dataset\\LiTS17\\'
    savepath = 'E:\\dataset\\LiTS17\\2d\\'
    filenames = os.listdir(path + "segmentation")
    num = 0
    
    for filename in filenames:
        num = save_fig(path, savepath, num, filename)

import os import numpy as np import nibabel as nib import imageio import cv2 def read_niifile(niifilepath): # 读取niifile文件 img = nib.load(niifilepath) # 提取niifile文件 img_fdata = img.get_fdata(dtype='float32') return img_fdata def save_fig(niifilepath, savepath, num, name): # 保存为图片 name = name.split('-')[1] filepath_seg = niifilepath + "segmentation\\" + "segmentation-" + name filepath_vol = niifilepath + "volume\\" + "volume-" + name savepath_seg = savepath + "segmentation\\" savepath_vol = savepath + "volume\\" if not os.path.exists(savepath_seg): os.makedirs(savepath_seg) if not os.path.exists(savepath_vol): os.makedirs(savepath_vol) fdata_vol = read_niifile(filepath_vol) fdata_seg = read_niifile(filepath_seg) (x, y, z) = fdata_seg.shape total = x * y for k in range(z): silce_seg = fdata_seg[:, :, k] # 三个位置表示三个不同角度的切片 if silce_seg.max() == 0: continue else: silce_seg = (silce_seg - silce_seg.min()) / (silce_seg.max() - silce_seg.min()) * 255 silce_seg = cv2.threshold(silce_seg, 1, 255, cv2.THRESH_BINARY)[1] if (np.sum(silce_seg == 255) / total) > 0.015: silce_vol = fdata_vol[:, :, k] silce_vol = (silce_vol - silce_vol.min()) / (silce_vol.max() - silce_vol.min()) * 255 imageio.imwrite(os.path.join(savepath_seg, '{}.png'.format(num)), silce_seg) imageio.imwrite(os.path.join(savepath_vol, '{}.png'.format(num)), silce_vol) num += 1 # 将切片信息保存为png格式 return num if __name__ == '__main__': path = r"C:\Users\Administrator\Desktop\LiTS2017" savepath = r"C:\Users\Administrator\Desktop\2D-LiTS2017" filenames = os.listdir(path + "segmentation") num = 0 for filename in filenames: num = save_fig(path, savepath, num, filename)替换掉代码中的cv2模块，实现相同功能

可以使用Pillow模块代替cv2模块来实现相同功能。Pillow模块是Python的一个图像处理库，可以用来读取、处理和保存多格式的图片。我们只需要将cv2.threshold方法替换成Pillow.ImageOps.autocontrast()即可。

替换后的代码如下：

import os
import numpy as np
import nibabel as nib
import imageio
from PIL import Image, ImageOps

def read_niifile(niifilepath): # 读取niifile文件
img = nib.load(niifilepath) # 提取niifile文件
img_fdata = img.get_fdata(dtype='float32')
return img_fdata

def save_fig(niifilepath, savepath, num, name): # 保存为图片
name = name.split('-')[1]
filepath_seg = niifilepath + "segmentation\\" + "segmentation-" + name
filepath_vol = niifilepath + "volume\\" + "volume-" + name
savepath_seg = savepath + "segmentation\\"
savepath_vol = savepath + "volume\\"

if not os.path.exists(savepath_seg):
os.makedirs(savepath_seg)
if not os.path.exists(savepath_vol):
os.makedirs(savepath_vol)

fdata_vol = read_niifile(filepath_vol)
fdata_seg = read_niifile(filepath_seg)
(x, y, z) = fdata_seg.shape
total = x * y

for k in range(z):
silce_seg = fdata_seg[:, :, k] # 三个位置表示三个不同角度的切片
if silce_seg.max() == 0:
continue
else:
silce_seg = (silce_seg - silce_seg.min()) / (silce_seg.max() - silce_seg.min()) * 255
silce_seg = Image.fromarray(silce_seg.astype(np.uint8))
silce_seg = ImageOps.autocontrast(silce_seg, cutoff=1)

if (np.sum(silce_seg == 255) / total) > 0.015:
silce_vol = fdata_vol[:, :, k]
silce_vol = (silce_vol - silce_vol.min()) / (silce_vol.max() - silce_vol.min()) * 255
silce_vol = Image.fromarray(silce_vol.astype(np.uint8))

imageio.imwrite(os.path.join(savepath_seg, '{}.png'.format(num)), np.array(silce_seg))
imageio.imwrite(os.path.join(savepath_vol, '{}.png'.format(num)), np.array(silce_vol))
num += 1 # 将切片信息保存为png格式

return num

if __name__ == '__main__':
path = r"C:\Users\Administrator\Desktop\LiTS2017"
savepath = r"C:\Users\Administrator\Desktop\2D-LiTS2017"
filenames = os.listdir(path + "segmentation")
num = 0
for filename in filenames:
num = save_fig(path, savepath, num, filename)