当前位置:网站首页>Use load_ decathlon_ Datalist (Monai) fast loading JSON data
Use load_ decathlon_ Datalist (Monai) fast loading JSON data
2022-07-07 10:37:00 【Sister Tina】
reflection : When you have a data that contains all the information JSON When you file , How to load into MONAI Inside the frame ?
As shown in the figure , From this json You can know the data in the file label Information , The true meaning of each category . And its mode is CT, Image is 3D And put the training set 、 The address of the image included in the verification set and the test connection is written .
We can feed the data to the model through this file .
stay MONAI It does provide loading json How to format data . Very convenient .
Empathy , We can write our own data as json Format loading .
This tutorial will cover these two contents , If you are interested, let's have a look
load_decathlon_datalist
Load data
Where to call ?
from monai.data import load_decathlon_datalist
Function parameter
load_decathlon_datalist(data_list_file_path: PathLike,is_segmentation: bool = True, data_list_key: str = “training”, base_dir: Optional[PathLike] = None,)
Args:
- data_list_file_path: the path to the json file of datalist. Yours json File address
- is_segmentation: whether the datalist is for segmentation task, default is True. Whether it is a split task
- data_list_key: the key to get a list of dictionary to be used, default is “training”. Which data set do you want to load (traning, validation, test), there key It's worth it json The name of the corresponding dataset in the file ( Look at the picture above ).
- base_dir: the base directory of the dataset, if None, use the datalist directory. Home directory of data . You can know from the picture , The address of the data is from imagesTs/imagesTr/labelsTr At the beginning . And the upper level address of these addresses needs to be provided . If you don't fill in , Default and json The files are in the same directory .
Demo sample :
I am here tested.py
Load data in the file
from monai.data import load_decathlon_datalist
data_dir = "dataset/dataset.json"
datalist = load_decathlon_datalist(data_dir, True, "training
# datalist = load_decathlon_datalist(data_dir, True, "training", 'dataset') add base_dir
such , accord with MONAI data Your dictionary will be created .
We can see , To have this json file , We can easily create data .
Next , Let's see how to create this json file
Create data json file
from collections import OrderedDict
import json
json_dict = OrderedDict()
json_dict['name'] = "your task"
json_dict['description'] = "btcv yucheng"
json_dict['tensorImageSize'] = "3D"
json_dict['reference'] = "see challenge website"
json_dict['licence'] = "see challenge website"
json_dict['release'] = "0.0"
json_dict['modality'] = {
"0": "CT",
}
json_dict['test'] = [
"imagesTs/img0061.nii.gz",
"imagesTs/img0062.nii.gz",
"imagesTs/img0063.nii.gz",
"imagesTs/img0064.nii.gz",
"imagesTs/img0065.nii.gz",
"imagesTs/img0066.nii.gz"] # Write in the list containing the data .
# What information do you want to save , stay json_dict Add a dictionary data inside
# preservation json
with open(os.path.join(out_base, "dataset.json"), 'w') as f:
json.dump(json_dict, f, indent=4, separators=(',', ': '))
Articles are constantly updated , You can pay attention to the official account of WeChat 【 Medical image AI combat camp 】 Get the latest , The official account of the frontier technology in the field of medical image processing . Stick to the practice , Take you hand in hand to do the project , Play the game , Write a paper . All original articles provide theoretical explanation , Experimental code , experimental data . Only practice can grow faster , Pay attention to our , Learn together ~
I am a Tina, I'll see you on our next blog ~
Working during the day and writing at night , cough
If you think it's well written, finally , Please thumb up , Comment on , Collection . Or three times with one click
边栏推荐
- Leetcode-304: two dimensional area and retrieval - matrix immutable
- 小程序跳转H5,配置业务域名经验教程
- CSAPP Bomb Lab 解析
- 深入分析ERC-4907协议的主要内容,思考此协议对NFT市场流动性意义!
- XML configuration file parsing and modeling
- Common shortcut keys in IDA
- Pre knowledge reserve of TS type gymnastics to become an excellent TS gymnastics master
- Application of OpenGL gllightfv function and related knowledge of light source
- Trajectory planning for multi robot systems: methods and Applications Overview reading notes
- OpenGL glLightfv 函数的应用以及光源的相关知识
猜你喜欢
[higherhrnet] higherhrnet detailed heat map regression code of higherhrnet
Leetcode-304: two dimensional area and retrieval - matrix immutable
[système recommandé 01] rechub
php \n 换行无法输出
[牛客网刷题 Day5] JZ77 按之字形顺序打印二叉树
1324:【例6.6】整数区间
IIC Basics
P1031 [NOIP2002 提高组] 均分纸牌
Yarn的基础介绍以及job的提交流程
Find the greatest common divisor and the least common multiple (C language)
随机推荐
浅谈日志中的返回格式封装格式处理,异常处理
Multisim--软件相关使用技巧
Hdu-2196 tree DP learning notes
Pre knowledge reserve of TS type gymnastics to become an excellent TS gymnastics master
5个chrome简单实用的日常开发功能详解,赶快解锁让你提升更多效率!
BUUCTF---Reverse---reverse1
【STM32】STM32烧录程序后SWD无法识别器件的问题解决方法
SQL Server 知识汇集11 : 约束
@Transcation的配置,使用,原理注意事项:
Adb 实用命令(网络包、日志、调优相关)
宁愿把简单的问题说一百遍,也不把复杂的问题做一遍
String formatting
根据设备信息进行页面跳转至移动端页面或者PC端页面
I'd rather say simple problems a hundred times than do complex problems once
深入分析ERC-4907协议的主要内容,思考此协议对NFT市场流动性意义!
1324: [example 6.6] integer interval
[homework] 2022.7.6 write your own cal function
【推荐系统 01】Rechub
[daiy5] jz77 print binary tree in zigzag order
原型与原型链