===============================================================================
= JSONLab =
= An open-source MATLAB/Octave JSON encoder and decoder =
===============================================================================
* Copyright (C) 2011-2019 Qianqian Fang <q.fang at neu.edu>
* License: BSD 3-clause license, see LICENSE_BSD*.txt
* Version: 1.9.8 (Magnus - beta)
* JData Specification Version: Draft 2 (http://github.com/fangq/jdata)
* URL: http://openjdata.org/jsonlab
-------------------------------------------------------------------------------
Table of Content:
0. What's New
I. Introduction
II. Installation
III.Using JSONLab
IV. Known Issues and TODOs
V. Contribution and feedback
V. Acknowledgement
-------------------------------------------------------------------------------
0. What's New
JSONLab v1.9.8 is the beta release of the next milestone - code named "Magnus".
Starting from this release, JSONLab supports encoding/decoding MessagePack,
a widely-used binary JSON-like data format. Via ZMat v0.9, JSONLab v1.9.8
also supports LZMA/LZ4/LZ4HC data compression/decompression. More importantly,
JSONLab is now the official reference implementation for JData Specification (Draft 2)
as defined in http://github.com/fangq/jdata, the foundation for the OpenJData
Project (http://openjdata.org).
There have been numerous major updates to this toolbox since the previous
release v1.9 in May 2019. A list of the major changes are summarized below
with key features marked by *:
* 2019-10-22*[650b5ec] enable preencode by default for savejson and saveubjson
* 2019-10-21*[874945f] decode graph data, encode non-char-keyed map data
* 2019-10-18 [11712b7] add any2jd, pass opt to name check, add more options
* 2019-10-18*[f97de9b] extract name encoding/decoding to separate function, like in easyh5
* 2019-10-17*[9d0fd4a] rewrite jdataencode
* 2019-10-15 [23f14d6] minor updates to make msgpack to work on octave
* 2019-09-16*[689cb40] support lz4 and lz4hc compression via zmat v0.9
* 2019-07-11*[06d33aa] update zmat test to support zmat v0.8 mox-the-fox
* 2019-06-24*[eba4078] saving table objects with new syntax
* 2019-06-12 [3eb6d56] change ArrayCompression keywords to ArrayZip to be short
* 2019-06-12*[e5f2ffb] complete saveubjson debug mode, add compression example
* 2019-06-11 [ebbcfd2] pass formatversion tag to jdatadecode
* 2019-06-10*[95b2eb0] add jdataencode and jdatadecode
* 2019-06-10*[f86219d] major update: use row-major for N-D array, incompatible with old JSONLab
* 2019-05-31*[0c467ee] support lzma and lzip compression decompression via zmat toolbox (http://github.com/fangq/zmat)
* 2019-05-31 [599ee4c] support categorical data
* 2019-05-30*[d47be45] fast bracket matching
* 2019-05-24*[0ec2d01] rewriting fastarrayparser, 10x faster for Octave, close #4 with fast bracket matching
* 2019-05-22*[d8c19b8] add support to MessagePack, close #53, add NestArray option, close #6
* 2019-05-19*[c87e7d2] support containers.Map
Please note that JSONLab v1.9.8 is compliant with JData Spec Draft 2, while
v1.9 and previous releases are compatible with Draft 1. The main differences are
* _ArrayCompressionMethod_, _ArrayCompressionSize_</tt> and <tt>_ArrayCompressedData_</tt> \
are replaced by <tt>_ArrayZipType_``, <tt>_ArrayZipSize_</tt> and <tt>_ArrayZipData_``, respectively
* The serialization of N-D array data stored in <tt>_ArrayData_``is changed from \
column-major to row-major
To read data files generated by JSONLab v1.9 or older versions, you need to attach
option <tt>'FormatVersion', 1.9</tt> in all the loadjson/savejson function calls.
To convert an older file (JSON/UBJSON) to the new format, you should run
data=loadjson('my_old_data_file.json','FormatVersion',1.9)
savejson('',data,'FileName','new_file.json')
You are strongly encouraged to convert all previously generated data files using the new
format.
-------------------------------------------------------------------------------
I. Introduction
JSONLab is a free and open-source implementation of a JSON/UBJSON/MessagePack encoder
and a decoder in the native MATLAB language. It can be used to convert a MATLAB
data structure (array, struct, cell, struct array, cell array, and objects) into
JSON/UBJSON/MessagePack formatted strings, or to decode a
JSON/UBJSON/MessagePack file into MATLAB data structure. JSONLab supports both
MATLAB and [http://www.gnu.org/software/octave GNU Octave] (a free MATLAB clone).
JSON ([http://www.json.org/ JavaScript Object Notation]) is a highly portable,
human-readable and [http://en.wikipedia.org/wiki/JSON "fat-free"] text format
to represent complex and hierarchical data. It is as powerful as [http://en.wikipedia.org/wiki/XML XML]
but less verbose. JSON format is widely used for data-exchange in applications.
UBJSON ([http://ubjson.org/ Universal Binary JSON]) is a binary JSON format, specifically
specifically optimized for compact file size and better performance while keeping
the semantics as simple as the text-based JSON format. Using the UBJSON
format allows to wrap complex binary data in a flexible and extensible
structure, making it possible to process complex and large dataset
without accuracy loss due to text conversions. MessagePack is another binary
JSON-like data format widely used in data exchange in web/native applications.
It is slightly more compact than UBJSON, but is not directly readable compared
to UBJSON.
We envision that both JSON and its binary counterparts will play important
roles as mainstream data-exchange formats for scientific research.
It has both the flexibility and generality as offered by other popular
general-purpose file specifications, such as [http://www.hdfgroup.org/HDF5/whatishdf5.html HDF5]
but with significantly reduced complexity and excellent readability.
Towards this goal, we have developed the JData Specification (http://github.com/fangq/jdata)
to standardize serializations of complex scientific data structures, such as
N-D arrays, sparse/complex-valued arrays, trees, maps, tables and graphs using
JSON/binary JSON constructs. The text and binary formatted JData files are
syntactically compatible with JSON/UBJSON formats, and can be readily parsed
using existing JSON and UBJSON parsers.
Please note that data files produced by <tt>saveubjson</tt> may utilize a special
"optimized header" to store N-D (N>1) arrays, as defined in the JData Specification Draft 2.
This feature is not supported by UBJSON Specification Draft 12. To produce
UBJSON files that can be parsed by UBJSON-Draft-12 compliant parsers, you must
add the option <tt>'NestArray',1</tt> in the call to <tt>saveubjson``.
-------------------------------------------------------------------------------
II. Installation
The installation of JSONLab is no different from installing any other
MATLAB toolbox. You only need to download/unzip the JSONLab package
to a folder, and add the folder's path to MATLAB/Octave's path list
by using the following command:
addpath('/path/to/jsonlab');
If you want to add this path permanently, you need to type "pathtool",
browse to the zmat root folder and add to the list, then click "Save".
Then, run "rehash" in MATLAB, and type "which savejson", if you see an
output, that means JSONLab is installed for MATLAB/Octave.
If you use MATLAB in a shared environment such as a Linux server, the
best way to add path is to type
mkdir ~/matlab/
nano ~/matlab/startup.m
and type addpath('/path/to/jsonlab') in this file, save and quit the editor.
MATLAB will execute this file every time it starts. For Octave, the file
you need to edit is ~/.octaverc , where "~" is your home directory.
=== Install JSONLab on Fedora 24 or later ===
JSONLab has been available as an official Fedora package since 2015. You may
install it directly using the below command
sudo dnf install octave-jsonlab
To enable da
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matlab_基于CNN卷积神经网络的图像中水域分割matlab仿真,仿真输出训练过程以及分割结果_源码.rar (62个子文件)
matlab_基于CNN卷积神经网络的图像中水域分割matlab仿真,仿真输出训练过程以及分割结果_源码
image2.jpg 47KB
DataMark.m 1KB
image2.json 61KB
image1.json 20.84MB
image_label.mat 154KB
jsonlab
jsonlab
lzmaencode.m 1KB
gendocs.sh 1KB
lz4decode.m 1KB
fast_match_bracket.m 2KB
loadubjson.m 12KB
lzipencode.m 1KB
lzmadecode.m 1KB
nestbracket2dim.m 2KB
jdatadecode.m 12KB
savemsgpack.m 1KB
AUTHORS.txt 3KB
lz4hcencode.m 1KB
README.rst 18KB
lz4hcdecode.m 1KB
gzipencode.m 2KB
loadmsgpack.m 8KB
examples
demo_msgpack_basic.m 9KB
demo_jsonlab_basic.m 13KB
jsonlab_ubjson_basictest.matlab 16KB
example1.json 436B
jsonlab_speedtest.m 675B
jsonlab_selftest.matlab 4KB
example3.json 272B
example2.json 583B
example4.json 563B
demo_ubjson_basic.m 12KB
jsonlab_selftest.m 995B
jsonlab_basictest.matlab 19KB
README.txt 18KB
base64encode.m 1KB
loadjson.m 19KB
ChangeLog.txt 10KB
isoctavemesh.m 497B
mergestruct.m 746B
package.json 531B
jsonopt.m 916B
base64decode.m 1KB
lz4encode.m 1KB
zlibdecode.m 2KB
encodevarname.m 2KB
zlibencode.m 2KB
decodevarname.m 2KB
lzipdecode.m 1KB
varargin2struct.m 1KB
.gitignore 395B
savejson.m 26KB
gzipdecode.m 2KB
DESCRIPTION 667B
genlog.sh 63B
LICENSE_BSD.txt 2KB
saveubjson.m 30KB
match_bracket.m 2KB
jdataencode.m 11KB
INDEX 551B
Contents.m 48KB
Runme.m 5KB
image1.TIF 54.52MB
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