simple-tools-for-machine-learning for a newer tool, which written in python3.8
,skimage
,numpy
and without opencv-python
. This repo will not be upgraded any more.
Visit ![](https://raw.githubusercontent.com/guchengxi1994/mask2json/master/convertmask/UI/statics/look.png)
convertmask
Issues and advices wanted.
Introduction
A small tool for image augmentation, including mask files to json/xml files , image augmentation(flip,rotation,noise,...) and so on
HOW TO USE.
Installation.
Try:
pip install -r requestments.txt
IF ERROR, try:
pip install -r requirements.txt --ignore-installed
Use.
Under this version, these tools are provided.
augmentation
1.img2xml
2.json2mask
3.json2xml
4.longImgSplit
5.xml2json
6.xml2mask
7.xml2yolo
8.yolo2xml
9.mask2json
10.CHANGE LOGS
2021.10.31
1.bump to 0.6.0
2. UI update
2021.1.14
testYoloLike.py. The test dataset can be found in ./test/ , 68 txts totally.
1.update spliting yolo-like dataset into train and val datasets AUTOMATICLY.See2020.11.25
1. negative sample AUTOMATICLY randomly generate. I am not sure if it is helpful to my face detection cnn.
mosaic.py(without resize the origin images). See here.
2. rewrite2020.11.16
here
1.support converting widerface annotations to xmls. see2020.11.10
here. Test script can be found here
1. object-oriented rewrite augumentation optional module. See2020.10.25
1. bump to 0.5.3
2. code structure change
here
3. mosiac(yolov4) augumentation supported(auto labeled for labelImg,for labelme will be updated as fast as i can). Script can be found2020.10.24
here)
1.image crop supported.(single and multiple crops,rectangle and polygon support. Seehere and the test script is here
2.image resize supported (auto labeled). See2020.10.23
1.image distortion supported.
see here or test-script for details.
2020.10.13
here
1.image augumentation support convert yolo txts to xmls(pascal). See2.speed up by using multiprocess
2020.10.12
here
1.image augumentation support generating several annotation/images with single image/annotation(json,xml). See2020.9.24
LabelImgTool, convert xmls to jsons is useful. Also ,i forked this repo and add some pyqt5/py3 support,see here.
1.inspired byexamples:
script here
2020.8.24
here
1.support convert xml files to yolo files. seeexamples:
2020.8.19
1. image translation supported.
combination of every augmentation method.
here
2. besides, a simple way convert json file(labelme) to xml file(labelImg) is provided. see2020.8.17
1. bug fix.
test_imgAug.py !
2. support image augmentation methods: noise,flip,rotation. tryhere are some examples:
flip
noise
rotation
2020.8.14
test_imgAug.py !
1. add image augmentation (image flip) test. see2020.7.14
1.bugfix , test multi objects to xml files, pretty xmls
eg:
2020.7.13
1. convert multi objects to xml files supported (untested)
2020.7.10
1. a lot of things to do ,such as many warnings related to labelme.
2020.6.12
1.support multiple objects mask to json
try test.py !
1.1 multiple objects in different classes
manually_labeled image
auto_labeled image
1.2 multiple objects in same classes
manually_labeled image
auto_labeled image
what to do next
support multiple files image augmentation (2020.8.21)
1. support image augmentation without a label/json file (2020.8.21)
2. support image augmentation with a labeled file (just support json file right now) (2020.9)
3. 4. image augmentation supports custom parameters (auto augmented right now)
5. do something more interesting
re-write main script (2020.10)
6. script by myself. maybe failure in the end.)~~
7. ~~ solve PyYmal installation error(currently write aimage augmentation zoooom (2020.10.14)
8. 9. yolo txts split train/val dataset automaticly.
OTHERS
if you test the json2mask.py script, you should change the path first and make sure the file is valid(maybe i have deleted :) )
Also, this script is just a reverse of mask2json, for a more COOOOOL method, see here , try convert.processor
SHORTCOMING
1.objects connected to each other is not supported yet.
this may happen if you labelling multiple-object-images with only 2 labels .Or some objects are of the same type and are connected to each other(eg. a bunch of grapes,it is hard to split one to the other).
2.Image Binarization issue