Merge branch 'master' of https://github.com/PaddlePaddle/PaddleX

DataAnnotation/README.md

 ### 数据标注
-在DataAnnotation模块下，我们依赖LabeMe标注工具，同时提供了数据处理脚本，帮助用户快速准备训练目标检测和语义分割任务所需的数据。
+您可以使用LabeMe标注工具对您的数据进行标注，同时提供了数据处理脚本，帮助用户快速准备训练目标检测和语义分割任务所需的数据。
 
 ### LabelMe
 LabelMe是目前广泛使用的数据标注工具，并且在GitHub上开源给用户使用。  

DataAnnotation/labelme/.github/stale.yaml

-# Number of days of inactivity before an issue becomes stale
-daysUntilStale: 30
-# Number of days of inactivity before a stale issue is closed
-daysUntilClose: 7
-# Issues with these labels will never be considered stale
-exemptLabels:
-  - bug
-# Label to use when marking an issue as stale
-staleLabel: stale
-# Comment to post when marking an issue as stale. Set to `false` to disable
-markComment: >
-  This issue has been automatically marked as stale because it has not had
-  recent activity. It will be closed if no further activity occurs. Thank you
-  for your contributions.
-# Comment to post when removing the stale label. Set to `false` to disable
-unmarkComment: false
-# Comment to post when closing a stale issue. Set to `false` to disable
-closeComment: >
-  This issue is closed as announced. Feel free to re-open it if needed.

DataAnnotation/labelme/.gitignore

-/.cache/
-/.pytest_cache/
-
-/build/
-/dist/
-/*.egg-info/
-
-*.py[cdo]
-
-.DS_Store

DataAnnotation/labelme/.gitmodules

-[submodule "github2pypi"]
-	path = github2pypi
-	url = https://github.com/wkentaro/github2pypi.git

DataAnnotation/labelme/.travis.yml

-language: generic
-
-cache:
-  - pip
-
-sudo: required
-
-dist: trusty
-
-branches:
-  only:
-    - master
-    - /v\d+\.\d+.\d+/
-
-notifications:
-  email: false
-
-env:
-  global:
-    # used by ci-helpers
-    - SETUP_XVFB=true
-    - PIP_DEPENDENCIES='hacking pytest pytest-qt'
-
-    - MPLBACKEND=TkAgg  # for osx
-matrix:
-  include:
-    - os: osx
-      env:
-        - PYTEST_QT_API=pyqt5
-        - PYQT_PACKAGE='pyqt=5'
-        - PYTHON_VERSION=3.6
-        - RUN_PYINSTALLER=true
-    - os: linux
-      dist: trusty
-      env:
-        - PYTEST_QT_API=pyqt4v2
-        - PYQT_PACKAGE='pyqt=4'
-        - PYTHON_VERSION=2.7
-    - os: linux
-      dist: trusty
-      env:
-        - PYTEST_QT_API=pyside2
-        - CONDA_CHANNELS='conda-forge'
-        - PYQT_PACKAGE='pyside2!=5.12.4'
-        - PYTHON_VERSION=2.7
-    - os: linux
-      dist: trusty
-      env:
-        - PYTEST_QT_API=pyside2
-        - CONDA_CHANNELS='conda-forge'
-        - PYQT_PACKAGE='pyside2'
-        - PYTHON_VERSION=3.6
-    - os: linux
-      dist: trusty
-      env:
-        - PYTEST_QT_API=pyqt5
-        - PYQT_PACKAGE='pyqt=5'
-        - PYTHON_VERSION=2.7
-    - os: linux
-      dist: trusty
-      env:
-        - PYTEST_QT_API=pyqt5
-        - PYQT_PACKAGE='pyqt=5'
-        - PYTHON_VERSION=3.6
-        - RUN_PYINSTALLER=true
-
-install:
-  # Setup X
-  - |
-    if [ $TRAVIS_OS_NAME = "linux" ]; then
-      sudo apt-get update
-      # Xvfb / window manager
-      sudo apt-get install -y xvfb herbstluftwm
-    elif [ $TRAVIS_OS_NAME = "osx" ]; then
-      brew cask install xquartz
-    fi
-
-  # Setup miniconda
-  - git clone --depth 1 git://github.com/astropy/ci-helpers.git
-  - CONDA_DEPENDENCIES=$PYQT_PACKAGE source ci-helpers/travis/setup_conda.sh
-  - source activate test && export LD_LIBRARY_PATH=$CONDA_PREFIX/lib:$LD_LIBRARY_PATH
-  - pip install .
-  - rm -rf ci-helpers miniconda.sh
-
-before_script:
-  - if [ $TRAVIS_OS_NAME = "linux" ]; then (herbstluftwm )& fi
-  - if [ $TRAVIS_OS_NAME = "osx" ]; then (sudo Xvfb :99 -ac -screen 0 1024x768x8 )& fi
-  - sleep 1
-
-script:
-  # Run flake8
-  - flake8 examples labelme setup.py tests
-
-  # Run help2man
-  - conda install -y help2man
-
-  # Run pytest
-  - pytest -v tests
-
-  - labelme --help
-  - labelme --version
-
-  # Run examples
-  - (cd examples/primitives && labelme_json_to_dataset primitives.json && rm -rf primitives_json)
-  - (cd examples/tutorial && rm -rf apc2016_obj3_json && labelme_json_to_dataset apc2016_obj3.json && python load_label_png.py && git checkout -- .)
-  - (cd examples/semantic_segmentation && rm -rf data_dataset_voc && ./labelme2voc.py data_annotated data_dataset_voc --labels labels.txt && git checkout -- .)
-  - (cd examples/instance_segmentation && rm -rf data_dataset_voc && ./labelme2voc.py data_annotated data_dataset_voc --labels labels.txt && git checkout -- .)
-  - (cd examples/video_annotation && rm -rf data_dataset_voc && ./labelme2voc.py data_annotated data_dataset_voc --labels labels.txt && git checkout -- .)
-
-  - pip install lxml  # for bbox_detection/labelme2voc.py
-  - (cd examples/bbox_detection && rm -rf data_dataset_voc && ./labelme2voc.py data_annotated data_dataset_voc --labels labels.txt && git checkout -- .)
-
-  - pip install cython && pip install pycocotools  # for instance_segmentation/labelme2coco.py
-  - (cd examples/instance_segmentation && rm -rf data_dataset_coco && ./labelme2coco.py data_annotated data_dataset_coco --labels labels.txt && git checkout -- .)
-
-  # Run pyinstaller
-  - |
-    if [ "$RUN_PYINSTALLER" = "true" ]; then
-      # Cleanup
-      pip uninstall -y $PIP_DEPENDENCIES
-
-      # https://github.com/wkentaro/labelme/issues/183
-      if [ $TRAVIS_OS_NAME = "osx" ]; then
-        pip uninstall -y Pillow
-        conda install -y Pillow
-      fi
-
-      # Build the standalone executable
-      pip install 'pyinstaller!=3.4'  # 3.4 raises error
-
-      # numpy 1.17 raises error
-      # See https://github.com/wkentaro/labelme/issues/465
-      pip install 'numpy<1.17'
-
-      pyinstaller labelme.spec
-      dist/labelme --version
-    fi
-
-after_script:
-  - true  # noop

DataAnnotation/labelme/LICENSE

-Copyright (C) 2016-2018 Kentaro Wada.
-Copyright (C) 2011 Michael Pitidis, Hussein Abdulwahid.
-
-Labelme is free software: you can redistribute it and/or modify
-it under the terms of the GNU General Public License as published by
-the Free Software Foundation, either version 3 of the License, or
-(at your option) any later version.
-
-Labelme is distributed in the hope that it will be useful,
-but WITHOUT ANY WARRANTY; without even the implied warranty of
-MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
-GNU General Public License for more details.
-
-You should have received a copy of the GNU General Public License
-along with Labelme.  If not, see <http://www.gnu.org/licenses/>.

DataAnnotation/labelme/MANIFEST.in

-include README.md

DataAnnotation/labelme/README.md

-<h1 align="center">
-  <img src="labelme/icons/icon.png"><br/>labelme
-</h1>
-
-<h4 align="center">
-  Image Polygonal Annotation with Python
-</h4>
-
-<div align="center">
-  <a href="https://pypi.python.org/pypi/labelme"><img src="https://img.shields.io/pypi/v/labelme.svg"></a>
-  <a href="https://pypi.org/project/labelme"><img src="https://img.shields.io/pypi/pyversions/labelme.svg"></a>
-  <a href="https://travis-ci.org/wkentaro/labelme"><img src="https://travis-ci.org/wkentaro/labelme.svg?branch=master"></a>
-  <a href="https://hub.docker.com/r/wkentaro/labelme"><img src="https://img.shields.io/docker/build/wkentaro/labelme.svg"></a>
-</div>
-
-<br/>
-
-<div align="center">
-  <img src="examples/instance_segmentation/.readme/annotation.jpg" width="70%">
-</div>
-
-## Description
-
-Labelme is a graphical image annotation tool inspired by <http://labelme.csail.mit.edu>.  
-It is written in Python and uses Qt for its graphical interface.
-
-<img src="examples/instance_segmentation/data_dataset_voc/JPEGImages/2011_000006.jpg" width="19%" /> <img src="examples/instance_segmentation/data_dataset_voc/SegmentationClassPNG/2011_000006.png" width="19%" /> <img src="examples/instance_segmentation/data_dataset_voc/SegmentationClassVisualization/2011_000006.jpg" width="19%" /> <img src="examples/instance_segmentation/data_dataset_voc/SegmentationObjectPNG/2011_000006.png" width="19%" /> <img src="examples/instance_segmentation/data_dataset_voc/SegmentationObjectVisualization/2011_000006.jpg" width="19%" />  
-<i>VOC dataset example of instance segmentation.</i>
-
-<img src="examples/semantic_segmentation/.readme/annotation.jpg" width="32%" /> <img src="examples/bbox_detection/.readme/annotation.jpg" width="30%" /> <img src="examples/classification/.readme/annotation_cat.jpg" width="35%" />  
-<i>Other examples (semantic segmentation, bbox detection, and classification).</i>
-
-<img src="https://user-images.githubusercontent.com/4310419/47907116-85667800-de82-11e8-83d0-b9f4eb33268f.gif" width="30%" /> <img src="https://user-images.githubusercontent.com/4310419/47922172-57972880-deae-11e8-84f8-e4324a7c856a.gif" width="30%" /> <img src="https://user-images.githubusercontent.com/14256482/46932075-92145f00-d080-11e8-8d09-2162070ae57c.png" width="32%" />  
-<i>Various primitives (polygon, rectangle, circle, line, and point).</i>
-
-
-## Features
-
-- [x] Image annotation for polygon, rectangle, circle, line and point. ([tutorial](examples/tutorial))
-- [x] Image flag annotation for classification and cleaning. ([#166](https://github.com/wkentaro/labelme/pull/166))
-- [x] Video annotation. ([video annotation](examples/video_annotation))
-- [x] GUI customization (predefined labels / flags, auto-saving, label validation, etc). ([#144](https://github.com/wkentaro/labelme/pull/144))
-- [x] Exporting VOC-format dataset for semantic/instance segmentation. ([semantic segmentation](examples/semantic_segmentation), [instance segmentation](examples/instance_segmentation))
-- [x] Exporting COCO-format dataset for instance segmentation. ([instance segmentation](examples/instance_segmentation))
-
-
-
-## Requirements
-
-- Ubuntu / macOS / Windows
-- Python2 / Python3
-- [PyQt4 / PyQt5](http://www.riverbankcomputing.co.uk/software/pyqt/intro) / [PySide2](https://wiki.qt.io/PySide2_GettingStarted)
-
-
-## Installation
-
-There are options:
-
-- Platform agonistic installation: [Anaconda](#anaconda), [Docker](#docker)
-- Platform specific installation: [Ubuntu](#ubuntu), [macOS](#macos), [Windows](#windows)
-
-### Anaconda
-
-You need install [Anaconda](https://www.continuum.io/downloads), then run below:
-
-```bash
-# python2
-conda create --name=labelme python=2.7
-source activate labelme
-# conda install -c conda-forge pyside2
-conda install pyqt
-pip install labelme
-# if you'd like to use the latest version. run below:
-# pip install git+https://github.com/wkentaro/labelme.git
-
-# python3
-conda create --name=labelme python=3.6
-source activate labelme
-# conda install -c conda-forge pyside2
-# conda install pyqt
-pip install pyqt5  # pyqt5 can be installed via pip on python3
-pip install labelme
-```
-
-### Docker
-
-You need install [docker](https://www.docker.com), then run below:
-
-```bash
-wget https://raw.githubusercontent.com/wkentaro/labelme/master/labelme/cli/on_docker.py -O labelme_on_docker
-chmod u+x labelme_on_docker
-
-# Maybe you need http://sourabhbajaj.com/blog/2017/02/07/gui-applications-docker-mac/ on macOS
-./labelme_on_docker examples/tutorial/apc2016_obj3.jpg -O examples/tutorial/apc2016_obj3.json
-./labelme_on_docker examples/semantic_segmentation/data_annotated
-```
-
-### Ubuntu
-
-```bash
-# Ubuntu 14.04 / Ubuntu 16.04
-# Python2
-# sudo apt-get install python-qt4  # PyQt4
-sudo apt-get install python-pyqt5  # PyQt5
-sudo pip install labelme
-# Python3
-sudo apt-get install python3-pyqt5  # PyQt5
-sudo pip3 install labelme
-```
-
-### Ubuntu 19.10+ / Debian (sid)
-
-```bash
-sudo apt-get install labelme
-```
-
-### macOS
-
-```bash
-# macOS Sierra
-brew install pyqt  # maybe pyqt5
-pip install labelme  # both python2/3 should work
-
-# or install standalone executable / app
-# NOTE: this only installs the `labelme` command
-brew install wkentaro/labelme/labelme
-brew cask install wkentaro/labelme/labelme
-```
-
-### Windows
-
-Firstly, follow instruction in [Anaconda](#anaconda).
-
-```bash
-# Pillow 5 causes dll load error on Windows.
-# https://github.com/wkentaro/labelme/pull/174
-conda install pillow=4.0.0
-```
-
-
-## Usage
-
-Run `labelme --help` for detail.  
-The annotations are saved as a [JSON](http://www.json.org/) file.
-
-```bash
-labelme  # just open gui
-
-# tutorial (single image example)
-cd examples/tutorial
-labelme apc2016_obj3.jpg  # specify image file
-labelme apc2016_obj3.jpg -O apc2016_obj3.json  # close window after the save
-labelme apc2016_obj3.jpg --nodata  # not include image data but relative image path in JSON file
-labelme apc2016_obj3.jpg \
-  --labels highland_6539_self_stick_notes,mead_index_cards,kong_air_dog_squeakair_tennis_ball  # specify label list
-
-# semantic segmentation example
-cd examples/semantic_segmentation
-labelme data_annotated/  # Open directory to annotate all images in it
-labelme data_annotated/ --labels labels.txt  # specify label list with a file
-```
-
-For more advanced usage, please refer to the examples:
-
-* [Tutorial (Single Image Example)](examples/tutorial)
-* [Semantic Segmentation Example](examples/semantic_segmentation)
-* [Instance Segmentation Example](examples/instance_segmentation)
-* [Video Annotation Example](examples/video_annotation)
-
-### Command Line Arguemnts
-- `--output` specifies the location that annotations will be written to. If the location ends with .json, a single annotation will be written to this file. Only one image can be annotated if a location is specified with .json. If the location does not end with .json, the program will assume it is a directory. Annotations will be stored in this directory with a name that corresponds to the image that the annotation was made on.
-- The first time you run labelme, it will create a config file in `~/.labelmerc`. You can edit this file and the changes will be applied the next time that you launch labelme. If you would prefer to use a config file from another location, you can specify this file with the `--config` flag.
-- Without the `--nosortlabels` flag, the program will list labels in alphabetical order. When the program is run with this flag, it will display labels in the order that they are provided.
-- Flags are assigned to an entire image. [Example](examples/classification)
-- Labels are assigned to a single polygon. [Example](examples/bbox_detection)
-
-## FAQ
-
-- **How to convert JSON file to numpy array?** See [examples/tutorial](examples/tutorial#convert-to-dataset).
-- **How to load label PNG file?** See [examples/tutorial](examples/tutorial#how-to-load-label-png-file).
-- **How to get annotations for semantic segmentation?** See [examples/semantic_segmentation](examples/semantic_segmentation).
-- **How to get annotations for instance segmentation?** See [examples/instance_segmentation](examples/instance_segmentation).
-
-
-## Testing
-
-```bash
-pip install hacking pytest pytest-qt
-flake8 .
-pytest -v tests
-```
-
-
-## Developing
-
-```bash
-git clone https://github.com/wkentaro/labelme.git
-cd labelme
-
-# Install anaconda3 and labelme
-curl -L https://github.com/wkentaro/dotfiles/raw/master/local/bin/install_anaconda3.sh | bash -s .
-source .anaconda3/bin/activate
-pip install -e .
-```
-
-
-## How to build standalone executable
-
-Below shows how to build the standalone executable on macOS, Linux and Windows.  
-Also, there are pre-built executables in
-[the release section](https://github.com/wkentaro/labelme/releases).
-
-```bash
-# Setup conda
-conda create --name labelme python==3.6.0
-conda activate labelme
-
-# Build the standalone executable
-pip install .
-pip install pyinstaller
-pyinstaller labelme.spec
-dist/labelme --version
-```
-
-
-## Acknowledgement
-
-This repo is the fork of [mpitid/pylabelme](https://github.com/mpitid/pylabelme),
-whose development has already stopped.
-
-
-## Cite This Project
-
-If you use this project in your research or wish to refer to the baseline results published in the README, please use the following BibTeX entry.
-
-```bash
-@misc{labelme2016,
-  author =       {Ketaro Wada},
-  title =        {{labelme: Image Polygonal Annotation with Python}},
-  howpublished = {\url{https://github.com/wkentaro/labelme}},
-  year =         {2016}
-}
-```

DataAnnotation/labelme/docker/Dockerfile

-FROM ubuntu:xenial
-
-# http://fabiorehm.com/blog/2014/09/11/running-gui-apps-with-docker/
-RUN export uid=1000 gid=1000 && \
-    mkdir -p /home/developer && \
-    echo "developer:x:${uid}:${gid}:Developer,,,:/home/developer:/bin/bash" >> /etc/passwd && \
-    echo "developer:x:${uid}:" >> /etc/group && \
-    mkdir -p /etc/sudoers.d && \
-    echo "developer ALL=(ALL) NOPASSWD: ALL" > /etc/sudoers.d/developer && \
-    chmod 0440 /etc/sudoers.d/developer && \
-    chown ${uid}:${gid} -R /home/developer
-
-RUN \
-  apt-get update -qq && \
-  apt-get upgrade -qq -y && \
-  apt-get install -qq -y \
-    # requirements
-    git \
-    python3 \
-    python3-pip \
-    python3-matplotlib \
-    python3-pyqt5 \
-    # utilities
-    sudo
-
-RUN pip3 install -v git+https://github.com/wkentaro/labelme.git
-
-USER developer
-ENV HOME /home/developer

DataAnnotation/labelme/docs/man/labelme.1

-.\" DO NOT MODIFY THIS FILE!  It was generated by help2man 1.47.8.
-.TH LABELME "1" "August 2019" "labelme 3.16.3" "User Commands"
-.SH NAME
-labelme \- manual page for labelme 3.16.3
-.SH DESCRIPTION
-usage: labelme [\-h] [\-\-version] [\-\-reset\-config]
-.IP
-[\-\-logger\-level {debug,info,warning,fatal,error}]
-[\-\-output OUTPUT] [\-\-config CONFIG_FILE] [\-\-nodata]
-[\-\-autosave] [\-\-nosortlabels] [\-\-flags FLAGS]
-[\-\-labelflags LABEL_FLAGS] [\-\-labels LABELS]
-[\-\-validatelabel {exact,instance}] [\-\-keep\-prev]
-[\-\-epsilon EPSILON]
-[filename]
-.SS "positional arguments:"
-.TP
-filename
-image or label filename
-.SS "optional arguments:"
-.TP
-\fB\-h\fR, \fB\-\-help\fR
-show this help message and exit
-.TP
-\fB\-\-version\fR, \fB\-V\fR
-show version
-.TP
-\fB\-\-reset\-config\fR
-reset qt config
-.TP
-\fB\-\-logger\-level\fR {debug,info,warning,fatal,error}
-logger level
-.TP
-\fB\-\-output\fR OUTPUT, \fB\-O\fR OUTPUT, \fB\-o\fR OUTPUT
-output file or directory (if it ends with .json it is
-recognized as file, else as directory)
-.TP
-\fB\-\-config\fR CONFIG_FILE
-config file (default: /home/wkentaro/.labelmerc)
-.TP
-\fB\-\-nodata\fR
-stop storing image data to JSON file
-.TP
-\fB\-\-autosave\fR
-auto save
-.TP
-\fB\-\-nosortlabels\fR
-stop sorting labels
-.TP
-\fB\-\-flags\fR FLAGS
-comma separated list of flags OR file containing flags
-.TP
-\fB\-\-labelflags\fR LABEL_FLAGS
-yaml string of label specific flags OR file containing
-json string of label specific flags (ex. {person\-\ed+:
-[male, tall], dog\-\ed+: [black, brown, white], .*:
-[occluded]})
-.TP
-\fB\-\-labels\fR LABELS
-comma separated list of labels OR file containing
-labels
-.TP
-\fB\-\-validatelabel\fR {exact,instance}
-label validation types
-.TP
-\fB\-\-keep\-prev\fR
-keep annotation of previous frame
-.TP
-\fB\-\-epsilon\fR EPSILON
-epsilon to find nearest vertex on canvas
-.SH "SEE ALSO"
-The full documentation for
-.B labelme
-is maintained as a Texinfo manual.  If the
-.B info
-and
-.B labelme
-programs are properly installed at your site, the command
-.IP
-.B info labelme
-.PP
-should give you access to the complete manual.

DataAnnotation/labelme/examples/bbox_detection/README.md

-# Bounding Box Detection Example
-
-
-## Usage
-
-```bash
-labelme data_annotated --labels labels.txt --nodata --autosave
-```
-
-![](.readme/annotation.jpg)
-
-
-## Convert to VOC-format Dataset
-
-```bash
-# It generates:
-#   - data_dataset_voc/JPEGImages
-#   - data_dataset_voc/Annotations
-#   - data_dataset_voc/AnnotationsVisualization
-./labelme2voc.py data_annotated data_dataset_voc --labels labels.txt
-```
-
-<img src="data_dataset_voc/JPEGImages/2011_000003.jpg" width="33%" /> <img src="data_dataset_voc/AnnotationsVisualization/2011_000003.jpg" width="33%" />
-
-<i>Fig1. JPEG image (left), Bounding box annotation visualization (right).</i>

DataAnnotation/labelme/examples/bbox_detection/data_annotated/2011_000003.json

-{
-  "flags": {},
-  "shapes": [
-    {
-      "label": "person",
-      "line_color": null,
-      "fill_color": null,
-      "points": [
-        [
-          191,
-          107
-        ],
-        [
-          313,
-          329
-        ]
-      ],
-      "shape_type": "rectangle"
-    },
-    {
-      "label": "person",
-      "line_color": null,
-      "fill_color": null,
-      "points": [
-        [
-          365,
-          83
-        ],
-        [
-          500,
-          333
-        ]
-      ],
-      "shape_type": "rectangle"
-    }
-  ],
-  "lineColor": [
-    0,
-    255,
-    0,
-    128
-  ],
-  "fillColor": [
-    255,
-    0,
-    0,
-    128
-  ],
-  "imagePath": "2011_000003.jpg",
-  "imageData": null
-}
\ No newline at end of file

DataAnnotation/labelme/examples/bbox_detection/data_annotated/2011_000006.json

-{
-  "flags": {},
-  "shapes": [
-    {
-      "label": "person",
-      "line_color": null,
-      "fill_color": null,
-      "points": [
-        [
-          91,
-          107
-        ],
-        [
-          240,
-          330
-        ]
-      ],
-      "shape_type": "rectangle"
-    },
-    {
-      "label": "person",
-      "line_color": null,
-      "fill_color": null,
-      "points": [
-        [
-          178,
-          110
-        ],
-        [
-          298,
-          282
-        ]
-      ],
-      "shape_type": "rectangle"
-    },
-    {
-      "label": "person",
-      "line_color": null,
-      "fill_color": null,
-      "points": [
-        [
-          254,
-          115
-        ],
-        [
-          369,
-          292
-        ]
-      ],
-      "shape_type": "rectangle"
-    },
-    {
-      "label": "person",
-      "line_color": null,
-      "fill_color": null,
-      "points": [
-        [
-          395,
-          81
-        ],
-        [
-          447,
-          117
-        ]
-      ],
-      "shape_type": "rectangle"
-    }
-  ],
-  "lineColor": [
-    0,
-    255,
-    0,
-    128
-  ],
-  "fillColor": [
-    255,
-    0,
-    0,
-    128
-  ],
-  "imagePath": "2011_000006.jpg",
-  "imageData": null
-}
\ No newline at end of file

DataAnnotation/labelme/examples/bbox_detection/data_annotated/2011_000025.json

-{
-  "flags": {},
-  "shapes": [
-    {
-      "label": "bus",
-      "line_color": null,
-      "fill_color": null,
-      "points": [
-        [
-          84,
-          20
-        ],
-        [
-          435,
-          373
-        ]
-      ],
-      "shape_type": "rectangle"
-    },
-    {
-      "label": "bus",
-      "line_color": null,
-      "fill_color": null,
-      "points": [
-        [
-          1,
-          99
-        ],
-        [
-          107,
-          282
-        ]
-      ],
-      "shape_type": "rectangle"
-    },
-    {
-      "label": "car",
-      "line_color": null,
-      "fill_color": null,
-      "points": [
-        [
-          409,
-          167
-        ],
-        [
-          500,
-          266
-        ]
-      ],
-      "shape_type": "rectangle"
-    }
-  ],
-  "lineColor": [
-    0,
-    255,
-    0,
-    128
-  ],
-  "fillColor": [
-    255,
-    0,
-    0,
-    128
-  ],
-  "imagePath": "2011_000025.jpg",
-  "imageData": null
-}
\ No newline at end of file

DataAnnotation/labelme/examples/bbox_detection/data_dataset_voc/Annotations/2011_000003.xml

-<annotation>
-  <folder/>
-  <filename>2011_000003.jpg</filename>
-  <database/>
-  <annotation/>
-  <image/>
-  <size>
-    <height>338</height>
-    <width>500</width>
-    <depth>3</depth>
-  </size>
-  <segmented/>
-  <object>
-    <name>person</name>
-    <pose/>
-    <truncated/>
-    <difficult/>
-    <bndbox>
-      <xmin>191</xmin>
-      <ymin>107</ymin>
-      <xmax>313</xmax>
-      <ymax>329</ymax>
-    </bndbox>
-  </object>
-  <object>
-    <name>person</name>
-    <pose/>
-    <truncated/>
-    <difficult/>
-    <bndbox>
-      <xmin>365</xmin>
-      <ymin>83</ymin>
-      <xmax>500</xmax>
-      <ymax>333</ymax>
-    </bndbox>
-  </object>
-</annotation>

DataAnnotation/labelme/examples/bbox_detection/data_dataset_voc/Annotations/2011_000006.xml

-<annotation>
-  <folder/>
-  <filename>2011_000006.jpg</filename>
-  <database/>
-  <annotation/>
-  <image/>
-  <size>
-    <height>375</height>
-    <width>500</width>
-    <depth>3</depth>
-  </size>
-  <segmented/>
-  <object>
-    <name>person</name>
-    <pose/>
-    <truncated/>
-    <difficult/>
-    <bndbox>
-      <xmin>91</xmin>
-      <ymin>107</ymin>
-      <xmax>240</xmax>
-      <ymax>330</ymax>
-    </bndbox>
-  </object>
-  <object>
-    <name>person</name>
-    <pose/>
-    <truncated/>
-    <difficult/>
-    <bndbox>
-      <xmin>178</xmin>
-      <ymin>110</ymin>
-      <xmax>298</xmax>
-      <ymax>282</ymax>
-    </bndbox>
-  </object>
-  <object>
-    <name>person</name>
-    <pose/>
-    <truncated/>
-    <difficult/>
-    <bndbox>
-      <xmin>254</xmin>
-      <ymin>115</ymin>
-      <xmax>369</xmax>
-      <ymax>292</ymax>
-    </bndbox>
-  </object>
-  <object>
-    <name>person</name>
-    <pose/>
-    <truncated/>
-    <difficult/>
-    <bndbox>
-      <xmin>395</xmin>
-      <ymin>81</ymin>
-      <xmax>447</xmax>
-      <ymax>117</ymax>
-    </bndbox>
-  </object>
-</annotation>

DataAnnotation/labelme/examples/bbox_detection/data_dataset_voc/Annotations/2011_000025.xml

-<annotation>
-  <folder/>
-  <filename>2011_000025.jpg</filename>
-  <database/>
-  <annotation/>
-  <image/>
-  <size>
-    <height>375</height>
-    <width>500</width>
-    <depth>3</depth>
-  </size>
-  <segmented/>
-  <object>
-    <name>bus</name>
-    <pose/>
-    <truncated/>
-    <difficult/>
-    <bndbox>
-      <xmin>84</xmin>
-      <ymin>20</ymin>
-      <xmax>435</xmax>
-      <ymax>373</ymax>
-    </bndbox>
-  </object>
-  <object>
-    <name>bus</name>
-    <pose/>
-    <truncated/>
-    <difficult/>
-    <bndbox>
-      <xmin>1</xmin>
-      <ymin>99</ymin>
-      <xmax>107</xmax>
-      <ymax>282</ymax>
-    </bndbox>
-  </object>
-  <object>
-    <name>car</name>
-    <pose/>
-    <truncated/>
-    <difficult/>
-    <bndbox>
-      <xmin>409</xmin>
-      <ymin>167</ymin>
-      <xmax>500</xmax>
-      <ymax>266</ymax>
-    </bndbox>
-  </object>
-</annotation>

DataAnnotation/labelme/examples/bbox_detection/data_dataset_voc/class_names.txt

-_background_
-aeroplane
-bicycle
-bird
-boat
-bottle
-bus
-car
-cat
-chair
-cow
-diningtable
-dog
-horse
-motorbike
-person
-potted plant
-sheep
-sofa
-train
-tv/monitor
\ No newline at end of file

DataAnnotation/labelme/examples/bbox_detection/labelme2voc.py

-#!/usr/bin/env python
-
-from __future__ import print_function
-
-import argparse
-import glob
-import json
-import os
-import os.path as osp
-import sys
-
-try:
-    import lxml.builder
-    import lxml.etree
-except ImportError:
-    print('Please install lxml:\n\n    pip install lxml\n')
-    sys.exit(1)
-import numpy as np
-import PIL.Image
-
-import labelme
-
-
-def main():
-    parser = argparse.ArgumentParser(
-        formatter_class=argparse.ArgumentDefaultsHelpFormatter
-    )
-    parser.add_argument('input_dir', help='input annotated directory')
-    parser.add_argument('output_dir', help='output dataset directory')
-    parser.add_argument('--labels', help='labels file', required=True)
-    args = parser.parse_args()
-
-    if osp.exists(args.output_dir):
-        print('Output directory already exists:', args.output_dir)
-        sys.exit(1)
-    os.makedirs(args.output_dir)
-    os.makedirs(osp.join(args.output_dir, 'JPEGImages'))
-    os.makedirs(osp.join(args.output_dir, 'Annotations'))
-    os.makedirs(osp.join(args.output_dir, 'AnnotationsVisualization'))
-    print('Creating dataset:', args.output_dir)
-
-    class_names = []
-    class_name_to_id = {}
-    for i, line in enumerate(open(args.labels).readlines()):
-        class_id = i - 1  # starts with -1
-        class_name = line.strip()
-        class_name_to_id[class_name] = class_id
-        if class_id == -1:
-            assert class_name == '__ignore__'
-            continue
-        elif class_id == 0:
-            assert class_name == '_background_'
-        class_names.append(class_name)
-    class_names = tuple(class_names)
-    print('class_names:', class_names)
-    out_class_names_file = osp.join(args.output_dir, 'class_names.txt')
-    with open(out_class_names_file, 'w') as f:
-        f.writelines('\n'.join(class_names))
-    print('Saved class_names:', out_class_names_file)
-
-    for label_file in glob.glob(osp.join(args.input_dir, '*.json')):
-        print('Generating dataset from:', label_file)
-        with open(label_file) as f:
-            data = json.load(f)
-        base = osp.splitext(osp.basename(label_file))[0]
-        out_img_file = osp.join(
-            args.output_dir, 'JPEGImages', base + '.jpg')
-        out_xml_file = osp.join(
-            args.output_dir, 'Annotations', base + '.xml')
-        out_viz_file = osp.join(
-            args.output_dir, 'AnnotationsVisualization', base + '.jpg')
-
-        img_file = osp.join(osp.dirname(label_file), data['imagePath'])
-        img = np.asarray(PIL.Image.open(img_file))
-        PIL.Image.fromarray(img).save(out_img_file)
-
-        maker = lxml.builder.ElementMaker()
-        xml = maker.annotation(
-            maker.folder(),
-            maker.filename(base + '.jpg'),
-            maker.database(),    # e.g., The VOC2007 Database
-            maker.annotation(),  # e.g., Pascal VOC2007
-            maker.image(),       # e.g., flickr
-            maker.size(
-                maker.height(str(img.shape[0])),
-                maker.width(str(img.shape[1])),
-                maker.depth(str(img.shape[2])),
-            ),
-            maker.segmented(),
-        )
-
-        bboxes = []
-        labels = []
-        for shape in data['shapes']:
-            if shape['shape_type'] != 'rectangle':
-                print('Skipping shape: label={label}, shape_type={shape_type}'
-                      .format(**shape))
-                continue
-
-            class_name = shape['label']
-            class_id = class_names.index(class_name)
-
-            (xmin, ymin), (xmax, ymax) = shape['points']
-            bboxes.append([xmin, ymin, xmax, ymax])
-            labels.append(class_id)
-
-            xml.append(
-                maker.object(
-                    maker.name(shape['label']),
-                    maker.pose(),
-                    maker.truncated(),
-                    maker.difficult(),
-                    maker.bndbox(
-                        maker.xmin(str(xmin)),
-                        maker.ymin(str(ymin)),
-                        maker.xmax(str(xmax)),
-                        maker.ymax(str(ymax)),
-                    ),
-                )
-            )
-
-        captions = [class_names[l] for l in labels]
-        viz = labelme.utils.draw_instances(
-            img, bboxes, labels, captions=captions
-        )
-        PIL.Image.fromarray(viz).save(out_viz_file)
-
-        with open(out_xml_file, 'wb') as f:
-            f.write(lxml.etree.tostring(xml, pretty_print=True))
-
-
-if __name__ == '__main__':
-    main()

DataAnnotation/labelme/examples/bbox_detection/labels.txt

-__ignore__
-_background_
-aeroplane
-bicycle
-bird
-boat
-bottle
-bus
-car
-cat
-chair
-cow
-diningtable
-dog
-horse
-motorbike
-person
-potted plant
-sheep
-sofa
-train
-tv/monitor
\ No newline at end of file

DataAnnotation/labelme/examples/classification/README.md

-# Classification Example
-
-
-## Usage
-
-```bash
-labelme data_annotated --flags flags.txt --nodata
-```
-
-<img src=".readme/annotation_cat.jpg" width="100%" />
-<img src=".readme/annotation_dog.jpg" width="100%" />

DataAnnotation/labelme/examples/classification/data_annotated/0001.json

-{
-  "flags": {
-    "__ignore__": false,
-    "cat": true,
-    "dog": false
-  },
-  "shapes": [],
-  "lineColor": [
-    0,
-    255,
-    0,
-    128
-  ],
-  "fillColor": [
-    255,
-    0,
-    0,
-    128
-  ],
-  "imagePath": "0001.jpg",
-  "imageData": null
-}
\ No newline at end of file

DataAnnotation/labelme/examples/classification/data_annotated/0002.json

-{
-  "flags": {
-    "__ignore__": false,
-    "cat": false,
-    "dog": true
-  },
-  "shapes": [],
-  "lineColor": [
-    0,
-    255,
-    0,
-    128
-  ],
-  "fillColor": [
-    255,
-    0,
-    0,
-    128
-  ],
-  "imagePath": "0002.jpg",
-  "imageData": null
-}
\ No newline at end of file

DataAnnotation/labelme/examples/classification/flags.txt

-__ignore__
-cat
-dog

DataAnnotation/labelme/examples/instance_segmentation/README.md

-# Instance Segmentation Example
-
-## Annotation
-
-```bash
-labelme data_annotated --labels labels.txt --nodata
-labelme data_annotated --labels labels.txt --nodata --labelflags '{.*: [occluded, truncated], person-\d+: [male]}'
-```
-
-![](.readme/annotation.jpg)
-
-## Convert to VOC-format Dataset
-
-```bash
-# It generates:
-#   - data_dataset_voc/JPEGImages
-#   - data_dataset_voc/SegmentationClass
-#   - data_dataset_voc/SegmentationClassVisualization
-#   - data_dataset_voc/SegmentationObject
-#   - data_dataset_voc/SegmentationObjectVisualization
-./labelme2voc.py data_annotated data_dataset_voc --labels labels.txt
-```
-
-<img src="data_dataset_voc/JPEGImages/2011_000003.jpg" width="33%" /> <img src="data_dataset_voc/SegmentationClassVisualization/2011_000003.jpg" width="33%" /> <img src="data_dataset_voc/SegmentationObjectVisualization/2011_000003.jpg" width="33%" />  
-Fig 1. JPEG image (left), JPEG class label visualization (center), JPEG instance label visualization (right)
-
-
-Note that the label file contains only very low label values (ex. `0, 4, 14`), and
-`255` indicates the `__ignore__` label value (`-1` in the npy file).  
-You can see the label PNG file by following.
-
-```bash
-labelme_draw_label_png data_dataset_voc/SegmentationClassPNG/2011_000003.png   # left
-labelme_draw_label_png data_dataset_voc/SegmentationObjectPNG/2011_000003.png  # right
-```
-
-<img src=".readme/draw_label_png_class.jpg" width="33%" /> <img src=".readme/draw_label_png_object.jpg" width="33%" />
-
-
-## Convert to COCO-format Dataset
-
-```bash
-# It generates:
-#   - data_dataset_coco/JPEGImages
-#   - data_dataset_coco/annotations.json
-./labelme2coco.py data_annotated data_dataset_coco --labels labels.txt
-```

DataAnnotation/labelme/examples/instance_segmentation/data_annotated/2011_000003.json

-{
-  "version": "3.14.2",
-  "flags": {},
-  "shapes": [
-    {
-      "label": "person-1",
-      "line_color": null,
-      "fill_color": null,
-      "points": [
-        [
-          250.984126984127,
-          106.92063492063491
-        ],
-        [
-          229.984126984127,
-          118.92063492063491
-        ],
-        [
-          221.984126984127,
-          134.9206349206349
-        ],
-        [
-          223.984126984127,
-          147.9206349206349
-        ],
-        [
-          217.984126984127,
-          160.9206349206349
-        ],
-        [
-          202.984126984127,
-          167.9206349206349
-        ],
-        [
-          192.984126984127,
-          199.9206349206349
-        ],
-        [
-          194.984126984127,
-          221.9206349206349
-        ],
-        [
-          199.984126984127,
-          226.9206349206349
-        ],
-        [
-          191.984126984127,
-          233.9206349206349
-        ],
-        [
-          197.984126984127,
-          263.92063492063494
-        ],
-        [
-          213.984126984127,
-          294.92063492063494
-        ],
-        [
-          214.984126984127,
-          319.92063492063494
-        ],
-        [
-          221.984126984127,
-          326.92063492063494
-        ],
-        [
-          235.984126984127,
-          325.92063492063494
-        ],
-        [
-          240.984126984127,
-          322.92063492063494
-        ],
-        [
-          235.984126984127,
-          297.92063492063494
-        ],
-        [
-          238.984126984127,
-          286.92063492063494
-        ],
-        [
-          234.984126984127,
-          267.92063492063494
-        ],
-        [
-          257.984126984127,
-          257.92063492063494
-        ],
-        [
-          264.984126984127,
-          263.92063492063494
-        ],
-        [
-          256.984126984127,
-          272.92063492063494
-        ],
-        [
-          259.984126984127,
-          281.92063492063494
-        ],
-        [
-          284.984126984127,
-          287.92063492063494
-        ],
-        [
-          297.984126984127,
-          277.92063492063494
-        ],
-        [
-          288.984126984127,
-          269.92063492063494
-        ],
-        [
-          281.984126984127,
-          269.92063492063494
-        ],
-        [
-          283.984126984127,
-          263.92063492063494
-        ],
-        [
-          292.984126984127,
-          260.92063492063494
-        ],
-        [
-          308.984126984127,
-          235.9206349206349
-        ],
-        [
-          313.984126984127,
-          216.9206349206349
-        ],
-        [
-          309.984126984127,
-          207.9206349206349
-        ],
-        [
-          312.984126984127,
-          201.9206349206349
-        ],
-        [
-          308.984126984127,
-          184.9206349206349
-        ],
-        [
-          291.984126984127,
-          172.9206349206349
-        ],
-        [
-          269.984126984127,
-          158.9206349206349
-        ],
-        [
-          261.984126984127,
-          153.9206349206349
-        ],
-        [
-          264.984126984127,
-          141.9206349206349
-        ],
-        [
-          273.984126984127,
-          136.9206349206349
-        ],
-        [
-          278.984126984127,
-          129.9206349206349
-        ],
-        [
-          270.984126984127,
-          120.92063492063491
-        ]
-      ],
-      "shape_type": "polygon",
-      "flags": {
-        "occluded": true,
-        "truncated": false,
-        "male": true
-      }
-    },
-    {
-      "label": "person-2",
-      "line_color": null,
-      "fill_color": null,
-      "points": [
-        [
-          482,
-          85
-        ],
-        [
-          468,
-          90
-        ],
-        [
-          460,
-          110
-        ],
-        [
-          460,
-          127
-        ],
-        [
-          444,
-          137
-        ],
-        [
-          419,
-          153
-        ],
-        [
-          410,
-          163
-        ],
-        [
-          403,
-          168
-        ],
-        [
-          394,
-          170
-        ],
-        [
-          386,
-          168
-        ],
-        [
-          386,
-          184
-        ],
-        [
-          392,
-          182
-        ],
-        [
-          410,
-          187
-        ],
-        [
-          414,
-          192
-        ],
-        [
-          437,
-          189
-        ],
-        [
-          434,
-          204
-        ],
-        [
-          390,
-          195
-        ],
-        [
-          386,
-          195
-        ],
-        [
-          387,
-          208
-        ],
-        [
-          381,
-          212
-        ],
-        [
-          372,
-          212
-        ],
-        [
-          372,
-          216
-        ],
-        [
-          400,
-          270
-        ],
-        [
-          389,
-          272
-        ],
-        [
-          389,
-          274
-        ],
-        [
-          403,
-          282
-        ],
-        [
-          444,
-          283
-        ],
-        [
-          443,
-          259
-        ],
-        [
-          426,
-          244
-        ],
-        [
-          462,
-          256
-        ],
-        [
-          474,
-          270
-        ],
-        [
-          477,
-          280
-        ],
-        [
-          473,
-          289
-        ],
-        [
-          471,
-          296
-        ],
-        [
-          472,
-          317
-        ],
-        [
-          480,
-          332
-        ],
-        [
-          494,
-          335
-        ],
-        [
-          498,
-          329
-        ],
-        [
-          494,
-          308
-        ],
-        [
-          499,
-          297
-        ],
-        [
-          499,
-          90
-        ]
-      ],
-      "shape_type": "polygon",
-      "flags": {
-        "occluded": true,
-        "truncated": true,
-        "male": true
-      }
-    },
-    {
-      "label": "bottle",
-      "line_color": null,
-      "fill_color": null,
-      "points": [
-        [
-          374,
-          159
-        ],
-        [
-          369,
-          170
-        ],
-        [
-          369,
-          210
-        ],
-        [
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499.81422924901193, 90.33596837944665], [370.81422924901193, 170.33596837944665, 366.81422924901193, 173.33596837944665, 365.81422924901193, 182.33596837944665, 368.81422924901193, 185.33596837944665]], "area": 17254.0, "iscrowd": null, "image_id": 0, "category_id": 15}, {"id": 2, "segmentation": [[374.81422924901193, 159.33596837944665, 369.81422924901193, 170.33596837944665, 369.81422924901193, 210.33596837944665, 375.81422924901193, 212.33596837944665, 387.81422924901193, 209.33596837944665, 385.81422924901193, 185.33596837944665, 385.81422924901193, 168.33596837944665, 385.81422924901193, 165.33596837944665, 382.81422924901193, 159.33596837944665]], "area": 873.0, "iscrowd": null, "image_id": 0, "category_id": 5}, {"id": 3, "segmentation": [[260.936170212766, 22.563829787234056, 193.936170212766, 19.563829787234056, 124.93617021276599, 39.563829787234056, 89.93617021276599, 101.56382978723406, 81.93617021276599, 150.56382978723406, 108.93617021276599, 145.56382978723406, 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0.9361702127659877, 265.56382978723406, 27.936170212765987, 265.56382978723406, 29.936170212765987, 283.56382978723406, 63.93617021276599, 281.56382978723406, 89.93617021276599, 252.56382978723406, 100.93617021276599, 183.56382978723406, 108.93617021276599, 145.56382978723406, 81.93617021276599, 151.56382978723406]], "area": 15781.0, "iscrowd": null, "image_id": 1, "category_id": 6}, {"id": 5, "segmentation": [[413.936170212766, 168.56382978723406, 497.936170212766, 168.56382978723406, 497.936170212766, 256.56382978723406, 431.936170212766, 258.56382978723406, 430.936170212766, 236.56382978723406, 408.936170212766, 218.56382978723406]], "area": 7256.0, "iscrowd": null, "image_id": 1, "category_id": 7}, {"id": 6, "segmentation": [[204.936170212766, 108.56382978723406, 183.936170212766, 141.56382978723406, 166.936170212766, 150.56382978723406, 108.93617021276599, 203.56382978723406, 92.93617021276599, 228.56382978723406, 95.93617021276599, 244.56382978723406, 105.93617021276599, 244.56382978723406, 116.93617021276599, 223.56382978723406, 163.936170212766, 187.56382978723406, 147.936170212766, 212.56382978723406, 117.93617021276599, 222.56382978723406, 108.93617021276599, 243.56382978723406, 100.93617021276599, 325.56382978723406, 135.936170212766, 329.56382978723406, 148.936170212766, 319.56382978723406, 150.936170212766, 295.56382978723406, 169.936170212766, 272.56382978723406, 171.936170212766, 249.56382978723406, 178.936170212766, 246.56382978723406, 186.936170212766, 225.56382978723406, 214.936170212766, 219.56382978723406, 242.936170212766, 157.56382978723406, 228.936170212766, 146.56382978723406, 228.936170212766, 125.56382978723406, 216.936170212766, 112.56382978723406]], "area": 15203.0, "iscrowd": null, "image_id": 2, "category_id": 15}, {"id": 7, "segmentation": [[271.936170212766, 109.56382978723406, 249.936170212766, 110.56382978723406, 244.936170212766, 150.56382978723406, 215.936170212766, 219.56382978723406, 208.936170212766, 245.56382978723406, 214.936170212766, 220.56382978723406, 188.936170212766, 227.56382978723406, 170.936170212766, 246.56382978723406, 170.936170212766, 275.56382978723406, 221.936170212766, 278.56382978723406, 233.936170212766, 259.56382978723406, 246.936170212766, 253.56382978723406, 245.936170212766, 256.56382978723406, 242.936170212766, 251.56382978723406, 262.936170212766, 256.56382978723406, 304.936170212766, 226.56382978723406, 297.936170212766, 199.56382978723406, 308.936170212766, 164.56382978723406, 296.936170212766, 148.56382978723406]], "area": 11735.0, "iscrowd": null, "image_id": 2, "category_id": 15}, {"id": 8, "segmentation": [[308.936170212766, 115.56382978723406, 298.936170212766, 145.56382978723406, 309.936170212766, 166.56382978723406, 297.936170212766, 200.56382978723406, 305.936170212766, 228.56382978723406, 262.936170212766, 258.56382978723406, 252.936170212766, 284.56382978723406, 272.936170212766, 291.56382978723406, 281.936170212766, 250.56382978723406, 326.936170212766, 235.56382978723406, 351.936170212766, 239.56382978723406, 365.936170212766, 223.56382978723406, 371.936170212766, 187.56382978723406, 353.936170212766, 168.56382978723406, 344.936170212766, 143.56382978723406, 336.936170212766, 115.56382978723406]], "area": 7597.0, "iscrowd": null, "image_id": 2, "category_id": 15}, {"id": 9, "segmentation": [[308.936170212766, 242.56382978723406, 281.936170212766, 251.56382978723406, 270.936170212766, 287.56382978723406, 174.936170212766, 275.56382978723406, 148.936170212766, 296.56382978723406, 150.936170212766, 319.56382978723406, 159.936170212766, 328.56382978723406, 164.77327127659578, 375.0, 485.936170212766, 373.56382978723406, 497.936170212766, 336.56382978723406, 497.936170212766, 202.56382978723406, 453.936170212766, 193.56382978723406, 434.936170212766, 212.56382978723406, 367.936170212766, 224.56382978723406, 350.936170212766, 241.56382978723406]], "area": 44532.0, "iscrowd": null, "image_id": 2, "category_id": 9}, {"id": 10, "segmentation": [[425.936170212766, 82.56382978723406, 404.936170212766, 109.56382978723406, 400.936170212766, 114.56382978723406, 437.936170212766, 114.56382978723406, 448.936170212766, 102.56382978723406, 446.936170212766, 91.56382978723406]], "area": 996.0, "iscrowd": null, "image_id": 2, "category_id": 15}, {"id": 11, "segmentation": [[183.936170212766, 140.56382978723406, 125.93617021276599, 140.56382978723406, 110.93617021276599, 187.56382978723406, 22.936170212765987, 199.56382978723406, 18.936170212765987, 218.56382978723406, 22.936170212765987, 234.56382978723406, 93.93617021276599, 239.56382978723406, 91.93617021276599, 229.56382978723406, 110.93617021276599, 203.56382978723406], [103.93617021276599, 290.56382978723406, 58.93617021276599, 303.56382978723406, 97.93617021276599, 311.56382978723406], [348.936170212766, 146.56382978723406, 472.936170212766, 149.56382978723406, 477.936170212766, 162.56382978723406, 471.936170212766, 196.56382978723406, 453.936170212766, 192.56382978723406, 434.936170212766, 213.56382978723406, 368.936170212766, 226.56382978723406, 375.936170212766, 187.56382978723406, 353.936170212766, 164.56382978723406], [246.936170212766, 252.56382978723406, 219.936170212766, 277.56382978723406, 254.936170212766, 287.56382978723406, 261.936170212766, 256.56382978723406]], "area": 14001.0, "iscrowd": null, "image_id": 2, "category_id": 18}], "categories": [{"supercategory": null, "id": 0, "name": "_background_"}, {"supercategory": null, "id": 1, "name": "aeroplane"}, {"supercategory": null, "id": 2, "name": "bicycle"}, {"supercategory": null, "id": 3, "name": "bird"}, {"supercategory": null, "id": 4, "name": "boat"}, {"supercategory": null, "id": 5, "name": "bottle"}, {"supercategory": null, "id": 6, "name": "bus"}, {"supercategory": null, "id": 7, "name": "car"}, {"supercategory": null, "id": 8, "name": "cat"}, {"supercategory": null, "id": 9, "name": "chair"}, {"supercategory": null, "id": 10, "name": "cow"}, {"supercategory": null, "id": 11, "name": "diningtable"}, {"supercategory": null, "id": 12, "name": "dog"}, {"supercategory": null, "id": 13, "name": "horse"}, {"supercategory": null, "id": 14, "name": "motorbike"}, {"supercategory": null, "id": 15, "name": "person"}, {"supercategory": null, "id": 16, "name": "potted plant"}, {"supercategory": null, "id": 17, "name": "sheep"}, {"supercategory": null, "id": 18, "name": "sofa"}, {"supercategory": null, "id": 19, "name": "train"}, {"supercategory": null, "id": 20, "name": "tv/monitor"}]}
\ No newline at end of file

DataAnnotation/labelme/examples/instance_segmentation/data_dataset_voc/class_names.txt

-_background_
-aeroplane
-bicycle
-bird
-boat
-bottle
-bus
-car
-cat
-chair
-cow
-diningtable
-dog
-horse
-motorbike
-person
-potted plant
-sheep
-sofa
-train
-tv/monitor
\ No newline at end of file

DataAnnotation/labelme/examples/instance_segmentation/labelme2coco.py

-#!/usr/bin/env python
-
-import argparse
-import collections
-import datetime
-import glob
-import json
-import os
-import os.path as osp
-import sys
-
-import numpy as np
-import PIL.Image
-
-import labelme
-
-try:
-    import pycocotools.mask
-except ImportError:
-    print('Please install pycocotools:\n\n    pip install pycocotools\n')
-    sys.exit(1)
-
-
-def main():
-    parser = argparse.ArgumentParser(
-        formatter_class=argparse.ArgumentDefaultsHelpFormatter
-    )
-    parser.add_argument('input_dir', help='input annotated directory')
-    parser.add_argument('output_dir', help='output dataset directory')
-    parser.add_argument('--labels', help='labels file', required=True)
-    args = parser.parse_args()
-
-    if osp.exists(args.output_dir):
-        print('Output directory already exists:', args.output_dir)
-        sys.exit(1)
-    os.makedirs(args.output_dir)
-    os.makedirs(osp.join(args.output_dir, 'JPEGImages'))
-    print('Creating dataset:', args.output_dir)
-
-    now = datetime.datetime.now()
-
-    data = dict(
-        info=dict(
-            description=None,
-            url=None,
-            version=None,
-            year=now.year,
-            contributor=None,
-            date_created=now.strftime('%Y-%m-%d %H:%M:%S.%f'),
-        ),
-        licenses=[dict(
-            url=None,
-            id=0,
-            name=None,
-        )],
-        images=[
-            # license, url, file_name, height, width, date_captured, id
-        ],
-        type='instances',
-        annotations=[
-            # segmentation, area, iscrowd, image_id, bbox, category_id, id
-        ],
-        categories=[
-            # supercategory, id, name
-        ],
-    )
-
-    class_name_to_id = {}
-    for i, line in enumerate(open(args.labels).readlines()):
-        class_id = i - 1  # starts with -1
-        class_name = line.strip()
-        if class_id == -1:
-            assert class_name == '__ignore__'
-            continue
-        class_name_to_id[class_name] = class_id
-        data['categories'].append(dict(
-            supercategory=None,
-            id=class_id,
-            name=class_name,
-        ))
-
-    out_ann_file = osp.join(args.output_dir, 'annotations.json')
-    label_files = glob.glob(osp.join(args.input_dir, '*.json'))
-    for image_id, label_file in enumerate(label_files):
-        print('Generating dataset from:', label_file)
-        with open(label_file) as f:
-            label_data = json.load(f)
-
-        base = osp.splitext(osp.basename(label_file))[0]
-        out_img_file = osp.join(
-            args.output_dir, 'JPEGImages', base + '.jpg'
-        )
-
-        img_file = osp.join(
-            osp.dirname(label_file), label_data['imagePath']
-        )
-        img = np.asarray(PIL.Image.open(img_file))
-        PIL.Image.fromarray(img).save(out_img_file)
-        data['images'].append(dict(
-            license=0,
-            url=None,
-            file_name=osp.relpath(out_img_file, osp.dirname(out_ann_file)),
-            height=img.shape[0],
-            width=img.shape[1],
-            date_captured=None,
-            id=image_id,
-        ))
-
-        masks = {}                                     # for area
-        segmentations = collections.defaultdict(list)  # for segmentation
-        for shape in label_data['shapes']:
-            points = shape['points']
-            label = shape['label']
-            shape_type = shape.get('shape_type', None)
-            mask = labelme.utils.shape_to_mask(
-                img.shape[:2], points, shape_type
-            )
-
-            if label in masks:
-                masks[label] = masks[label] | mask
-            else:
-                masks[label] = mask
-
-            points = np.asarray(points).flatten().tolist()
-            segmentations[label].append(points)
-
-        for label, mask in masks.items():
-            cls_name = label.split('-')[0]
-            if cls_name not in class_name_to_id:
-                continue
-            cls_id = class_name_to_id[cls_name]
-
-            mask = np.asfortranarray(mask.astype(np.uint8))
-            mask = pycocotools.mask.encode(mask)
-            area = float(pycocotools.mask.area(mask))
-            bbox = pycocotools.mask.toBbox(mask).flatten().tolist()
-
-            data['annotations'].append(dict(
-                id=len(data['annotations']),
-                image_id=image_id,
-                category_id=cls_id,
-                segmentation=segmentations[label],
-                area=area,
-                bbox=bbox,
-                iscrowd=0,
-            ))
-
-    with open(out_ann_file, 'w') as f:
-        json.dump(data, f)
-
-
-if __name__ == '__main__':
-    main()

DataAnnotation/labelme/examples/instance_segmentation/labelme2voc.py

-#!/usr/bin/env python
-
-from __future__ import print_function
-
-import argparse
-import glob
-import json
-import os
-import os.path as osp
-import sys
-
-import numpy as np
-import PIL.Image
-
-import labelme
-
-
-def main():
-    parser = argparse.ArgumentParser(
-        formatter_class=argparse.ArgumentDefaultsHelpFormatter
-    )
-    parser.add_argument('input_dir', help='input annotated directory')
-    parser.add_argument('output_dir', help='output dataset directory')
-    parser.add_argument('--labels', help='labels file', required=True)
-    args = parser.parse_args()
-
-    if osp.exists(args.output_dir):
-        print('Output directory already exists:', args.output_dir)
-        sys.exit(1)
-    os.makedirs(args.output_dir)
-    os.makedirs(osp.join(args.output_dir, 'JPEGImages'))
-    os.makedirs(osp.join(args.output_dir, 'SegmentationClass'))
-    os.makedirs(osp.join(args.output_dir, 'SegmentationClassPNG'))
-    os.makedirs(osp.join(args.output_dir, 'SegmentationClassVisualization'))
-    os.makedirs(osp.join(args.output_dir, 'SegmentationObject'))
-    os.makedirs(osp.join(args.output_dir, 'SegmentationObjectPNG'))
-    os.makedirs(osp.join(args.output_dir, 'SegmentationObjectVisualization'))
-    print('Creating dataset:', args.output_dir)
-
-    class_names = []
-    class_name_to_id = {}
-    for i, line in enumerate(open(args.labels).readlines()):
-        class_id = i - 1  # starts with -1
-        class_name = line.strip()
-        class_name_to_id[class_name] = class_id
-        if class_id == -1:
-            assert class_name == '__ignore__'
-            continue
-        elif class_id == 0:
-            assert class_name == '_background_'
-        class_names.append(class_name)
-    class_names = tuple(class_names)
-    print('class_names:', class_names)
-    out_class_names_file = osp.join(args.output_dir, 'class_names.txt')
-    with open(out_class_names_file, 'w') as f:
-        f.writelines('\n'.join(class_names))
-    print('Saved class_names:', out_class_names_file)
-
-    colormap = labelme.utils.label_colormap(255)
-
-    for label_file in glob.glob(osp.join(args.input_dir, '*.json')):
-        print('Generating dataset from:', label_file)
-        with open(label_file) as f:
-            base = osp.splitext(osp.basename(label_file))[0]
-            out_img_file = osp.join(
-                args.output_dir, 'JPEGImages', base + '.jpg')
-            out_cls_file = osp.join(
-                args.output_dir, 'SegmentationClass', base + '.npy')
-            out_clsp_file = osp.join(
-                args.output_dir, 'SegmentationClassPNG', base + '.png')
-            out_clsv_file = osp.join(
-                args.output_dir,
-                'SegmentationClassVisualization',
-                base + '.jpg',
-            )
-            out_ins_file = osp.join(
-                args.output_dir, 'SegmentationObject', base + '.npy')
-            out_insp_file = osp.join(
-                args.output_dir, 'SegmentationObjectPNG', base + '.png')
-            out_insv_file = osp.join(
-                args.output_dir,
-                'SegmentationObjectVisualization',
-                base + '.jpg',
-            )
-
-            data = json.load(f)
-
-            img_file = osp.join(osp.dirname(label_file), data['imagePath'])
-            img = np.asarray(PIL.Image.open(img_file))
-            PIL.Image.fromarray(img).save(out_img_file)
-
-            cls, ins = labelme.utils.shapes_to_label(
-                img_shape=img.shape,
-                shapes=data['shapes'],
-                label_name_to_value=class_name_to_id,
-                type='instance',
-            )
-            ins[cls == -1] = 0  # ignore it.
-
-            # class label
-            labelme.utils.lblsave(out_clsp_file, cls)
-            np.save(out_cls_file, cls)
-            clsv = labelme.utils.draw_label(
-                cls, img, class_names, colormap=colormap)
-            PIL.Image.fromarray(clsv).save(out_clsv_file)
-
-            # instance label
-            labelme.utils.lblsave(out_insp_file, ins)
-            np.save(out_ins_file, ins)
-            instance_ids = np.unique(ins)
-            instance_names = [str(i) for i in range(max(instance_ids) + 1)]
-            insv = labelme.utils.draw_label(ins, img, instance_names)
-            PIL.Image.fromarray(insv).save(out_insv_file)
-
-
-if __name__ == '__main__':
-    main()

DataAnnotation/labelme/examples/instance_segmentation/labels.txt

-__ignore__
-_background_
-aeroplane
-bicycle
-bird
-boat
-bottle
-bus
-car
-cat
-chair
-cow
-diningtable
-dog
-horse
-motorbike
-person
-potted plant
-sheep
-sofa
-train
-tv/monitor
\ No newline at end of file

DataAnnotation/labelme/examples/primitives/primitives.json

-{
-  "version": "3.5.0",
-  "flags": {},
-  "shapes": [
-    {
-      "label": "rectangle",
-      "line_color": null,
-      "fill_color": null,
-      "points": [
-        [
-          32,
-          35
-        ],
-        [
-          132,
-          135
-        ]
-      ],
-      "shape_type": "rectangle"
-    },
-    {
-      "label": "circle",
-      "line_color": null,
-      "fill_color": null,
-      "points": [
-        [
-          195,
-          84
-        ],
-        [
-          225,
-          125
-        ]
-      ],
-      "shape_type": "circle"
-    },
-    {
-      "label": "rectangle",
-      "line_color": null,
-      "fill_color": null,
-      "points": [
-        [
-          391,
-          33
-        ],
-        [
-          542,
-          135
-        ]
-      ],
-      "shape_type": "rectangle"
-    },
-    {
-      "label": "polygon",
-      "line_color": null,
-      "fill_color": null,
-      "points": [
-        [
-          69,
-          318
-        ],
-        [
-          45,
-          403
-        ],
-        [
-          173,
-          406
-        ],
-        [
-          198,
-          321
-        ]
-      ],
-      "shape_type": "polygon"
-    },
-    {
-      "label": "line",
-      "line_color": null,
-      "fill_color": null,
-      "points": [
-        [
-          188,
-          178
-        ],
-        [
-          160,
-          224
-        ]
-      ],
-      "shape_type": "line"
-    },
-    {
-      "label": "point",
-      "line_color": null,
-      "fill_color": null,
-      "points": [
-        [
-          345,
-          174
-        ]
-      ],
-      "shape_type": "point"
-    },
-    {
-      "label": "line_strip",
-      "line_color": null,
-      "fill_color": null,
-      "points": [
-        [
-          441,
-          181
-        ],
-        [
-          403,
-          274
-        ],
-        [
-          545,
-          275
-        ]
-      ],
-      "shape_type": "linestrip"
-    }
-  ],
-  "lineColor": [
-    0,
-    255,
-    0,
-    128
-  ],
-  "fillColor": [
-    255,
-    0,
-    0,
-    128
-  ],
-  "imagePath": "primitives.jpg",
-  "imageData": null
-}
\ No newline at end of file

DataAnnotation/labelme/examples/semantic_segmentation/README.md

-# Semantic Segmentation Example
-
-## Annotation
-
-```bash
-labelme data_annotated --labels labels.txt --nodata
-```
-
-![](.readme/annotation.jpg)
-
-
-## Convert to VOC-format Dataset
-
-```bash
-# It generates:
-#   - data_dataset_voc/JPEGImages
-#   - data_dataset_voc/SegmentationClass
-#   - data_dataset_voc/SegmentationClassVisualization
-./labelme2voc.py data_annotated data_dataset_voc --labels labels.txt
-```
-
-<img src="data_dataset_voc/JPEGImages/2011_000003.jpg" width="33%" /> <img src="data_dataset_voc/SegmentationClassPNG/2011_000003.png" width="33%" /> <img src="data_dataset_voc/SegmentationClassVisualization/2011_000003.jpg" width="33%" />
-
-Fig 1. JPEG image (left), PNG label (center), JPEG label visualization (right)  
-
-
-Note that the label file contains only very low label values (ex. `0, 4, 14`), and
-`255` indicates the `__ignore__` label value (`-1` in the npy file).  
-You can see the label PNG file by following.
-
-```bash
-labelme_draw_label_png data_dataset_voc/SegmentationClassPNG/2011_000003.png
-```
-
-<img src=".readme/draw_label_png.jpg" width="33%" />

DataAnnotation/labelme/examples/semantic_segmentation/data_annotated/2011_000003.json

-{
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-      "line_color": null,
-      "fill_color": null,
-      "points": [
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-        ],
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-        [
-          194.8142292490119,
-          222.33596837944665
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-          199.8142292490119,
-          227.33596837944665
-        ],
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-          234.33596837944665
-        ],
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-          309.81422924901193,
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-          130.33596837944665
-        ],
-        [
-          270.81422924901193,
-          121.33596837944665
-        ]
-      ]
-    },
-    {
-      "label": "person",
-      "line_color": null,
-      "fill_color": null,
-      "points": [
-        [
-          482.81422924901193,
-          85.33596837944665
-        ],
-        [
-          468.81422924901193,
-          90.33596837944665
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-        [
-          460.81422924901193,
-          110.33596837944665
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-          460.81422924901193,
-          127.33596837944665
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-          444.81422924901193,
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-          184.33596837944665
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-          182.33596837944665
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-          187.33596837944665
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-          414.81422924901193,
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-      "fill_color": null,
-      "points": [
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-  "lineColor": [
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-    255,
-    0,
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-  "fillColor": [
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-    0,
-    128
-  ],
-  "imagePath": "2011_000003.jpg",
-  "imageData": null
-}
\ No newline at end of file

DataAnnotation/labelme/examples/semantic_segmentation/data_annotated/2011_000006.json

-{
-  "shapes": [
-    {
-      "label": "person",
-      "line_color": null,
-      "fill_color": null,
-      "points": [
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-        [
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-      "label": "chair",
-      "line_color": null,
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-      "label": "person",
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-      ]
-    },
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-      "label": "__ignore__",
-      "line_color": null,
-      "fill_color": null,
-      "points": [
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-    },
-    {
-      "label": "sofa",
-      "line_color": null,
-      "fill_color": null,
-      "points": [
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-    {
-      "label": "sofa",
-      "line_color": null,
-      "fill_color": null,
-      "points": [
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-      ]
-    },
-    {
-      "label": "sofa",
-      "line_color": null,
-      "fill_color": null,
-      "points": [
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-        [
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-          164.56382978723406
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-      ]
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-    {
-      "label": "sofa",
-      "line_color": null,
-      "fill_color": null,
-      "points": [
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-  "imagePath": "2011_000006.jpg",
-  "imageData": null
-}
\ No newline at end of file

DataAnnotation/labelme/examples/semantic_segmentation/data_annotated/2011_000025.json

-{
-  "shapes": [
-    {
-      "label": "bus",
-      "line_color": null,
-      "fill_color": null,
-      "points": [
-        [
-          260.936170212766,
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-        [
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-        [
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-      ]
-    },
-    {
-      "label": "bus",
-      "line_color": null,
-      "fill_color": null,
-      "points": [
-        [
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-          115.56382978723406
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-        ],
-        [
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-          151.56382978723406
-        ]
-      ]
-    },
-    {
-      "label": "car",
-      "line_color": null,
-      "fill_color": null,
-      "points": [
-        [
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-          258.56382978723406
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-        [
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-          236.56382978723406
-        ],
-        [
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-          218.56382978723406
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-      ]
-    }
-  ],
-  "lineColor": [
-    0,
-    255,
-    0,
-    128
-  ],
-  "fillColor": [
-    255,
-    0,
-    0,
-    128
-  ],
-  "imagePath": "2011_000025.jpg",
-  "imageData": null
-}
\ No newline at end of file

DataAnnotation/labelme/examples/semantic_segmentation/data_dataset_voc/class_names.txt

-_background_
-aeroplane
-bicycle
-bird
-boat
-bottle
-bus
-car
-cat
-chair
-cow
-diningtable
-dog
-horse
-motorbike
-person
-potted plant
-sheep
-sofa
-train
-tv/monitor
\ No newline at end of file

DataAnnotation/labelme/examples/semantic_segmentation/labelme2voc.py

-#!/usr/bin/env python
-
-from __future__ import print_function
-
-import argparse
-import glob
-import json
-import os
-import os.path as osp
-import sys
-
-import numpy as np
-import PIL.Image
-
-import labelme
-
-
-def main():
-    parser = argparse.ArgumentParser(
-        formatter_class=argparse.ArgumentDefaultsHelpFormatter
-    )
-    parser.add_argument('input_dir', help='input annotated directory')
-    parser.add_argument('output_dir', help='output dataset directory')
-    parser.add_argument('--labels', help='labels file', required=True)
-    args = parser.parse_args()
-
-    if osp.exists(args.output_dir):
-        print('Output directory already exists:', args.output_dir)
-        sys.exit(1)
-    os.makedirs(args.output_dir)
-    os.makedirs(osp.join(args.output_dir, 'JPEGImages'))
-    os.makedirs(osp.join(args.output_dir, 'SegmentationClass'))
-    os.makedirs(osp.join(args.output_dir, 'SegmentationClassPNG'))
-    os.makedirs(osp.join(args.output_dir, 'SegmentationClassVisualization'))
-    print('Creating dataset:', args.output_dir)
-
-    class_names = []
-    class_name_to_id = {}
-    for i, line in enumerate(open(args.labels).readlines()):
-        class_id = i - 1  # starts with -1
-        class_name = line.strip()
-        class_name_to_id[class_name] = class_id
-        if class_id == -1:
-            assert class_name == '__ignore__'
-            continue
-        elif class_id == 0:
-            assert class_name == '_background_'
-        class_names.append(class_name)
-    class_names = tuple(class_names)
-    print('class_names:', class_names)
-    out_class_names_file = osp.join(args.output_dir, 'class_names.txt')
-    with open(out_class_names_file, 'w') as f:
-        f.writelines('\n'.join(class_names))
-    print('Saved class_names:', out_class_names_file)
-
-    colormap = labelme.utils.label_colormap(255)
-
-    for label_file in glob.glob(osp.join(args.input_dir, '*.json')):
-        print('Generating dataset from:', label_file)
-        with open(label_file) as f:
-            base = osp.splitext(osp.basename(label_file))[0]
-            out_img_file = osp.join(
-                args.output_dir, 'JPEGImages', base + '.jpg')
-            out_lbl_file = osp.join(
-                args.output_dir, 'SegmentationClass', base + '.npy')
-            out_png_file = osp.join(
-                args.output_dir, 'SegmentationClassPNG', base + '.png')
-            out_viz_file = osp.join(
-                args.output_dir,
-                'SegmentationClassVisualization',
-                base + '.jpg',
-            )
-
-            data = json.load(f)
-
-            img_file = osp.join(osp.dirname(label_file), data['imagePath'])
-            img = np.asarray(PIL.Image.open(img_file))
-            PIL.Image.fromarray(img).save(out_img_file)
-
-            lbl = labelme.utils.shapes_to_label(
-                img_shape=img.shape,
-                shapes=data['shapes'],
-                label_name_to_value=class_name_to_id,
-            )
-            labelme.utils.lblsave(out_png_file, lbl)
-
-            np.save(out_lbl_file, lbl)
-
-            viz = labelme.utils.draw_label(
-                lbl, img, class_names, colormap=colormap)
-            PIL.Image.fromarray(viz).save(out_viz_file)
-
-
-if __name__ == '__main__':
-    main()

DataAnnotation/labelme/examples/semantic_segmentation/labels.txt

-__ignore__
-_background_
-aeroplane
-bicycle
-bird
-boat
-bottle
-bus
-car
-cat
-chair
-cow
-diningtable
-dog
-horse
-motorbike
-person
-potted plant
-sheep
-sofa
-train
-tv/monitor
\ No newline at end of file

DataAnnotation/labelme/examples/tutorial/README.md

-# Tutorial (Single Image Example)
-
-## Annotation
-
-```bash
-labelme apc2016_obj3.jpg -O apc2016_obj3.json
-```
-
-![](.readme/annotation.jpg)
-
-
-## Visualization
-
-To view the json file quickly, you can use utility script:
-
-```bash
-labelme_draw_json apc2016_obj3.json
-```
-
-<img src=".readme/draw_json.jpg" width="70%" />
-
-
-## Convert to Dataset
-
-To convert the json to set of image and label, you can run following:
-
-
-```bash
-labelme_json_to_dataset apc2016_obj3.json -o apc2016_obj3_json
-```
-
-It generates standard files from the JSON file.
-
-- [img.png](apc2016_obj3_json/img.png): Image file.
-- [label.png](apc2016_obj3_json/label.png): uint8 label file.
-- [label_viz.png](apc2016_obj3_json/label_viz.png): Visualization of `label.png`.
-- [label_names.txt](apc2016_obj3_json/label_names.txt): Label names for values in `label.png`.
-
-## How to load label PNG file?
-
-Note that loading `label.png` is a bit difficult
-(`scipy.misc.imread`, `skimage.io.imread` may not work correctly),
-and please use `PIL.Image.open` to avoid unexpected behavior:
-
-```python
-# see load_label_png.py also.
->>> import numpy as np
->>> import PIL.Image
-
->>> label_png = 'apc2016_obj3_json/label.png'
->>> lbl = np.asarray(PIL.Image.open(label_png))
->>> print(lbl.dtype)
-dtype('uint8')
->>> np.unique(lbl)
-array([0, 1, 2, 3], dtype=uint8)
->>> lbl.shape
-(907, 1210)
-```
-
-Also, you can see the label PNG file by:
-
-```python
-labelme_draw_label_png apc2016_obj3_json/label.png
-```
-
-<img src=".readme/draw_label_png.jpg" width="35%" />

DataAnnotation/labelme/examples/tutorial/apc2016_obj3.json

-{
-  "shapes": [
-    {
-      "label": "shelf",
-      "line_color": null,
-      "fill_color": null,
-      "points": [
-        [
-          7.942307692307736,
-          79.82692307692312
-        ],
-        [
-          171.94230769230774,
-          713.8269230769231
-        ],
-        [
-          968.9423076923077,
-          732.8269230769231
-        ],
-        [
-          1181.9423076923076,
-          109.82692307692312
-        ]
-      ]
-    },
-    {
-      "label": "highland_6539_self_stick_notes",
-      "line_color": null,
-      "fill_color": null,
-      "points": [
-        [
-          430.16339869281046,
-          516.2450980392157
-        ],
-        [
-          390.9477124183006,
-          606.4411764705883
-        ],
-        [
-          398.7908496732026,
-          697.2908496732026
-        ],
-        [
-          522.3202614379085,
-          711.6699346405229
-        ],
-        [
-          762.18954248366,
-          721.4738562091503
-        ],
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-          777.2222222222222,
-          634.5457516339869
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-        [
-          761.5359477124183,
-          537.8137254901961
-        ],
-        [
-          634.0849673202614,
-          518.8594771241831
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-        [
-          573.3006535947712,
-          512.9771241830066
-        ],
-        [
-          534.0849673202614,
-          513.6307189542484
-        ]
-      ]
-    },
-    {
-      "label": "mead_index_cards",
-      "line_color": null,
-      "fill_color": null,
-      "points": [
-        [
-          447.156862745098,
-          394.6764705882353
-        ],
-        [
-          410.55555555555554,
-          480.95098039215685
-        ],
-        [
-          415.1307189542483,
-          522.781045751634
-        ],
-        [
-          422.9738562091503,
-          522.781045751634
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-          427.5490196078431,
-          515.5915032679738
-        ],
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-          570.032679738562,
-          512.3235294117648
-        ],
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-          732.1241830065359,
-          528.0098039215686
-        ],
-        [
-          733.4313725490196,
-          492.71568627450984
-        ],
-        [
-          724.9346405228757,
-          407.0947712418301
-        ]
-      ]
-    },
-    {
-      "label": "kong_air_dog_squeakair_tennis_ball",
-      "line_color": null,
-      "fill_color": null,
-      "points": [
-        [
-          419.05228758169926,
-          266.5718954248366
-        ],
-        [
-          343.235294117647,
-          303.1732026143791
-        ],
-        [
-          511.2091503267974,
-          318.859477124183
-        ],
-        [
-          519.7058823529411,
-          334.5457516339869
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"
-}
\ No newline at end of file

DataAnnotation/labelme/examples/tutorial/apc2016_obj3_json/info.yaml

-label_names:
-- _background_
-- shelf
-- highland_6539_self_stick_notes
-- mead_index_cards
-- kong_air_dog_squeakair_tennis_ball

DataAnnotation/labelme/examples/tutorial/apc2016_obj3_json/label_names.txt

-_background_
-shelf
-highland_6539_self_stick_notes
-mead_index_cards
-kong_air_dog_squeakair_tennis_ball

DataAnnotation/labelme/examples/tutorial/load_label_png.py

-#!/usr/bin/env python
-
-from __future__ import print_function
-
-import os.path as osp
-
-import numpy as np
-import PIL.Image
-
-
-here = osp.dirname(osp.abspath(__file__))
-
-
-def main():
-    label_png = osp.join(here, 'apc2016_obj3_json/label.png')
-    print('Loading:', label_png)
-    print()
-
-    lbl = np.asarray(PIL.Image.open(label_png))
-    labels = np.unique(lbl)
-
-    label_names_txt = osp.join(here, 'apc2016_obj3_json/label_names.txt')
-    label_names = [name.strip() for name in open(label_names_txt)]
-    print('# of labels:', len(labels))
-    print('# of label_names:', len(label_names))
-    if len(labels) != len(label_names):
-        print('Number of unique labels and label_names must be same.')
-        quit(1)
-    print()
-
-    print('label: label_name')
-    for label, label_name in zip(labels, label_names):
-        print('%d: %s' % (label, label_name))
-
-
-if __name__ == '__main__':
-    main()

DataAnnotation/labelme/examples/video_annotation/README.md

-# Video Annotation Example
-
-
-## Annotation
-
-```bash
-labelme data_annotated --labels labels.txt --nodata --keep-prev
-```
-
-<img src=".readme/00000100.jpg" width="49%" /> <img src=".readme/00000101.jpg" width="49%" />
-
-*Fig 1. Video annotation example. A frame (left), The next frame (right).*
-
-
-<img src=".readme/data_annotated.gif" width="98%" />
-
-*Fig 2. Visualization of video semantic segmentation.*
-
-
-## How to Convert a Video File to Images for Annotation?
-
-```bash
-# Download and install software for converting a video file (MP4) to images
-wget https://raw.githubusercontent.com/wkentaro/dotfiles/f3c5ad1f47834818d4f123c36ed59a5943709518/local/bin/video_to_images
-pip install imageio imageio-ffmpeg tqdm
-
-python video_to_images your_video.mp4  # this creates your_video/ directory
-ls your_video/
-
-labelme your_video/
-```

DataAnnotation/labelme/examples/video_annotation/data_annotated/00000100.json

-{
-  "flags": {},
-  "shapes": [
-    {
-      "label": "track",
-      "line_color": null,
-      "fill_color": null,
-      "points": [
-        [
-          634,
-          204
-        ],
-        [
-          604,
-          275
-        ],
-        [
-          603,
-          340
-        ],
-        [
-          622,
-          363
-        ],
-        [
-          639,
-          363
-        ],
-        [
-          649,
-          354
-        ],
-        [
-          682,
-          383
-        ],
-        [
-          733,
-          390
-        ],
-        [
-          748,
-          364
-        ],
-        [
-          827,
-          359
-        ],
-        [
-          829,
-          250
-        ],
-        [
-          800,
-          194
-        ],
-        [
-          775,
-          185
-        ],
-        [
-          740,
-          199
-        ]
-      ]
-    },
-    {
-      "label": "track",
-      "line_color": null,
-      "fill_color": null,
-      "points": [
-        [
-          860,
-          190
-        ],
-        [
-          997,
-          186
-        ],
-        [
-          998,
-          305
-        ],
-        [
-          924,
-          320
-        ],
-        [
-          905,
-          352
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-        [
-          877,
-          353
-        ],
-        [
-          869,
-          245
-        ],
-        [
-          879,
-          222
-        ]
-      ]
-    },
-    {
-      "label": "car",
-      "line_color": null,
-      "fill_color": null,
-      "points": [
-        [
-          924,
-          321
-        ],
-        [
-          905,
-          352
-        ],
-        [
-          909,
-          388
-        ],
-        [
-          936,
-          404
-        ],
-        [
-          959,
-          411
-        ],
-        [
-          966,
-          431
-        ],
-        [
-          1000.0,
-          432.0
-        ],
-        [
-          1000.0,
-          306.0
-        ]
-      ]
-    }
-  ],
-  "lineColor": [
-    0,
-    255,
-    0,
-    128
-  ],
-  "fillColor": [
-    255,
-    0,
-    0,
-    128
-  ],
-  "imagePath": "00000100.jpg",
-  "imageData": null
-}
\ No newline at end of file

DataAnnotation/labelme/examples/video_annotation/data_annotated/00000101.json

-{
-  "flags": {},
-  "shapes": [
-    {
-      "label": "track",
-      "line_color": null,
-      "fill_color": null,
-      "points": [
-        [
-          614.0,
-          204.0
-        ],
-        [
-          584.0,
-          275.0
-        ],
-        [
-          583.0,
-          340.0
-        ],
-        [
-          602.0,
-          363.0
-        ],
-        [
-          619.0,
-          363.0
-        ],
-        [
-          629.0,
-          354.0
-        ],
-        [
-          662.0,
-          383.0
-        ],
-        [
-          713.0,
-          390.0
-        ],
-        [
-          728.0,
-          364.0
-        ],
-        [
-          827.0,
-          358.0
-        ],
-        [
-          825.0,
-          249.0
-        ],
-        [
-          801.0,
-          200.0
-        ],
-        [
-          757.0,
-          194.0
-        ],
-        [
-          720.0,
-          199.0
-        ]
-      ]
-    },
-    {
-      "label": "track",
-      "line_color": null,
-      "fill_color": null,
-      "points": [
-        [
-          860.0,
-          190.0
-        ],
-        [
-          997.0,
-          186.0
-        ],
-        [
-          998.0,
-          305.0
-        ],
-        [
-          924.0,
-          320.0
-        ],
-        [
-          905.0,
-          352.0
-        ],
-        [
-          877.0,
-          353.0
-        ],
-        [
-          869.0,
-          245.0
-        ],
-        [
-          879.0,
-          222.0
-        ]
-      ]
-    },
-    {
-      "label": "car",
-      "line_color": null,
-      "fill_color": null,
-      "points": [
-        [
-          924.0,
-          321.0
-        ],
-        [
-          905.0,
-          352.0
-        ],
-        [
-          909.0,
-          388.0
-        ],
-        [
-          936.0,
-          404.0
-        ],
-        [
-          959.0,
-          411.0
-        ],
-        [
-          966.0,
-          431.0
-        ],
-        [
-          1000.0,
-          432.0
-        ],
-        [
-          1000.0,
-          306.0
-        ]
-      ]
-    }
-  ],
-  "lineColor": [
-    0,
-    255,
-    0,
-    128
-  ],
-  "fillColor": [
-    255,
-    0,
-    0,
-    128
-  ],
-  "imagePath": "00000101.jpg",
-  "imageData": null
-}
\ No newline at end of file

DataAnnotation/labelme/examples/video_annotation/data_annotated/00000102.json

-{
-  "flags": {},
-  "shapes": [
-    {
-      "label": "track",
-      "line_color": null,
-      "fill_color": null,
-      "points": [
-        [
-          593.0,
-          204.0
-        ],
-        [
-          563.0,
-          275.0
-        ],
-        [
-          562.0,
-          340.0
-        ],
-        [
-          581.0,
-          363.0
-        ],
-        [
-          598.0,
-          363.0
-        ],
-        [
-          608.0,
-          354.0
-        ],
-        [
-          641.0,
-          383.0
-        ],
-        [
-          692.0,
-          390.0
-        ],
-        [
-          707.0,
-          364.0
-        ],
-        [
-          827.0,
-          358.0
-        ],
-        [
-          823.0,
-          243.0
-        ],
-        [
-          802.0,
-          199.0
-        ],
-        [
-          736.0,
-          194.0
-        ],
-        [
-          699.0,
-          199.0
-        ]
-      ]
-    },
-    {
-      "label": "track",
-      "line_color": null,
-      "fill_color": null,
-      "points": [
-        [
-          860.0,
-          190.0
-        ],
-        [
-          997.0,
-          186.0
-        ],
-        [
-          998.0,
-          305.0
-        ],
-        [
-          924.0,
-          320.0
-        ],
-        [
-          905.0,
-          352.0
-        ],
-        [
-          877.0,
-          353.0
-        ],
-        [
-          869.0,
-          245.0
-        ],
-        [
-          879.0,
-          222.0
-        ]
-      ]
-    },
-    {
-      "label": "car",
-      "line_color": null,
-      "fill_color": null,
-      "points": [
-        [
-          924.0,
-          321.0
-        ],
-        [
-          905.0,
-          352.0
-        ],
-        [
-          909.0,
-          388.0
-        ],
-        [
-          936.0,
-          404.0
-        ],
-        [
-          959.0,
-          411.0
-        ],
-        [
-          966.0,
-          431.0
-        ],
-        [
-          1000.0,
-          432.0
-        ],
-        [
-          1000.0,
-          306.0
-        ]
-      ]
-    }
-  ],
-  "lineColor": [
-    0,
-    255,
-    0,
-    128
-  ],
-  "fillColor": [
-    255,
-    0,
-    0,
-    128
-  ],
-  "imagePath": "00000102.jpg",
-  "imageData": null
-}
\ No newline at end of file

DataAnnotation/labelme/examples/video_annotation/data_annotated/00000103.json

-{
-  "flags": {},
-  "shapes": [
-    {
-      "label": "track",
-      "line_color": null,
-      "fill_color": null,
-      "points": [
-        [
-          573.0,
-          207.0
-        ],
-        [
-          543.0,
-          278.0
-        ],
-        [
-          542.0,
-          343.0
-        ],
-        [
-          561.0,
-          366.0
-        ],
-        [
-          578.0,
-          366.0
-        ],
-        [
-          588.0,
-          357.0
-        ],
-        [
-          621.0,
-          386.0
-        ],
-        [
-          672.0,
-          393.0
-        ],
-        [
-          687.0,
-          367.0
-        ],
-        [
-          829.0,
-          354.0
-        ],
-        [
-          821.0,
-          236.0
-        ],
-        [
-          801.0,
-          199.0
-        ],
-        [
-          716.0,
-          197.0
-        ],
-        [
-          679.0,
-          202.0
-        ]
-      ]
-    },
-    {
-      "label": "track",
-      "line_color": null,
-      "fill_color": null,
-      "points": [
-        [
-          860.0,
-          190.0
-        ],
-        [
-          997.0,
-          186.0
-        ],
-        [
-          998.0,
-          305.0
-        ],
-        [
-          924.0,
-          320.0
-        ],
-        [
-          905.0,
-          352.0
-        ],
-        [
-          877.0,
-          353.0
-        ],
-        [
-          869.0,
-          245.0
-        ],
-        [
-          879.0,
-          222.0
-        ]
-      ]
-    },
-    {
-      "label": "car",
-      "line_color": null,
-      "fill_color": null,
-      "points": [
-        [
-          924.0,
-          321.0
-        ],
-        [
-          905.0,
-          352.0
-        ],
-        [
-          909.0,
-          388.0
-        ],
-        [
-          936.0,
-          404.0
-        ],
-        [
-          959.0,
-          411.0
-        ],
-        [
-          966.0,
-          431.0
-        ],
-        [
-          1000.0,
-          432.0
-        ],
-        [
-          1000.0,
-          306.0
-        ]
-      ]
-    }
-  ],
-  "lineColor": [
-    0,
-    255,
-    0,
-    128
-  ],
-  "fillColor": [
-    255,
-    0,
-    0,
-    128
-  ],
-  "imagePath": "00000103.jpg",
-  "imageData": null
-}
\ No newline at end of file

DataAnnotation/labelme/examples/video_annotation/data_annotated/00000104.json

-{
-  "flags": {},
-  "shapes": [
-    {
-      "label": "track",
-      "line_color": null,
-      "fill_color": null,
-      "points": [
-        [
-          556.0,
-          201.0
-        ],
-        [
-          528.0,
-          277.0
-        ],
-        [
-          524.0,
-          342.0
-        ],
-        [
-          528.0,
-          361.0
-        ],
-        [
-          563.0,
-          365.0
-        ],
-        [
-          573.0,
-          356.0
-        ],
-        [
-          606.0,
-          385.0
-        ],
-        [
-          657.0,
-          392.0
-        ],
-        [
-          672.0,
-          366.0
-        ],
-        [
-          825.0,
-          354.0
-        ],
-        [
-          826.0,
-          238.0
-        ],
-        [
-          801.0,
-          202.0
-        ],
-        [
-          701.0,
-          196.0
-        ],
-        [
-          664.0,
-          201.0
-        ]
-      ]
-    },
-    {
-      "label": "track",
-      "line_color": null,
-      "fill_color": null,
-      "points": [
-        [
-          860.0,
-          190.0
-        ],
-        [
-          997.0,
-          186.0
-        ],
-        [
-          998.0,
-          305.0
-        ],
-        [
-          924.0,
-          320.0
-        ],
-        [
-          905.0,
-          352.0
-        ],
-        [
-          874.0,
-          354.0
-        ],
-        [
-          869.0,
-          245.0
-        ],
-        [
-          879.0,
-          222.0
-        ]
-      ]
-    },
-    {
-      "label": "car",
-      "line_color": null,
-      "fill_color": null,
-      "points": [
-        [
-          924.0,
-          321.0
-        ],
-        [
-          905.0,
-          352.0
-        ],
-        [
-          909.0,
-          388.0
-        ],
-        [
-          936.0,
-          404.0
-        ],
-        [
-          959.0,
-          411.0
-        ],
-        [
-          966.0,
-          431.0
-        ],
-        [
-          1000.0,
-          432.0
-        ],
-        [
-          1000.0,
-          306.0
-        ]
-      ]
-    }
-  ],
-  "lineColor": [
-    0,
-    255,
-    0,
-    128
-  ],
-  "fillColor": [
-    255,
-    0,
-    0,
-    128
-  ],
-  "imagePath": "00000104.jpg",
-  "imageData": null
-}
\ No newline at end of file

DataAnnotation/labelme/examples/video_annotation/data_dataset_voc/class_names.txt

-_background_
-car
-track
\ No newline at end of file

DataAnnotation/labelme/examples/video_annotation/labelme2voc.py

-../semantic_segmentation/labelme2voc.py
\ No newline at end of file

DataAnnotation/labelme/examples/video_annotation/labels.txt

-__ignore__
-_background_
-car
-track

DataAnnotation/labelme/github2pypi/.travis.yml

-sudo: false
-
-cache:
-  - pip
-
-dist: trusty
-
-language: python
-
-python:
-  - '3.6'
-  - '2.7'
-
-branches:
-  only:
-    - master
-
-notifications:
-  email: false
-
-install:
-  - true  # drop pip install -r requirements.txt
-
-script:
-  - pip install flake8
-  - flake8 .

DataAnnotation/labelme/github2pypi/README.md

-<h1 align="center">
-  github2pypi
-</h1>
-
-<h4 align="center">
-  Utils to release Python repository on GitHub to PyPi
-</h4>
-
-<div align="center">
-  <a href="https://travis-ci.com/wkentaro/github2pypi"><img src="https://travis-ci.com/wkentaro/github2pypi.svg?branch=master"></a>
-</div>
-
-
-## Usage
-
-
-### 1. Add `github2pypi` as submodule.
-
-See [imgviz](https://github.com/wkentaro/imgviz) as an example.
-
-```bash
-git clone https://github.com/wkentaro/imgviz
-cd imgviz
-
-git submodule add https://github.com/wkentaro/github2pypi.git
-```
-
-
-### 2. Edit `setup.py`.
-
-```python
-import github2pypi
-
-...
-with open('README.md') as f:
-    # e.g., ![](examples/image.jpg) ->
-    #       ![](https://github.com/wkentaro/imgviz/blob/master/examples/image.jpg)
-    long_description = github2pypi.replace_url(
-        slug='wkentaro/imgviz', content=f.read()
-    )
-
-setup(
-    ...
-    long_description=long_description,
-    long_description_content_type='text/markdown',
-)
-```

DataAnnotation/labelme/github2pypi/__init__.py

-# flake8: noqa
-
-from .replace_url import replace_url

DataAnnotation/labelme/github2pypi/replace_url.py

-import re
-
-
-def replace_url(slug, content, branch='master'):
-
-    def repl(match):
-        if not match:
-            return
-
-        url = match.group(1)
-        if url.startswith('http'):
-            return match.group(0)
-
-        url_new = (
-            'https://github.com/{slug}/blob/{branch}/{url}'
-            .format(slug=slug, branch=branch, url=url)
-        )
-        if re.match(r'.*[\.jpg|\.png]$', url_new):
-            url_new += '?raw=true'
-
-        start0, end0 = match.regs[0]
-        start, end = match.regs[1]
-        start -= start0
-        end -= start0
-
-        res = match.group(0)
-        res = res[:start] + url_new + res[end:]
-        return res
-
-    lines = []
-    for line in content.splitlines():
-        patterns = [
-            r'!\[.*?\]\((.*?)\)',
-            r'<img.*?src="(.*?)".*?>',
-            r'\[.*?\]\((.*?)\)',
-            r'<a.*?href="(.*?)".*?>',
-        ]
-        for pattern in patterns:
-            line = re.sub(pattern, repl, line)
-        lines.append(line)
-    return '\n'.join(lines)

DataAnnotation/labelme/labelme.spec

-# -*- mode: python -*-
-# vim: ft=python
-
-
-block_cipher = None
-
-
-a = Analysis(
-    ['labelme/main.py'],
-    pathex=['labelme'],
-    binaries=[],
-    datas=[
-        ('labelme/config/default_config.yaml', 'labelme/config'),
-        ('labelme/icons/*', 'labelme/icons'),
-    ],
-    hiddenimports=[],
-    hookspath=[],
-    runtime_hooks=[],
-    excludes=['matplotlib'],
-    win_no_prefer_redirects=False,
-    win_private_assemblies=False,
-    cipher=block_cipher,
-)
-pyz = PYZ(a.pure, a.zipped_data, cipher=block_cipher)
-exe = EXE(
-    pyz,
-    a.scripts,
-    a.binaries,
-    a.zipfiles,
-    a.datas,
-    name='labelme',
-    debug=False,
-    strip=False,
-    upx=True,
-    runtime_tmpdir=None,
-    console=False,
-    icon='labelme/icons/icon.ico',
-)
-app = BUNDLE(
-    exe,
-    name='labelme.app',
-    icon='labelme/icons/icon.icns',
-    bundle_identifier=None,
-    info_plist={'NSHighResolutionCapable': 'True'},
-)

DataAnnotation/labelme/labelme/__init__.py

-# flake8: noqa
-
-import logging
-import sys
-
-from qtpy import QT_VERSION
-
-
-__appname__ = 'labelme'
-
-QT4 = QT_VERSION[0] == '4'
-QT5 = QT_VERSION[0] == '5'
-del QT_VERSION
-
-PY2 = sys.version[0] == '2'
-PY3 = sys.version[0] == '3'
-del sys
-
-
-from labelme._version import __version__
-
-from labelme import testing
-from labelme import utils

DataAnnotation/labelme/labelme/_version.py

-# Semantic Versioning 2.0.0: https://semver.org/
-# 1. MAJOR version when you make incompatible API changes;
-# 2. MINOR version when you add functionality in a backwards-compatible manner;
-# 3. PATCH version when you make backwards-compatible bug fixes.
-__version__ = '3.16.3'

DataAnnotation/labelme/labelme/app.py

-import functools
-import os
-import os.path as osp
-import re
-import webbrowser
-
-from qtpy import QtCore
-from qtpy.QtCore import Qt
-from qtpy import QtGui
-from qtpy import QtWidgets
-
-from labelme import __appname__
-from labelme import PY2
-from labelme import QT5
-
-from . import utils
-from labelme.config import get_config
-from labelme.label_file import LabelFile
-from labelme.label_file import LabelFileError
-from labelme.logger import logger
-from labelme.shape import DEFAULT_FILL_COLOR
-from labelme.shape import DEFAULT_LINE_COLOR
-from labelme.shape import Shape
-from labelme.widgets import Canvas
-from labelme.widgets import ColorDialog
-from labelme.widgets import EscapableQListWidget
-from labelme.widgets import LabelDialog
-from labelme.widgets import LabelQListWidget
-from labelme.widgets import ToolBar
-from labelme.widgets import ZoomWidget
-
-
-# FIXME
-# - [medium] Set max zoom value to something big enough for FitWidth/Window
-
-# TODO(unknown):
-# - [high] Add polygon movement with arrow keys
-# - [high] Deselect shape when clicking and already selected(?)
-# - [low,maybe] Open images with drag & drop.
-# - [low,maybe] Preview images on file dialogs.
-# - Zoom is too "steppy".
-
-
-class MainWindow(QtWidgets.QMainWindow):
-
-    FIT_WINDOW, FIT_WIDTH, MANUAL_ZOOM = 0, 1, 2
-
-    def __init__(
-        self,
-        config=None,
-        filename=None,
-        output=None,
-        output_file=None,
-        output_dir=None,
-    ):
-        if output is not None:
-            logger.warning(
-                'argument output is deprecated, use output_file instead'
-            )
-            if output_file is None:
-                output_file = output
-
-        # see labelme/config/default_config.yaml for valid configuration
-        if config is None:
-            config = get_config()
-        self._config = config
-
-        super(MainWindow, self).__init__()
-        self.setWindowTitle(__appname__)
-
-        # Whether we need to save or not.
-        self.dirty = False
-
-        self._noSelectionSlot = False
-
-        # Main widgets and related state.
-        self.labelDialog = LabelDialog(
-            parent=self,
-            labels=self._config['labels'],
-            sort_labels=self._config['sort_labels'],
-            show_text_field=self._config['show_label_text_field'],
-            completion=self._config['label_completion'],
-            fit_to_content=self._config['fit_to_content'],
-            flags=self._config['label_flags']
-        )
-
-        self.labelList = LabelQListWidget()
-        self.lastOpenDir = None
-
-        self.flag_dock = self.flag_widget = None
-        self.flag_dock = QtWidgets.QDockWidget('Flags', self)
-        self.flag_dock.setObjectName('Flags')
-        self.flag_widget = QtWidgets.QListWidget()
-        if config['flags']:
-            self.loadFlags({k: False for k in config['flags']})
-        self.flag_dock.setWidget(self.flag_widget)
-        self.flag_widget.itemChanged.connect(self.setDirty)
-
-        self.labelList.itemActivated.connect(self.labelSelectionChanged)
-        self.labelList.itemSelectionChanged.connect(self.labelSelectionChanged)
-        self.labelList.itemDoubleClicked.connect(self.editLabel)
-        # Connect to itemChanged to detect checkbox changes.
-        self.labelList.itemChanged.connect(self.labelItemChanged)
-        self.labelList.setDragDropMode(
-            QtWidgets.QAbstractItemView.InternalMove)
-        self.labelList.setParent(self)
-        self.shape_dock = QtWidgets.QDockWidget('Polygon Labels', self)
-        self.shape_dock.setObjectName('Labels')
-        self.shape_dock.setWidget(self.labelList)
-
-        self.uniqLabelList = EscapableQListWidget()
-        self.uniqLabelList.setToolTip(
-            "Select label to start annotating for it. "
-            "Press 'Esc' to deselect.")
-        if self._config['labels']:
-            self.uniqLabelList.addItems(self._config['labels'])
-            self.uniqLabelList.sortItems()
-        self.label_dock = QtWidgets.QDockWidget(u'Label List', self)
-        self.label_dock.setObjectName(u'Label List')
-        self.label_dock.setWidget(self.uniqLabelList)
-
-        self.fileSearch = QtWidgets.QLineEdit()
-        self.fileSearch.setPlaceholderText('Search Filename')
-        self.fileSearch.textChanged.connect(self.fileSearchChanged)
-        self.fileListWidget = QtWidgets.QListWidget()
-        self.fileListWidget.itemSelectionChanged.connect(
-            self.fileSelectionChanged
-        )
-        fileListLayout = QtWidgets.QVBoxLayout()
-        fileListLayout.setContentsMargins(0, 0, 0, 0)
-        fileListLayout.setSpacing(0)
-        fileListLayout.addWidget(self.fileSearch)
-        fileListLayout.addWidget(self.fileListWidget)
-        self.file_dock = QtWidgets.QDockWidget(u'File List', self)
-        self.file_dock.setObjectName(u'Files')
-        fileListWidget = QtWidgets.QWidget()
-        fileListWidget.setLayout(fileListLayout)
-        self.file_dock.setWidget(fileListWidget)
-
-        self.zoomWidget = ZoomWidget()
-        self.colorDialog = ColorDialog(parent=self)
-
-        self.canvas = self.labelList.canvas = Canvas(
-            epsilon=self._config['epsilon'],
-        )
-        self.canvas.zoomRequest.connect(self.zoomRequest)
-
-        scrollArea = QtWidgets.QScrollArea()
-        scrollArea.setWidget(self.canvas)
-        scrollArea.setWidgetResizable(True)
-        self.scrollBars = {
-            Qt.Vertical: scrollArea.verticalScrollBar(),
-            Qt.Horizontal: scrollArea.horizontalScrollBar(),
-        }
-        self.canvas.scrollRequest.connect(self.scrollRequest)
-
-        self.canvas.newShape.connect(self.newShape)
-        self.canvas.shapeMoved.connect(self.setDirty)
-        self.canvas.selectionChanged.connect(self.shapeSelectionChanged)
-        self.canvas.drawingPolygon.connect(self.toggleDrawingSensitive)
-
-        self.setCentralWidget(scrollArea)
-
-        features = QtWidgets.QDockWidget.DockWidgetFeatures()
-        for dock in ['flag_dock', 'label_dock', 'shape_dock', 'file_dock']:
-            if self._config[dock]['closable']:
-                features = features | QtWidgets.QDockWidget.DockWidgetClosable
-            if self._config[dock]['floatable']:
-                features = features | QtWidgets.QDockWidget.DockWidgetFloatable
-            if self._config[dock]['movable']:
-                features = features | QtWidgets.QDockWidget.DockWidgetMovable
-            getattr(self, dock).setFeatures(features)
-            if self._config[dock]['show'] is False:
-                getattr(self, dock).setVisible(False)
-
-        self.addDockWidget(Qt.RightDockWidgetArea, self.flag_dock)
-        self.addDockWidget(Qt.RightDockWidgetArea, self.label_dock)
-        self.addDockWidget(Qt.RightDockWidgetArea, self.shape_dock)
-        self.addDockWidget(Qt.RightDockWidgetArea, self.file_dock)
-
-        # Actions
-        action = functools.partial(utils.newAction, self)
-        shortcuts = self._config['shortcuts']
-        quit = action('&Quit', self.close, shortcuts['quit'], 'quit',
-                      'Quit application')
-        open_ = action('&Open', self.openFile, shortcuts['open'], 'open',
-                       'Open image or label file')
-        opendir = action('&Open Dir', self.openDirDialog,
-                         shortcuts['open_dir'], 'open', u'Open Dir')
-        openNextImg = action(
-            '&Next Image',
-            self.openNextImg,
-            shortcuts['open_next'],
-            'next',
-            u'Open next (hold Ctl+Shift to copy labels)',
-            enabled=False,
-        )
-        openPrevImg = action(
-            '&Prev Image',
-            self.openPrevImg,
-            shortcuts['open_prev'],
-            'prev',
-            u'Open prev (hold Ctl+Shift to copy labels)',
-            enabled=False,
-        )
-        save = action('&Save', self.saveFile, shortcuts['save'], 'save',
-                      'Save labels to file', enabled=False)
-        saveAs = action('&Save As', self.saveFileAs, shortcuts['save_as'],
-                        'save-as', 'Save labels to a different file',
-                        enabled=False)
-
-        deleteFile = action(
-            '&Delete File',
-            self.deleteFile,
-            shortcuts['delete_file'],
-            'delete',
-            'Delete current label file',
-            enabled=False)
-
-        changeOutputDir = action(
-            '&Change Output Dir',
-            slot=self.changeOutputDirDialog,
-            shortcut=shortcuts['save_to'],
-            icon='open',
-            tip=u'Change where annotations are loaded/saved'
-        )
-
-        saveAuto = action(
-            text='Save &Automatically',
-            slot=lambda x: self.actions.saveAuto.setChecked(x),
-            icon='save',
-            tip='Save automatically',
-            checkable=True,
-            enabled=True,
-        )
-        saveAuto.setChecked(self._config['auto_save'])
-
-        close = action('&Close', self.closeFile, shortcuts['close'], 'close',
-                       'Close current file')
-        color1 = action('Polygon &Line Color', self.chooseColor1,
-                        shortcuts['edit_line_color'], 'color_line',
-                        'Choose polygon line color')
-        color2 = action('Polygon &Fill Color', self.chooseColor2,
-                        shortcuts['edit_fill_color'], 'color',
-                        'Choose polygon fill color')
-
-        toggle_keep_prev_mode = action(
-            'Keep Previous Annotation',
-            self.toggleKeepPrevMode,
-            shortcuts['toggle_keep_prev_mode'], None,
-            'Toggle "keep pevious annotation" mode',
-            checkable=True)
-        toggle_keep_prev_mode.setChecked(self._config['keep_prev'])
-
-        createMode = action(
-            'Create Polygons',
-            lambda: self.toggleDrawMode(False, createMode='polygon'),
-            shortcuts['create_polygon'],
-            'objects',
-            'Start drawing polygons',
-            enabled=False,
-        )
-        createRectangleMode = action(
-            'Create Rectangle',
-            lambda: self.toggleDrawMode(False, createMode='rectangle'),
-            shortcuts['create_rectangle'],
-            'objects',
-            'Start drawing rectangles',
-            enabled=False,
-        )
-        createCircleMode = action(
-            'Create Circle',
-            lambda: self.toggleDrawMode(False, createMode='circle'),
-            shortcuts['create_circle'],
-            'objects',
-            'Start drawing circles',
-            enabled=False,
-        )
-        createLineMode = action(
-            'Create Line',
-            lambda: self.toggleDrawMode(False, createMode='line'),
-            shortcuts['create_line'],
-            'objects',
-            'Start drawing lines',
-            enabled=False,
-        )
-        createPointMode = action(
-            'Create Point',
-            lambda: self.toggleDrawMode(False, createMode='point'),
-            shortcuts['create_point'],
-            'objects',
-            'Start drawing points',
-            enabled=False,
-        )
-        createLineStripMode = action(
-            'Create LineStrip',
-            lambda: self.toggleDrawMode(False, createMode='linestrip'),
-            shortcuts['create_linestrip'],
-            'objects',
-            'Start drawing linestrip. Ctrl+LeftClick ends creation.',
-            enabled=False,
-        )
-        editMode = action('Edit Polygons', self.setEditMode,
-                          shortcuts['edit_polygon'], 'edit',
-                          'Move and edit the selected polygons', enabled=False)
-
-        delete = action('Delete Polygons', self.deleteSelectedShape,
-                        shortcuts['delete_polygon'], 'cancel',
-                        'Delete the selected polygons', enabled=False)
-        copy = action('Duplicate Polygons', self.copySelectedShape,
-                      shortcuts['duplicate_polygon'], 'copy',
-                      'Create a duplicate of the selected polygons',
-                      enabled=False)
-        undoLastPoint = action('Undo last point', self.canvas.undoLastPoint,
-                               shortcuts['undo_last_point'], 'undo',
-                               'Undo last drawn point', enabled=False)
-        addPointToEdge = action(
-            'Add Point to Edge',
-            self.canvas.addPointToEdge,
-            shortcuts['add_point_to_edge'],
-            'edit',
-            'Add point to the nearest edge',
-            enabled=False,
-        )
-
-        undo = action('Undo', self.undoShapeEdit, shortcuts['undo'], 'undo',
-                      'Undo last add and edit of shape', enabled=False)
-
-        hideAll = action('&Hide\nPolygons',
-                         functools.partial(self.togglePolygons, False),
-                         icon='eye', tip='Hide all polygons', enabled=False)
-        showAll = action('&Show\nPolygons',
-                         functools.partial(self.togglePolygons, True),
-                         icon='eye', tip='Show all polygons', enabled=False)
-
-        help = action('&Tutorial', self.tutorial, icon='help',
-                      tip='Show tutorial page')
-
-        zoom = QtWidgets.QWidgetAction(self)
-        zoom.setDefaultWidget(self.zoomWidget)
-        self.zoomWidget.setWhatsThis(
-            'Zoom in or out of the image. Also accessible with '
-            '{} and {} from the canvas.'
-            .format(
-                utils.fmtShortcut(
-                    '{},{}'.format(
-                        shortcuts['zoom_in'], shortcuts['zoom_out']
-                    )
-                ),
-                utils.fmtShortcut("Ctrl+Wheel"),
-            )
-        )
-        self.zoomWidget.setEnabled(False)
-
-        zoomIn = action('Zoom &In', functools.partial(self.addZoom, 1.1),
-                        shortcuts['zoom_in'], 'zoom-in',
-                        'Increase zoom level', enabled=False)
-        zoomOut = action('&Zoom Out', functools.partial(self.addZoom, 0.9),
-                         shortcuts['zoom_out'], 'zoom-out',
-                         'Decrease zoom level', enabled=False)
-        zoomOrg = action('&Original size',
-                         functools.partial(self.setZoom, 100),
-                         shortcuts['zoom_to_original'], 'zoom',
-                         'Zoom to original size', enabled=False)
-        fitWindow = action('&Fit Window', self.setFitWindow,
-                           shortcuts['fit_window'], 'fit-window',
-                           'Zoom follows window size', checkable=True,
-                           enabled=False)
-        fitWidth = action('Fit &Width', self.setFitWidth,
-                          shortcuts['fit_width'], 'fit-width',
-                          'Zoom follows window width',
-                          checkable=True, enabled=False)
-        # Group zoom controls into a list for easier toggling.
-        zoomActions = (self.zoomWidget, zoomIn, zoomOut, zoomOrg,
-                       fitWindow, fitWidth)
-        self.zoomMode = self.FIT_WINDOW
-        fitWindow.setChecked(Qt.Checked)
-        self.scalers = {
-            self.FIT_WINDOW: self.scaleFitWindow,
-            self.FIT_WIDTH: self.scaleFitWidth,
-            # Set to one to scale to 100% when loading files.
-            self.MANUAL_ZOOM: lambda: 1,
-        }
-
-        edit = action('&Edit Label', self.editLabel, shortcuts['edit_label'],
-                      'edit', 'Modify the label of the selected polygon',
-                      enabled=False)
-
-        shapeLineColor = action(
-            'Shape &Line Color', self.chshapeLineColor, icon='color-line',
-            tip='Change the line color for this specific shape', enabled=False)
-        shapeFillColor = action(
-            'Shape &Fill Color', self.chshapeFillColor, icon='color',
-            tip='Change the fill color for this specific shape', enabled=False)
-        fill_drawing = action(
-            'Fill Drawing Polygon',
-            lambda x: self.canvas.setFillDrawing(x),
-            None,
-            'color',
-            'Fill polygon while drawing',
-            checkable=True,
-            enabled=True,
-        )
-        fill_drawing.setChecked(True)
-
-        # Lavel list context menu.
-        labelMenu = QtWidgets.QMenu()
-        utils.addActions(labelMenu, (edit, delete))
-        self.labelList.setContextMenuPolicy(Qt.CustomContextMenu)
-        self.labelList.customContextMenuRequested.connect(
-            self.popLabelListMenu)
-
-        # Store actions for further handling.
-        self.actions = utils.struct(
-            saveAuto=saveAuto,
-            changeOutputDir=changeOutputDir,
-            save=save, saveAs=saveAs, open=open_, close=close,
-            deleteFile=deleteFile,
-            lineColor=color1, fillColor=color2,
-            toggleKeepPrevMode=toggle_keep_prev_mode,
-            delete=delete, edit=edit, copy=copy,
-            undoLastPoint=undoLastPoint, undo=undo,
-            addPointToEdge=addPointToEdge,
-            createMode=createMode, editMode=editMode,
-            createRectangleMode=createRectangleMode,
-            createCircleMode=createCircleMode,
-            createLineMode=createLineMode,
-            createPointMode=createPointMode,
-            createLineStripMode=createLineStripMode,
-            shapeLineColor=shapeLineColor, shapeFillColor=shapeFillColor,
-            zoom=zoom, zoomIn=zoomIn, zoomOut=zoomOut, zoomOrg=zoomOrg,
-            fitWindow=fitWindow, fitWidth=fitWidth,
-            zoomActions=zoomActions,
-            openNextImg=openNextImg, openPrevImg=openPrevImg,
-            fileMenuActions=(open_, opendir, save, saveAs, close, quit),
-            tool=(),
-            # XXX: need to add some actions here to activate the shortcut
-            editMenu=(
-                edit,
-                copy,
-                delete,
-                None,
-                undo,
-                undoLastPoint,
-                None,
-                addPointToEdge,
-                None,
-                color1,
-                color2,
-                None,
-                toggle_keep_prev_mode,
-            ),
-            # menu shown at right click
-            menu=(
-                createMode,
-                createRectangleMode,
-                createCircleMode,
-                createLineMode,
-                createPointMode,
-                createLineStripMode,
-                editMode,
-                edit,
-                copy,
-                delete,
-                shapeLineColor,
-                shapeFillColor,
-                undo,
-                undoLastPoint,
-                addPointToEdge,
-            ),
-            onLoadActive=(
-                close,
-                createMode,
-                createRectangleMode,
-                createCircleMode,
-                createLineMode,
-                createPointMode,
-                createLineStripMode,
-                editMode,
-            ),
-            onShapesPresent=(saveAs, hideAll, showAll),
-        )
-
-        self.canvas.edgeSelected.connect(
-            self.actions.addPointToEdge.setEnabled
-        )
-
-        self.menus = utils.struct(
-            file=self.menu('&File'),
-            edit=self.menu('&Edit'),
-            view=self.menu('&View'),
-            help=self.menu('&Help'),
-            recentFiles=QtWidgets.QMenu('Open &Recent'),
-            labelList=labelMenu,
-        )
-
-        utils.addActions(
-            self.menus.file,
-            (
-                open_,
-                openNextImg,
-                openPrevImg,
-                opendir,
-                self.menus.recentFiles,
-                save,
-                saveAs,
-                saveAuto,
-                changeOutputDir,
-                close,
-                deleteFile,
-                None,
-                quit,
-            ),
-        )
-        utils.addActions(self.menus.help, (help,))
-        utils.addActions(
-            self.menus.view,
-            (
-                self.flag_dock.toggleViewAction(),
-                self.label_dock.toggleViewAction(),
-                self.shape_dock.toggleViewAction(),
-                self.file_dock.toggleViewAction(),
-                None,
-                fill_drawing,
-                None,
-                hideAll,
-                showAll,
-                None,
-                zoomIn,
-                zoomOut,
-                zoomOrg,
-                None,
-                fitWindow,
-                fitWidth,
-                None,
-            ),
-        )
-
-        self.menus.file.aboutToShow.connect(self.updateFileMenu)
-
-        # Custom context menu for the canvas widget:
-        utils.addActions(self.canvas.menus[0], self.actions.menu)
-        utils.addActions(
-            self.canvas.menus[1],
-            (
-                action('&Copy here', self.copyShape),
-                action('&Move here', self.moveShape),
-            ),
-        )
-
-        self.tools = self.toolbar('Tools')
-        # Menu buttons on Left
-        self.actions.tool = (
-            open_,
-            opendir,
-            openNextImg,
-            openPrevImg,
-            save,
-            deleteFile,
-            None,
-            createMode,
-            editMode,
-            copy,
-            delete,
-            undo,
-            None,
-            zoomIn,
-            zoom,
-            zoomOut,
-            fitWindow,
-            fitWidth,
-        )
-
-        self.statusBar().showMessage('%s started.' % __appname__)
-        self.statusBar().show()
-
-        if output_file is not None and self._config['auto_save']:
-            logger.warn(
-                'If `auto_save` argument is True, `output_file` argument '
-                'is ignored and output filename is automatically '
-                'set as IMAGE_BASENAME.json.'
-            )
-        self.output_file = output_file
-        self.output_dir = output_dir
-
-        # Application state.
-        self.image = QtGui.QImage()
-        self.imagePath = None
-        self.recentFiles = []
-        self.maxRecent = 7
-        self.lineColor = None
-        self.fillColor = None
-        self.otherData = None
-        self.zoom_level = 100
-        self.fit_window = False
-
-        if filename is not None and osp.isdir(filename):
-            self.importDirImages(filename, load=False)
-        else:
-            self.filename = filename
-
-        if config['file_search']:
-            self.fileSearch.setText(config['file_search'])
-            self.fileSearchChanged()
-
-        # XXX: Could be completely declarative.
-        # Restore application settings.
-        self.settings = QtCore.QSettings('labelme', 'labelme')
-        # FIXME: QSettings.value can return None on PyQt4
-        self.recentFiles = self.settings.value('recentFiles', []) or []
-        size = self.settings.value('window/size', QtCore.QSize(600, 500))
-        position = self.settings.value('window/position', QtCore.QPoint(0, 0))
-        self.resize(size)
-        self.move(position)
-        # or simply:
-        # self.restoreGeometry(settings['window/geometry']
-        self.restoreState(
-            self.settings.value('window/state', QtCore.QByteArray()))
-        self.lineColor = QtGui.QColor(
-            self.settings.value('line/color', Shape.line_color))
-        self.fillColor = QtGui.QColor(
-            self.settings.value('fill/color', Shape.fill_color))
-        Shape.line_color = self.lineColor
-        Shape.fill_color = self.fillColor
-
-        # Populate the File menu dynamically.
-        self.updateFileMenu()
-        # Since loading the file may take some time,
-        # make sure it runs in the background.
-        if self.filename is not None:
-            self.queueEvent(functools.partial(self.loadFile, self.filename))
-
-        # Callbacks:
-        self.zoomWidget.valueChanged.connect(self.paintCanvas)
-
-        self.populateModeActions()
-
-        # self.firstStart = True
-        # if self.firstStart:
-        #    QWhatsThis.enterWhatsThisMode()
-
-    def menu(self, title, actions=None):
-        menu = self.menuBar().addMenu(title)
-        if actions:
-            utils.addActions(menu, actions)
-        return menu
-
-    def toolbar(self, title, actions=None):
-        toolbar = ToolBar(title)
-        toolbar.setObjectName('%sToolBar' % title)
-        # toolbar.setOrientation(Qt.Vertical)
-        toolbar.setToolButtonStyle(Qt.ToolButtonTextUnderIcon)
-        if actions:
-            utils.addActions(toolbar, actions)
-        self.addToolBar(Qt.LeftToolBarArea, toolbar)
-        return toolbar
-
-    # Support Functions
-
-    def noShapes(self):
-        return not self.labelList.itemsToShapes
-
-    def populateModeActions(self):
-        tool, menu = self.actions.tool, self.actions.menu
-        self.tools.clear()
-        utils.addActions(self.tools, tool)
-        self.canvas.menus[0].clear()
-        utils.addActions(self.canvas.menus[0], menu)
-        self.menus.edit.clear()
-        actions = (
-            self.actions.createMode,
-            self.actions.createRectangleMode,
-            self.actions.createCircleMode,
-            self.actions.createLineMode,
-            self.actions.createPointMode,
-            self.actions.createLineStripMode,
-            self.actions.editMode,
-        )
-        utils.addActions(self.menus.edit, actions + self.actions.editMenu)
-
-    def setDirty(self):
-        if self._config['auto_save'] or self.actions.saveAuto.isChecked():
-            label_file = osp.splitext(self.imagePath)[0] + '.json'
-            if self.output_dir:
-                label_file_without_path = osp.basename(label_file)
-                label_file = osp.join(self.output_dir, label_file_without_path)
-            self.saveLabels(label_file)
-            return
-        self.dirty = True
-        self.actions.save.setEnabled(True)
-        self.actions.undo.setEnabled(self.canvas.isShapeRestorable)
-        title = __appname__
-        if self.filename is not None:
-            title = '{} - {}*'.format(title, self.filename)
-        self.setWindowTitle(title)
-
-    def setClean(self):
-        self.dirty = False
-        self.actions.save.setEnabled(False)
-        self.actions.createMode.setEnabled(True)
-        self.actions.createRectangleMode.setEnabled(True)
-        self.actions.createCircleMode.setEnabled(True)
-        self.actions.createLineMode.setEnabled(True)
-        self.actions.createPointMode.setEnabled(True)
-        self.actions.createLineStripMode.setEnabled(True)
-        title = __appname__
-        if self.filename is not None:
-            title = '{} - {}'.format(title, self.filename)
-        self.setWindowTitle(title)
-
-        if self.hasLabelFile():
-            self.actions.deleteFile.setEnabled(True)
-        else:
-            self.actions.deleteFile.setEnabled(False)
-
-    def toggleActions(self, value=True):
-        """Enable/Disable widgets which depend on an opened image."""
-        for z in self.actions.zoomActions:
-            z.setEnabled(value)
-        for action in self.actions.onLoadActive:
-            action.setEnabled(value)
-
-    def queueEvent(self, function):
-        QtCore.QTimer.singleShot(0, function)
-
-    def status(self, message, delay=5000):
-        self.statusBar().showMessage(message, delay)
-
-    def resetState(self):
-        self.labelList.clear()
-        self.filename = None
-        self.imagePath = None
-        self.imageData = None
-        self.labelFile = None
-        self.otherData = None
-        self.canvas.resetState()
-
-    def currentItem(self):
-        items = self.labelList.selectedItems()
-        if items:
-            return items[0]
-        return None
-
-    def addRecentFile(self, filename):
-        if filename in self.recentFiles:
-            self.recentFiles.remove(filename)
-        elif len(self.recentFiles) >= self.maxRecent:
-            self.recentFiles.pop()
-        self.recentFiles.insert(0, filename)
-
-    # Callbacks
-
-    def undoShapeEdit(self):
-        self.canvas.restoreShape()
-        self.labelList.clear()
-        self.loadShapes(self.canvas.shapes)
-        self.actions.undo.setEnabled(self.canvas.isShapeRestorable)
-
-    def tutorial(self):
-        url = 'https://github.com/wkentaro/labelme/tree/master/examples/tutorial'  # NOQA
-        webbrowser.open(url)
-
-    def toggleDrawingSensitive(self, drawing=True):
-        """Toggle drawing sensitive.
-
-        In the middle of drawing, toggling between modes should be disabled.
-        """
-        self.actions.editMode.setEnabled(not drawing)
-        self.actions.undoLastPoint.setEnabled(drawing)
-        self.actions.undo.setEnabled(not drawing)
-        self.actions.delete.setEnabled(not drawing)
-
-    def toggleDrawMode(self, edit=True, createMode='polygon'):
-        self.canvas.setEditing(edit)
-        self.canvas.createMode = createMode
-        if edit:
-            self.actions.createMode.setEnabled(True)
-            self.actions.createRectangleMode.setEnabled(True)
-            self.actions.createCircleMode.setEnabled(True)
-            self.actions.createLineMode.setEnabled(True)
-            self.actions.createPointMode.setEnabled(True)
-            self.actions.createLineStripMode.setEnabled(True)
-        else:
-            if createMode == 'polygon':
-                self.actions.createMode.setEnabled(False)
-                self.actions.createRectangleMode.setEnabled(True)
-                self.actions.createCircleMode.setEnabled(True)
-                self.actions.createLineMode.setEnabled(True)
-                self.actions.createPointMode.setEnabled(True)
-                self.actions.createLineStripMode.setEnabled(True)
-            elif createMode == 'rectangle':
-                self.actions.createMode.setEnabled(True)
-                self.actions.createRectangleMode.setEnabled(False)
-                self.actions.createCircleMode.setEnabled(True)
-                self.actions.createLineMode.setEnabled(True)
-                self.actions.createPointMode.setEnabled(True)
-                self.actions.createLineStripMode.setEnabled(True)
-            elif createMode == 'line':
-                self.actions.createMode.setEnabled(True)
-                self.actions.createRectangleMode.setEnabled(True)
-                self.actions.createCircleMode.setEnabled(True)
-                self.actions.createLineMode.setEnabled(False)
-                self.actions.createPointMode.setEnabled(True)
-                self.actions.createLineStripMode.setEnabled(True)
-            elif createMode == 'point':
-                self.actions.createMode.setEnabled(True)
-                self.actions.createRectangleMode.setEnabled(True)
-                self.actions.createCircleMode.setEnabled(True)
-                self.actions.createLineMode.setEnabled(True)
-                self.actions.createPointMode.setEnabled(False)
-                self.actions.createLineStripMode.setEnabled(True)
-            elif createMode == "circle":
-                self.actions.createMode.setEnabled(True)
-                self.actions.createRectangleMode.setEnabled(True)
-                self.actions.createCircleMode.setEnabled(False)
-                self.actions.createLineMode.setEnabled(True)
-                self.actions.createPointMode.setEnabled(True)
-                self.actions.createLineStripMode.setEnabled(True)
-            elif createMode == "linestrip":
-                self.actions.createMode.setEnabled(True)
-                self.actions.createRectangleMode.setEnabled(True)
-                self.actions.createCircleMode.setEnabled(True)
-                self.actions.createLineMode.setEnabled(True)
-                self.actions.createPointMode.setEnabled(True)
-                self.actions.createLineStripMode.setEnabled(False)
-            else:
-                raise ValueError('Unsupported createMode: %s' % createMode)
-        self.actions.editMode.setEnabled(not edit)
-
-    def setEditMode(self):
-        self.toggleDrawMode(True)
-
-    def updateFileMenu(self):
-        current = self.filename
-
-        def exists(filename):
-            return osp.exists(str(filename))
-
-        menu = self.menus.recentFiles
-        menu.clear()
-        files = [f for f in self.recentFiles if f != current and exists(f)]
-        for i, f in enumerate(files):
-            icon = utils.newIcon('labels')
-            action = QtWidgets.QAction(
-                icon, '&%d %s' % (i + 1, QtCore.QFileInfo(f).fileName()), self)
-            action.triggered.connect(functools.partial(self.loadRecent, f))
-            menu.addAction(action)
-
-    def popLabelListMenu(self, point):
-        self.menus.labelList.exec_(self.labelList.mapToGlobal(point))
-
-    def validateLabel(self, label):
-        # no validation
-        if self._config['validate_label'] is None:
-            return True
-
-        for i in range(self.uniqLabelList.count()):
-            label_i = self.uniqLabelList.item(i).text()
-            if self._config['validate_label'] in ['exact', 'instance']:
-                if label_i == label:
-                    return True
-            if self._config['validate_label'] == 'instance':
-                m = re.match(r'^{}-[0-9]*$'.format(label_i), label)
-                if m:
-                    return True
-        return False
-
-    def editLabel(self, item=False):
-        if item and not isinstance(item, QtWidgets.QListWidgetItem):
-            raise TypeError('unsupported type of item: {}'.format(type(item)))
-
-        if not self.canvas.editing():
-            return
-        if not item:
-            item = self.currentItem()
-        if item is None:
-            return
-        shape = self.labelList.get_shape_from_item(item)
-        if shape is None:
-            return
-        text, flags = self.labelDialog.popUp(shape.label, flags=shape.flags)
-        if text is None:
-            return
-        if not self.validateLabel(text):
-            self.errorMessage('Invalid label',
-                              "Invalid label '{}' with validation type '{}'"
-                              .format(text, self._config['validate_label']))
-            return
-        shape.label = text
-        shape.flags = flags
-        item.setText(text)
-        self.setDirty()
-        if not self.uniqLabelList.findItems(text, Qt.MatchExactly):
-            self.uniqLabelList.addItem(text)
-            self.uniqLabelList.sortItems()
-
-    def fileSearchChanged(self):
-        self.importDirImages(
-            self.lastOpenDir,
-            pattern=self.fileSearch.text(),
-            load=False,
-        )
-
-    def fileSelectionChanged(self):
-        items = self.fileListWidget.selectedItems()
-        if not items:
-            return
-        item = items[0]
-
-        if not self.mayContinue():
-            return
-
-        currIndex = self.imageList.index(str(item.text()))
-        if currIndex < len(self.imageList):
-            filename = self.imageList[currIndex]
-            if filename:
-                self.loadFile(filename)
-
-    # React to canvas signals.
-    def shapeSelectionChanged(self, selected_shapes):
-        self._noSelectionSlot = True
-        for shape in self.canvas.selectedShapes:
-            shape.selected = False
-        self.labelList.clearSelection()
-        self.canvas.selectedShapes = selected_shapes
-        for shape in self.canvas.selectedShapes:
-            shape.selected = True
-            item = self.labelList.get_item_from_shape(shape)
-            item.setSelected(True)
-        self._noSelectionSlot = False
-        n_selected = len(selected_shapes)
-        self.actions.delete.setEnabled(n_selected)
-        self.actions.copy.setEnabled(n_selected)
-        self.actions.edit.setEnabled(n_selected == 1)
-        self.actions.shapeLineColor.setEnabled(n_selected)
-        self.actions.shapeFillColor.setEnabled(n_selected)
-
-    def addLabel(self, shape):
-        item = QtWidgets.QListWidgetItem(shape.label)
-        item.setFlags(item.flags() | Qt.ItemIsUserCheckable)
-        item.setCheckState(Qt.Checked)
-        self.labelList.itemsToShapes.append((item, shape))
-        self.labelList.addItem(item)
-        if not self.uniqLabelList.findItems(shape.label, Qt.MatchExactly):
-            self.uniqLabelList.addItem(shape.label)
-            self.uniqLabelList.sortItems()
-        self.labelDialog.addLabelHistory(item.text())
-        for action in self.actions.onShapesPresent:
-            action.setEnabled(True)
-
-    def remLabels(self, shapes):
-        for shape in shapes:
-            item = self.labelList.get_item_from_shape(shape)
-            self.labelList.takeItem(self.labelList.row(item))
-
-    def loadShapes(self, shapes, replace=True):
-        self._noSelectionSlot = True
-        for shape in shapes:
-            self.addLabel(shape)
-        self.labelList.clearSelection()
-        self._noSelectionSlot = False
-        self.canvas.loadShapes(shapes, replace=replace)
-
-    def loadLabels(self, shapes):
-        s = []
-        for label, points, line_color, fill_color, shape_type, flags in shapes:
-            shape = Shape(label=label, shape_type=shape_type)
-            for x, y in points:
-                shape.addPoint(QtCore.QPointF(x, y))
-            shape.close()
-
-            if line_color:
-                shape.line_color = QtGui.QColor(*line_color)
-
-            if fill_color:
-                shape.fill_color = QtGui.QColor(*fill_color)
-
-            default_flags = {}
-            if self._config['label_flags']:
-                for pattern, keys in self._config['label_flags'].items():
-                    if re.match(pattern, label):
-                        for key in keys:
-                            default_flags[key] = False
-            shape.flags = default_flags
-            shape.flags.update(flags)
-
-            s.append(shape)
-        self.loadShapes(s)
-
-    def loadFlags(self, flags):
-        self.flag_widget.clear()
-        for key, flag in flags.items():
-            item = QtWidgets.QListWidgetItem(key)
-            item.setFlags(item.flags() | Qt.ItemIsUserCheckable)
-            item.setCheckState(Qt.Checked if flag else Qt.Unchecked)
-            self.flag_widget.addItem(item)
-
-    def saveLabels(self, filename):
-        lf = LabelFile()
-
-        def format_shape(s):
-            return dict(
-                label=s.label.encode('utf-8') if PY2 else s.label,
-                line_color=s.line_color.getRgb()
-                if s.line_color != self.lineColor else None,
-                fill_color=s.fill_color.getRgb()
-                if s.fill_color != self.fillColor else None,
-                points=[(p.x(), p.y()) for p in s.points],
-                shape_type=s.shape_type,
-                flags=s.flags
-            )
-
-        shapes = [format_shape(shape) for shape in self.labelList.shapes]
-        flags = {}
-        for i in range(self.flag_widget.count()):
-            item = self.flag_widget.item(i)
-            key = item.text()
-            flag = item.checkState() == Qt.Checked
-            flags[key] = flag
-        try:
-            imagePath = osp.relpath(
-                self.imagePath, osp.dirname(filename))
-            imageData = self.imageData if self._config['store_data'] else None
-            if osp.dirname(filename) and not osp.exists(osp.dirname(filename)):
-                os.makedirs(osp.dirname(filename))
-            lf.save(
-                filename=filename,
-                shapes=shapes,
-                imagePath=imagePath,
-                imageData=imageData,
-                imageHeight=self.image.height(),
-                imageWidth=self.image.width(),
-                lineColor=self.lineColor.getRgb(),
-                fillColor=self.fillColor.getRgb(),
-                otherData=self.otherData,
-                flags=flags,
-            )
-            self.labelFile = lf
-            items = self.fileListWidget.findItems(
-                self.imagePath, Qt.MatchExactly
-            )
-            if len(items) > 0:
-                if len(items) != 1:
-                    raise RuntimeError('There are duplicate files.')
-                items[0].setCheckState(Qt.Checked)
-            # disable allows next and previous image to proceed
-            # self.filename = filename
-            return True
-        except LabelFileError as e:
-            self.errorMessage('Error saving label data', '<b>%s</b>' % e)
-            return False
-
-    def copySelectedShape(self):
-        added_shapes = self.canvas.copySelectedShapes()
-        self.labelList.clearSelection()
-        for shape in added_shapes:
-            self.addLabel(shape)
-        self.setDirty()
-
-    def labelSelectionChanged(self):
-        if self._noSelectionSlot:
-            return
-        if self.canvas.editing():
-            selected_shapes = []
-            for item in self.labelList.selectedItems():
-                shape = self.labelList.get_shape_from_item(item)
-                selected_shapes.append(shape)
-            if selected_shapes:
-                self.canvas.selectShapes(selected_shapes)
-
-    def labelItemChanged(self, item):
-        shape = self.labelList.get_shape_from_item(item)
-        label = str(item.text())
-        if label != shape.label:
-            shape.label = str(item.text())
-            self.setDirty()
-        else:  # User probably changed item visibility
-            self.canvas.setShapeVisible(shape, item.checkState() == Qt.Checked)
-
-    # Callback functions:
-
-    def newShape(self):
-        """Pop-up and give focus to the label editor.
-
-        position MUST be in global coordinates.
-        """
-        items = self.uniqLabelList.selectedItems()
-        text = None
-        flags = {}
-        if items:
-            text = items[0].text()
-        if self._config['display_label_popup'] or not text:
-            # instance label auto increment
-            if self._config['instance_label_auto_increment']:
-                previous_label = self.labelDialog.edit.text()
-                split = previous_label.split('-')
-                if len(split) > 1 and split[-1].isdigit():
-                    split[-1] = str(int(split[-1]) + 1)
-                    instance_text = '-'.join(split)
-                else:
-                    instance_text = previous_label
-                if instance_text != '':
-                    text = instance_text
-            text, flags = self.labelDialog.popUp(text)
-            if text is None:
-                self.labelDialog.edit.setText(previous_label)
-
-        if text and not self.validateLabel(text):
-            self.errorMessage('Invalid label',
-                              "Invalid label '{}' with validation type '{}'"
-                              .format(text, self._config['validate_label']))
-            text = ''
-        if text:
-            self.labelList.clearSelection()
-            self.addLabel(self.canvas.setLastLabel(text, flags))
-            self.actions.editMode.setEnabled(True)
-            self.actions.undoLastPoint.setEnabled(False)
-            self.actions.undo.setEnabled(True)
-            self.setDirty()
-        else:
-            self.canvas.undoLastLine()
-            self.canvas.shapesBackups.pop()
-
-    def scrollRequest(self, delta, orientation):
-        units = - delta * 0.1  # natural scroll
-        bar = self.scrollBars[orientation]
-        bar.setValue(bar.value() + bar.singleStep() * units)
-
-    def setZoom(self, value):
-        self.actions.fitWidth.setChecked(False)
-        self.actions.fitWindow.setChecked(False)
-        self.zoomMode = self.MANUAL_ZOOM
-        self.zoomWidget.setValue(value)
-
-    def addZoom(self, increment=1.1):
-        self.setZoom(self.zoomWidget.value() * increment)
-
-    def zoomRequest(self, delta, pos):
-        canvas_width_old = self.canvas.width()
-        units = 1.1
-        if delta < 0:
-            units = 0.9
-        self.addZoom(units)
-
-        canvas_width_new = self.canvas.width()
-        if canvas_width_old != canvas_width_new:
-            canvas_scale_factor = canvas_width_new / canvas_width_old
-
-            x_shift = round(pos.x() * canvas_scale_factor) - pos.x()
-            y_shift = round(pos.y() * canvas_scale_factor) - pos.y()
-
-            self.scrollBars[Qt.Horizontal].setValue(
-                self.scrollBars[Qt.Horizontal].value() + x_shift)
-            self.scrollBars[Qt.Vertical].setValue(
-                self.scrollBars[Qt.Vertical].value() + y_shift)
-
-    def setFitWindow(self, value=True):
-        if value:
-            self.actions.fitWidth.setChecked(False)
-        self.zoomMode = self.FIT_WINDOW if value else self.MANUAL_ZOOM
-        self.adjustScale()
-
-    def setFitWidth(self, value=True):
-        if value:
-            self.actions.fitWindow.setChecked(False)
-        self.zoomMode = self.FIT_WIDTH if value else self.MANUAL_ZOOM
-        self.adjustScale()
-
-    def togglePolygons(self, value):
-        for item, shape in self.labelList.itemsToShapes:
-            item.setCheckState(Qt.Checked if value else Qt.Unchecked)
-
-    def loadFile(self, filename=None):
-        """Load the specified file, or the last opened file if None."""
-        # changing fileListWidget loads file
-        if (filename in self.imageList and
-                self.fileListWidget.currentRow() !=
-                self.imageList.index(filename)):
-            self.fileListWidget.setCurrentRow(self.imageList.index(filename))
-            self.fileListWidget.repaint()
-            return
-
-        self.resetState()
-        self.canvas.setEnabled(False)
-        if filename is None:
-            filename = self.settings.value('filename', '')
-        filename = str(filename)
-        if not QtCore.QFile.exists(filename):
-            self.errorMessage(
-                'Error opening file', 'No such file: <b>%s</b>' % filename)
-            return False
-        # assumes same name, but json extension
-        self.status("Loading %s..." % osp.basename(str(filename)))
-        label_file = osp.splitext(filename)[0] + '.json'
-        if self.output_dir:
-            label_file_without_path = osp.basename(label_file)
-            label_file = osp.join(self.output_dir, label_file_without_path)
-        if QtCore.QFile.exists(label_file) and \
-                LabelFile.is_label_file(label_file):
-            try:
-                self.labelFile = LabelFile(label_file)
-            except LabelFileError as e:
-                self.errorMessage(
-                    'Error opening file',
-                    "<p><b>%s</b></p>"
-                    "<p>Make sure <i>%s</i> is a valid label file."
-                    % (e, label_file))
-                self.status("Error reading %s" % label_file)
-                return False
-            self.imageData = self.labelFile.imageData
-            self.imagePath = osp.join(
-                osp.dirname(label_file),
-                self.labelFile.imagePath,
-            )
-            if self.labelFile.lineColor is not None:
-                self.lineColor = QtGui.QColor(*self.labelFile.lineColor)
-            if self.labelFile.fillColor is not None:
-                self.fillColor = QtGui.QColor(*self.labelFile.fillColor)
-            self.otherData = self.labelFile.otherData
-        else:
-            self.imageData = LabelFile.load_image_file(filename)
-            if self.imageData:
-                self.imagePath = filename
-            self.labelFile = None
-        image = QtGui.QImage.fromData(self.imageData)
-
-        if image.isNull():
-            formats = ['*.{}'.format(fmt.data().decode())
-                       for fmt in QtGui.QImageReader.supportedImageFormats()]
-            self.errorMessage(
-                'Error opening file',
-                '<p>Make sure <i>{0}</i> is a valid image file.<br/>'
-                'Supported image formats: {1}</p>'
-                .format(filename, ','.join(formats)))
-            self.status("Error reading %s" % filename)
-            return False
-        self.image = image
-        self.filename = filename
-        if self._config['keep_prev']:
-            prev_shapes = self.canvas.shapes
-        self.canvas.loadPixmap(QtGui.QPixmap.fromImage(image))
-        if self._config['flags']:
-            self.loadFlags({k: False for k in self._config['flags']})
-        if self.labelFile:
-            self.loadLabels(self.labelFile.shapes)
-            if self.labelFile.flags is not None:
-                self.loadFlags(self.labelFile.flags)
-        if self._config['keep_prev'] and not self.labelList.shapes:
-            self.loadShapes(prev_shapes, replace=False)
-        self.setClean()
-        self.canvas.setEnabled(True)
-        self.adjustScale(initial=True)
-        self.paintCanvas()
-        self.addRecentFile(self.filename)
-        self.toggleActions(True)
-        self.status("Loaded %s" % osp.basename(str(filename)))
-        return True
-
-    def resizeEvent(self, event):
-        if self.canvas and not self.image.isNull()\
-           and self.zoomMode != self.MANUAL_ZOOM:
-            self.adjustScale()
-        super(MainWindow, self).resizeEvent(event)
-
-    def paintCanvas(self):
-        assert not self.image.isNull(), "cannot paint null image"
-        self.canvas.scale = 0.01 * self.zoomWidget.value()
-        self.canvas.adjustSize()
-        self.canvas.update()
-
-    def adjustScale(self, initial=False):
-        value = self.scalers[self.FIT_WINDOW if initial else self.zoomMode]()
-        self.zoomWidget.setValue(int(100 * value))
-
-    def scaleFitWindow(self):
-        """Figure out the size of the pixmap to fit the main widget."""
-        e = 2.0  # So that no scrollbars are generated.
-        w1 = self.centralWidget().width() - e
-        h1 = self.centralWidget().height() - e
-        a1 = w1 / h1
-        # Calculate a new scale value based on the pixmap's aspect ratio.
-        w2 = self.canvas.pixmap.width() - 0.0
-        h2 = self.canvas.pixmap.height() - 0.0
-        a2 = w2 / h2
-        return w1 / w2 if a2 >= a1 else h1 / h2
-
-    def scaleFitWidth(self):
-        # The epsilon does not seem to work too well here.
-        w = self.centralWidget().width() - 2.0
-        return w / self.canvas.pixmap.width()
-
-    def closeEvent(self, event):
-        if not self.mayContinue():
-            event.ignore()
-        self.settings.setValue(
-            'filename', self.filename if self.filename else '')
-        self.settings.setValue('window/size', self.size())
-        self.settings.setValue('window/position', self.pos())
-        self.settings.setValue('window/state', self.saveState())
-        self.settings.setValue('line/color', self.lineColor)
-        self.settings.setValue('fill/color', self.fillColor)
-        self.settings.setValue('recentFiles', self.recentFiles)
-        # ask the use for where to save the labels
-        # self.settings.setValue('window/geometry', self.saveGeometry())
-
-    # User Dialogs #
-
-    def loadRecent(self, filename):
-        if self.mayContinue():
-            self.loadFile(filename)
-
-    def openPrevImg(self, _value=False):
-        keep_prev = self._config['keep_prev']
-        if QtGui.QGuiApplication.keyboardModifiers() == \
-                (QtCore.Qt.ControlModifier | QtCore.Qt.ShiftModifier):
-            self._config['keep_prev'] = True
-
-        if not self.mayContinue():
-            return
-
-        if len(self.imageList) <= 0:
-            return
-
-        if self.filename is None:
-            return
-
-        currIndex = self.imageList.index(self.filename)
-        if currIndex - 1 >= 0:
-            filename = self.imageList[currIndex - 1]
-            if filename:
-                self.loadFile(filename)
-
-        self._config['keep_prev'] = keep_prev
-
-    def openNextImg(self, _value=False, load=True):
-        keep_prev = self._config['keep_prev']
-        if QtGui.QGuiApplication.keyboardModifiers() == \
-                (QtCore.Qt.ControlModifier | QtCore.Qt.ShiftModifier):
-            self._config['keep_prev'] = True
-
-        if not self.mayContinue():
-            return
-
-        if len(self.imageList) <= 0:
-            return
-
-        filename = None
-        if self.filename is None:
-            filename = self.imageList[0]
-        else:
-            currIndex = self.imageList.index(self.filename)
-            if currIndex + 1 < len(self.imageList):
-                filename = self.imageList[currIndex + 1]
-            else:
-                filename = self.imageList[-1]
-        self.filename = filename
-
-        if self.filename and load:
-            self.loadFile(self.filename)
-
-        self._config['keep_prev'] = keep_prev
-
-    def openFile(self, _value=False):
-        if not self.mayContinue():
-            return
-        path = osp.dirname(str(self.filename)) if self.filename else '.'
-        formats = ['*.{}'.format(fmt.data().decode())
-                   for fmt in QtGui.QImageReader.supportedImageFormats()]
-        filters = "Image & Label files (%s)" % ' '.join(
-            formats + ['*%s' % LabelFile.suffix])
-        filename = QtWidgets.QFileDialog.getOpenFileName(
-            self, '%s - Choose Image or Label file' % __appname__,
-            path, filters)
-        if QT5:
-            filename, _ = filename
-        filename = str(filename)
-        if filename:
-            self.loadFile(filename)
-
-    def changeOutputDirDialog(self, _value=False):
-        default_output_dir = self.output_dir
-        if default_output_dir is None and self.filename:
-            default_output_dir = osp.dirname(self.filename)
-        if default_output_dir is None:
-            default_output_dir = self.currentPath()
-
-        output_dir = QtWidgets.QFileDialog.getExistingDirectory(
-            self, '%s - Save/Load Annotations in Directory' % __appname__,
-            default_output_dir,
-            QtWidgets.QFileDialog.ShowDirsOnly |
-            QtWidgets.QFileDialog.DontResolveSymlinks,
-        )
-        output_dir = str(output_dir)
-
-        if not output_dir:
-            return
-
-        self.output_dir = output_dir
-
-        self.statusBar().showMessage(
-            '%s . Annotations will be saved/loaded in %s' %
-            ('Change Annotations Dir', self.output_dir))
-        self.statusBar().show()
-
-        current_filename = self.filename
-        self.importDirImages(self.lastOpenDir, load=False)
-
-        if current_filename in self.imageList:
-            # retain currently selected file
-            self.fileListWidget.setCurrentRow(
-                self.imageList.index(current_filename))
-            self.fileListWidget.repaint()
-
-    def saveFile(self, _value=False):
-        assert not self.image.isNull(), "cannot save empty image"
-        if self._config['flags'] or self.hasLabels():
-            if self.labelFile:
-                # DL20180323 - overwrite when in directory
-                self._saveFile(self.labelFile.filename)
-            elif self.output_file:
-                self._saveFile(self.output_file)
-                self.close()
-            else:
-                self._saveFile(self.saveFileDialog())
-
-    def saveFileAs(self, _value=False):
-        assert not self.image.isNull(), "cannot save empty image"
-        if self.hasLabels():
-            self._saveFile(self.saveFileDialog())
-
-    def saveFileDialog(self):
-        caption = '%s - Choose File' % __appname__
-        filters = 'Label files (*%s)' % LabelFile.suffix
-        if self.output_dir:
-            dlg = QtWidgets.QFileDialog(
-                self, caption, self.output_dir, filters
-            )
-        else:
-            dlg = QtWidgets.QFileDialog(
-                self, caption, self.currentPath(), filters
-            )
-        dlg.setDefaultSuffix(LabelFile.suffix[1:])
-        dlg.setAcceptMode(QtWidgets.QFileDialog.AcceptSave)
-        dlg.setOption(QtWidgets.QFileDialog.DontConfirmOverwrite, False)
-        dlg.setOption(QtWidgets.QFileDialog.DontUseNativeDialog, False)
-        basename = osp.basename(osp.splitext(self.filename)[0])
-        if self.output_dir:
-            default_labelfile_name = osp.join(
-                self.output_dir, basename + LabelFile.suffix
-            )
-        else:
-            default_labelfile_name = osp.join(
-                self.currentPath(), basename + LabelFile.suffix
-            )
-        filename = dlg.getSaveFileName(
-            self, 'Choose File', default_labelfile_name,
-            'Label files (*%s)' % LabelFile.suffix)
-        if QT5:
-            filename, _ = filename
-        filename = str(filename)
-        return filename
-
-    def _saveFile(self, filename):
-        if filename and self.saveLabels(filename):
-            self.addRecentFile(filename)
-            self.setClean()
-
-    def closeFile(self, _value=False):
-        if not self.mayContinue():
-            return
-        self.resetState()
-        self.setClean()
-        self.toggleActions(False)
-        self.canvas.setEnabled(False)
-        self.actions.saveAs.setEnabled(False)
-
-    def getLabelFile(self):
-        if self.filename.lower().endswith('.json'):
-            label_file = self.filename
-        else:
-            label_file = osp.splitext(self.filename)[0] + '.json'
-
-        return label_file
-
-    def deleteFile(self):
-        mb = QtWidgets.QMessageBox
-        msg = 'You are about to permanently delete this label file, ' \
-              'proceed anyway?'
-        answer = mb.warning(self, 'Attention', msg, mb.Yes | mb.No)
-        if answer != mb.Yes:
-            return
-
-        label_file = self.getLabelFile()
-        if osp.exists(label_file):
-            os.remove(label_file)
-            logger.info('Label file is removed: {}'.format(label_file))
-
-            item = self.fileListWidget.currentItem()
-            item.setCheckState(Qt.Unchecked)
-
-            self.resetState()
-
-    # Message Dialogs. #
-    def hasLabels(self):
-        if not self.labelList.itemsToShapes:
-            self.errorMessage(
-                'No objects labeled',
-                'You must label at least one object to save the file.')
-            return False
-        return True
-
-    def hasLabelFile(self):
-        if self.filename is None:
-            return False
-
-        label_file = self.getLabelFile()
-        return osp.exists(label_file)
-
-    def mayContinue(self):
-        if not self.dirty:
-            return True
-        mb = QtWidgets.QMessageBox
-        msg = 'Save annotations to "{}" before closing?'.format(self.filename)
-        answer = mb.question(self,
-                             'Save annotations?',
-                             msg,
-                             mb.Save | mb.Discard | mb.Cancel,
-                             mb.Save)
-        if answer == mb.Discard:
-            return True
-        elif answer == mb.Save:
-            self.saveFile()
-            return True
-        else:  # answer == mb.Cancel
-            return False
-
-    def errorMessage(self, title, message):
-        return QtWidgets.QMessageBox.critical(
-            self, title, '<p><b>%s</b></p>%s' % (title, message))
-
-    def currentPath(self):
-        return osp.dirname(str(self.filename)) if self.filename else '.'
-
-    def chooseColor1(self):
-        color = self.colorDialog.getColor(
-            self.lineColor, 'Choose line color', default=DEFAULT_LINE_COLOR)
-        if color:
-            self.lineColor = color
-            # Change the color for all shape lines:
-            Shape.line_color = self.lineColor
-            self.canvas.update()
-            self.setDirty()
-
-    def chooseColor2(self):
-        color = self.colorDialog.getColor(
-            self.fillColor, 'Choose fill color', default=DEFAULT_FILL_COLOR)
-        if color:
-            self.fillColor = color
-            Shape.fill_color = self.fillColor
-            self.canvas.update()
-            self.setDirty()
-
-    def toggleKeepPrevMode(self):
-        self._config['keep_prev'] = not self._config['keep_prev']
-
-    def deleteSelectedShape(self):
-        yes, no = QtWidgets.QMessageBox.Yes, QtWidgets.QMessageBox.No
-        msg = 'You are about to permanently delete {} polygons, ' \
-              'proceed anyway?'.format(len(self.canvas.selectedShapes))
-        if yes == QtWidgets.QMessageBox.warning(self, 'Attention', msg,
-                                                yes | no):
-            self.remLabels(self.canvas.deleteSelected())
-            self.setDirty()
-            if self.noShapes():
-                for action in self.actions.onShapesPresent:
-                    action.setEnabled(False)
-
-    def chshapeLineColor(self):
-        color = self.colorDialog.getColor(
-            self.lineColor, 'Choose line color', default=DEFAULT_LINE_COLOR)
-        if color:
-            for shape in self.canvas.selectedShapes:
-                shape.line_color = color
-            self.canvas.update()
-            self.setDirty()
-
-    def chshapeFillColor(self):
-        color = self.colorDialog.getColor(
-            self.fillColor, 'Choose fill color', default=DEFAULT_FILL_COLOR)
-        if color:
-            for shape in self.canvas.selectedShapes:
-                shape.fill_color = color
-            self.canvas.update()
-            self.setDirty()
-
-    def copyShape(self):
-        self.canvas.endMove(copy=True)
-        self.labelList.clearSelection()
-        for shape in self.canvas.selectedShapes:
-            self.addLabel(shape)
-        self.setDirty()
-
-    def moveShape(self):
-        self.canvas.endMove(copy=False)
-        self.setDirty()
-
-    def openDirDialog(self, _value=False, dirpath=None):
-        if not self.mayContinue():
-            return
-
-        defaultOpenDirPath = dirpath if dirpath else '.'
-        if self.lastOpenDir and osp.exists(self.lastOpenDir):
-            defaultOpenDirPath = self.lastOpenDir
-        else:
-            defaultOpenDirPath = osp.dirname(self.filename) \
-                if self.filename else '.'
-
-        targetDirPath = str(QtWidgets.QFileDialog.getExistingDirectory(
-            self, '%s - Open Directory' % __appname__, defaultOpenDirPath,
-            QtWidgets.QFileDialog.ShowDirsOnly |
-            QtWidgets.QFileDialog.DontResolveSymlinks))
-        self.importDirImages(targetDirPath)
-
-    @property
-    def imageList(self):
-        lst = []
-        for i in range(self.fileListWidget.count()):
-            item = self.fileListWidget.item(i)
-            lst.append(item.text())
-        return lst
-
-    def importDirImages(self, dirpath, pattern=None, load=True):
-        self.actions.openNextImg.setEnabled(True)
-        self.actions.openPrevImg.setEnabled(True)
-
-        if not self.mayContinue() or not dirpath:
-            return
-
-        self.lastOpenDir = dirpath
-        self.filename = None
-        self.fileListWidget.clear()
-        for filename in self.scanAllImages(dirpath):
-            if pattern and pattern not in filename:
-                continue
-            label_file = osp.splitext(filename)[0] + '.json'
-            if self.output_dir:
-                label_file_without_path = osp.basename(label_file)
-                label_file = osp.join(self.output_dir, label_file_without_path)
-            item = QtWidgets.QListWidgetItem(filename)
-            item.setFlags(Qt.ItemIsEnabled | Qt.ItemIsSelectable)
-            if QtCore.QFile.exists(label_file) and \
-                    LabelFile.is_label_file(label_file):
-                item.setCheckState(Qt.Checked)
-            else:
-                item.setCheckState(Qt.Unchecked)
-            self.fileListWidget.addItem(item)
-        self.openNextImg(load=load)
-
-    def scanAllImages(self, folderPath):
-        extensions = ['.%s' % fmt.data().decode("ascii").lower()
-                      for fmt in QtGui.QImageReader.supportedImageFormats()]
-        images = []
-
-        for root, dirs, files in os.walk(folderPath):
-            for file in files:
-                if file.lower().endswith(tuple(extensions)):
-                    relativePath = osp.join(root, file)
-                    images.append(relativePath)
-        images.sort(key=lambda x: x.lower())
-        return images

DataAnnotation/labelme/labelme/cli/__init__.py

-# flake8: noqa
-
-from . import draw_json
-from . import draw_label_png
-from . import json_to_dataset
-from . import on_docker

DataAnnotation/labelme/labelme/cli/draw_json.py

-#!/usr/bin/env python
-
-import argparse
-import base64
-import json
-import os
-import sys
-
-import matplotlib.pyplot as plt
-
-from labelme import utils
-
-
-PY2 = sys.version_info[0] == 2
-
-
-def main():
-    parser = argparse.ArgumentParser()
-    parser.add_argument('json_file')
-    args = parser.parse_args()
-
-    json_file = args.json_file
-
-    data = json.load(open(json_file))
-
-    if data['imageData']:
-        imageData = data['imageData']
-    else:
-        imagePath = os.path.join(os.path.dirname(json_file), data['imagePath'])
-        with open(imagePath, 'rb') as f:
-            imageData = f.read()
-            imageData = base64.b64encode(imageData).decode('utf-8')
-    img = utils.img_b64_to_arr(imageData)
-
-    label_name_to_value = {'_background_': 0}
-    for shape in sorted(data['shapes'], key=lambda x: x['label']):
-        label_name = shape['label']
-        if label_name in label_name_to_value:
-            label_value = label_name_to_value[label_name]
-        else:
-            label_value = len(label_name_to_value)
-            label_name_to_value[label_name] = label_value
-    lbl = utils.shapes_to_label(img.shape, data['shapes'], label_name_to_value)
-
-    label_names = [None] * (max(label_name_to_value.values()) + 1)
-    for name, value in label_name_to_value.items():
-        label_names[value] = name
-    lbl_viz = utils.draw_label(lbl, img, label_names)
-
-    plt.subplot(121)
-    plt.imshow(img)
-    plt.subplot(122)
-    plt.imshow(lbl_viz)
-    plt.show()
-
-
-if __name__ == '__main__':
-    main()

DataAnnotation/labelme/labelme/cli/draw_label_png.py

-import argparse
-
-import matplotlib.pyplot as plt
-import numpy as np
-import PIL.Image
-
-from labelme.logger import logger
-from labelme import utils
-
-
-def main():
-    parser = argparse.ArgumentParser(
-        formatter_class=argparse.ArgumentDefaultsHelpFormatter)
-    parser.add_argument('label_png', help='label PNG file')
-    args = parser.parse_args()
-
-    lbl = np.asarray(PIL.Image.open(args.label_png))
-
-    logger.info('label shape: {}'.format(lbl.shape))
-    logger.info('unique label values: {}'.format(np.unique(lbl)))
-
-    lbl_viz = utils.draw_label(lbl)
-    plt.imshow(lbl_viz)
-    plt.show()
-
-
-if __name__ == '__main__':
-    main()

DataAnnotation/labelme/labelme/cli/json_to_dataset.py

-import argparse
-import base64
-import json
-import os
-import os.path as osp
-
-import PIL.Image
-import yaml
-
-from labelme.logger import logger
-from labelme import utils
-
-
-def main():
-    logger.warning('This script is aimed to demonstrate how to convert the'
-                   'JSON file to a single image dataset, and not to handle'
-                   'multiple JSON files to generate a real-use dataset.')
-
-    parser = argparse.ArgumentParser()
-    parser.add_argument('json_file')
-    parser.add_argument('-o', '--out', default=None)
-    args = parser.parse_args()
-
-    json_file = args.json_file
-
-    if args.out is None:
-        out_dir = osp.basename(json_file).replace('.', '_')
-        out_dir = osp.join(osp.dirname(json_file), out_dir)
-    else:
-        out_dir = args.out
-    if not osp.exists(out_dir):
-        os.mkdir(out_dir)
-
-    data = json.load(open(json_file))
-    imageData = data.get('imageData')
-
-    if not imageData:
-        imagePath = os.path.join(os.path.dirname(json_file), data['imagePath'])
-        with open(imagePath, 'rb') as f:
-            imageData = f.read()
-            imageData = base64.b64encode(imageData).decode('utf-8')
-    img = utils.img_b64_to_arr(imageData)
-
-    label_name_to_value = {'_background_': 0}
-    for shape in sorted(data['shapes'], key=lambda x: x['label']):
-        label_name = shape['label']
-        if label_name in label_name_to_value:
-            label_value = label_name_to_value[label_name]
-        else:
-            label_value = len(label_name_to_value)
-            label_name_to_value[label_name] = label_value
-    lbl = utils.shapes_to_label(img.shape, data['shapes'], label_name_to_value)
-
-    label_names = [None] * (max(label_name_to_value.values()) + 1)
-    for name, value in label_name_to_value.items():
-        label_names[value] = name
-    lbl_viz = utils.draw_label(lbl, img, label_names)
-
-    PIL.Image.fromarray(img).save(osp.join(out_dir, 'img.png'))
-    utils.lblsave(osp.join(out_dir, 'label.png'), lbl)
-    PIL.Image.fromarray(lbl_viz).save(osp.join(out_dir, 'label_viz.png'))
-
-    with open(osp.join(out_dir, 'label_names.txt'), 'w') as f:
-        for lbl_name in label_names:
-            f.write(lbl_name + '\n')
-
-    logger.warning('info.yaml is being replaced by label_names.txt')
-    info = dict(label_names=label_names)
-    with open(osp.join(out_dir, 'info.yaml'), 'w') as f:
-        yaml.safe_dump(info, f, default_flow_style=False)
-
-    logger.info('Saved to: {}'.format(out_dir))
-
-
-if __name__ == '__main__':
-    main()

DataAnnotation/labelme/labelme/cli/on_docker.py

-#!/usr/bin/env python
-
-from __future__ import print_function
-
-import argparse
-import distutils.spawn
-import json
-import os
-import os.path as osp
-import platform
-import shlex
-import subprocess
-import sys
-
-
-def get_ip():
-    dist = platform.platform().split('-')[0]
-    if dist == 'Linux':
-        return ''
-    elif dist == 'Darwin':
-        cmd = 'ifconfig en0'
-        output = subprocess.check_output(shlex.split(cmd))
-        if str != bytes:  # Python3
-            output = output.decode('utf-8')
-        for row in output.splitlines():
-            cols = row.strip().split(' ')
-            if cols[0] == 'inet':
-                ip = cols[1]
-                return ip
-        else:
-            raise RuntimeError('No ip is found.')
-    else:
-        raise RuntimeError('Unsupported platform.')
-
-
-def labelme_on_docker(in_file, out_file):
-    ip = get_ip()
-    cmd = 'xhost + %s' % ip
-    subprocess.check_output(shlex.split(cmd))
-
-    if out_file:
-        out_file = osp.abspath(out_file)
-        if osp.exists(out_file):
-            raise RuntimeError('File exists: %s' % out_file)
-        else:
-            open(osp.abspath(out_file), 'w')
-
-    cmd = 'docker run -it --rm' \
-        ' -e DISPLAY={0}:0' \
-        ' -e QT_X11_NO_MITSHM=1' \
-        ' -v /tmp/.X11-unix:/tmp/.X11-unix' \
-        ' -v {1}:{2}' \
-        ' -w /home/developer'
-    in_file_a = osp.abspath(in_file)
-    in_file_b = osp.join('/home/developer', osp.basename(in_file))
-    cmd = cmd.format(
-        ip,
-        in_file_a,
-        in_file_b,
-    )
-    if out_file:
-        out_file_a = osp.abspath(out_file)
-        out_file_b = osp.join('/home/developer', osp.basename(out_file))
-        cmd += ' -v {0}:{1}'.format(out_file_a, out_file_b)
-    cmd += ' wkentaro/labelme labelme {0}'.format(in_file_b)
-    if out_file:
-        cmd += ' -O {0}'.format(out_file_b)
-    subprocess.call(shlex.split(cmd))
-
-    if out_file:
-        try:
-            json.load(open(out_file))
-            return out_file
-        except Exception:
-            if open(out_file).read() == '':
-                os.remove(out_file)
-            raise RuntimeError('Annotation is cancelled.')
-
-
-def main():
-    parser = argparse.ArgumentParser()
-    parser.add_argument('in_file', help='Input file or directory.')
-    parser.add_argument('-O', '--output')
-    args = parser.parse_args()
-
-    if not distutils.spawn.find_executable('docker'):
-        print('Please install docker', file=sys.stderr)
-        sys.exit(1)
-
-    try:
-        out_file = labelme_on_docker(args.in_file, args.output)
-        if out_file:
-            print('Saved to: %s' % out_file)
-    except RuntimeError as e:
-        sys.stderr.write(e.__str__() + '\n')
-        sys.exit(1)
-
-
-if __name__ == '__main__':
-    main()

DataAnnotation/labelme/labelme/config/__init__.py

-import os.path as osp
-import shutil
-
-import yaml
-
-from labelme.logger import logger
-
-
-here = osp.dirname(osp.abspath(__file__))
-
-
-def update_dict(target_dict, new_dict, validate_item=None):
-    for key, value in new_dict.items():
-        if validate_item:
-            validate_item(key, value)
-        if key not in target_dict:
-            logger.warn('Skipping unexpected key in config: {}'
-                        .format(key))
-            continue
-        if isinstance(target_dict[key], dict) and \
-                isinstance(value, dict):
-            update_dict(target_dict[key], value, validate_item=validate_item)
-        else:
-            target_dict[key] = value
-
-
-# -----------------------------------------------------------------------------
-
-
-def get_default_config():
-    config_file = osp.join(here, 'default_config.yaml')
-    with open(config_file) as f:
-        config = yaml.safe_load(f)
-
-    # save default config to ~/.labelmerc
-    user_config_file = osp.join(osp.expanduser('~'), '.labelmerc')
-    if not osp.exists(user_config_file):
-        try:
-            shutil.copy(config_file, user_config_file)
-        except Exception:
-            logger.warn('Failed to save config: {}'.format(user_config_file))
-
-    return config
-
-
-def validate_config_item(key, value):
-    if key == 'validate_label' and value not in [None, 'exact', 'instance']:
-        raise ValueError(
-            "Unexpected value for config key 'validate_label': {}"
-            .format(value)
-        )
-    if key == 'labels' and value is not None and len(value) != len(set(value)):
-        raise ValueError(
-            "Duplicates are detected for config key 'labels': {}".format(value)
-        )
-
-
-def get_config(config_from_args=None, config_file=None):
-    # Configuration load order:
-    #
-    #   1. default config (lowest priority)
-    #   2. config file passed by command line argument or ~/.labelmerc
-    #   3. command line argument (highest priority)
-
-    # 1. default config
-    config = get_default_config()
-
-    # 2. config from yaml file
-    if config_file is not None and osp.exists(config_file):
-        with open(config_file) as f:
-            user_config = yaml.safe_load(f) or {}
-        update_dict(config, user_config, validate_item=validate_config_item)
-
-    # 3. command line argument
-    if config_from_args is not None:
-        update_dict(config, config_from_args,
-                    validate_item=validate_config_item)
-
-    return config

DataAnnotation/labelme/labelme/config/default_config.yaml

-auto_save: false
-display_label_popup: true
-instance_label_auto_increment: true
-store_data: true
-keep_prev: false
-logger_level: info
-
-flags: null
-label_flags: null
-labels: null
-file_search: null
-sort_labels: true
-validate_label: null
-
-# main
-flag_dock:
-  show: true
-  closable: true
-  movable: true
-  floatable: true
-label_dock:
-  show: true
-  closable: true
-  movable: true
-  floatable: true
-shape_dock:
-  show: true
-  closable: true
-  movable: true
-  floatable: true
-file_dock:
-  show: true
-  closable: true
-  movable: true
-  floatable: true
-
-# label_dialog
-show_label_text_field: true
-label_completion: startswith
-fit_to_content:
-  column: true
-  row: false
-
-epsilon: 10.0
-
-shortcuts:
-  close: Ctrl+W
-  open: Ctrl+O
-  open_dir: Ctrl+U
-  quit: Ctrl+Q
-  save: Ctrl+S
-  save_as: Ctrl+Shift+S
-  save_to: null
-  delete_file: Ctrl+Delete
-
-  open_next: [D, Ctrl+Shift+D]
-  open_prev: [A, Ctrl+Shift+A]
-
-  zoom_in: [Ctrl++, Ctrl+=]
-  zoom_out: Ctrl+-
-  zoom_to_original: Ctrl+0
-  fit_window: Ctrl+F
-  fit_width: Ctrl+Shift+F
-
-  create_polygon: Ctrl+N
-  create_rectangle: Ctrl+R
-  create_circle: null
-  create_line: null
-  create_point: null
-  create_linestrip: null
-  edit_polygon: Ctrl+J
-  delete_polygon: Delete
-  duplicate_polygon: Ctrl+D
-  undo: Ctrl+Z
-  undo_last_point: [Ctrl+Z, Backspace]
-  add_point_to_edge: Ctrl+Shift+P
-  edit_label: Ctrl+E
-  edit_line_color: Ctrl+L
-  edit_fill_color: Ctrl+Shift+L
-  toggle_keep_prev_mode: Ctrl+P

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-       d="M13.244,27.583v13.104h17.249V27.583H13.244z M19.413,37.209h-3.884v-7.074h3.884V37.209z"
-       id="path667" />
-    <linearGradient
-       id="path228_1_"
-       gradientUnits="userSpaceOnUse"
-       x1="-68.1494"
-       y1="388.4561"
-       x2="-68.1494"
-       y2="404.6693"
-       gradientTransform="matrix(0.1875 0 0 -0.1875 51.5 83.75)">
-      <stop
-         offset="0"
-         style="stop-color:#3399FF"
-         id="stop669" />
-      <stop
-         offset="1"
-         style="stop-color:#000000"
-         id="stop670" />
-      <a:midPointStop
-         offset="0"
-         style="stop-color:#3399FF"
-         id="midPointStop671" />
-      <a:midPointStop
-         offset="0.5"
-         style="stop-color:#3399FF"
-         id="midPointStop672" />
-      <a:midPointStop
-         offset="1"
-         style="stop-color:#000000"
-         id="midPointStop673" />
-    </linearGradient>
-    <rect
-       id="path228"
-       x="37.83"
-       y="9.031"
-       style="fill:url(#path228_1_);"
-       width="1.784"
-       height="1.785" />
-    <polyline
-       id="_x3C_Slice_x3E_"
-       style="fill:none;"
-       points="0,48 0,0 48,0 48,48 " />
-  </g>
-</svg>

DataAnnotation/labelme/labelme/label_file.py

-import base64
-import io
-import json
-import os.path as osp
-
-import PIL.Image
-
-from labelme._version import __version__
-from labelme.logger import logger
-from labelme import PY2
-from labelme import QT4
-from labelme import utils
-
-
-class LabelFileError(Exception):
-    pass
-
-
-class LabelFile(object):
-
-    suffix = '.json'
-
-    def __init__(self, filename=None):
-        self.shapes = ()
-        self.imagePath = None
-        self.imageData = None
-        if filename is not None:
-            self.load(filename)
-        self.filename = filename
-
-    @staticmethod
-    def load_image_file(filename):
-        try:
-            image_pil = PIL.Image.open(filename)
-        except IOError:
-            logger.error('Failed opening image file: {}'.format(filename))
-            return
-
-        # apply orientation to image according to exif
-        image_pil = utils.apply_exif_orientation(image_pil)
-
-        with io.BytesIO() as f:
-            ext = osp.splitext(filename)[1].lower()
-            if PY2 and QT4:
-                format = 'PNG'
-            elif ext in ['.jpg', '.jpeg']:
-                format = 'JPEG'
-            else:
-                format = 'PNG'
-            image_pil.save(f, format=format)
-            f.seek(0)
-            return f.read()
-
-    def load(self, filename):
-        keys = [
-            'imageData',
-            'imagePath',
-            'lineColor',
-            'fillColor',
-            'shapes',  # polygonal annotations
-            'flags',   # image level flags
-            'imageHeight',
-            'imageWidth',
-        ]
-        try:
-            with open(filename, 'rb' if PY2 else 'r') as f:
-                data = json.load(f)
-            if data['imageData'] is not None:
-                imageData = base64.b64decode(data['imageData'])
-                if PY2 and QT4:
-                    imageData = utils.img_data_to_png_data(imageData)
-            else:
-                # relative path from label file to relative path from cwd
-                imagePath = osp.join(osp.dirname(filename), data['imagePath'])
-                imageData = self.load_image_file(imagePath)
-            flags = data.get('flags') or {}
-            imagePath = data['imagePath']
-            self._check_image_height_and_width(
-                base64.b64encode(imageData).decode('utf-8'),
-                data.get('imageHeight'),
-                data.get('imageWidth'),
-            )
-            lineColor = data['lineColor']
-            fillColor = data['fillColor']
-            shapes = (
-                (
-                    s['label'],
-                    s['points'],
-                    s['line_color'],
-                    s['fill_color'],
-                    s.get('shape_type', 'polygon'),
-                    s.get('flags', {}),
-                )
-                for s in data['shapes']
-            )
-        except Exception as e:
-            raise LabelFileError(e)
-
-        otherData = {}
-        for key, value in data.items():
-            if key not in keys:
-                otherData[key] = value
-
-        # Only replace data after everything is loaded.
-        self.flags = flags
-        self.shapes = shapes
-        self.imagePath = imagePath
-        self.imageData = imageData
-        self.lineColor = lineColor
-        self.fillColor = fillColor
-        self.filename = filename
-        self.otherData = otherData
-
-    @staticmethod
-    def _check_image_height_and_width(imageData, imageHeight, imageWidth):
-        img_arr = utils.img_b64_to_arr(imageData)
-        if imageHeight is not None and img_arr.shape[0] != imageHeight:
-            logger.error(
-                'imageHeight does not match with imageData or imagePath, '
-                'so getting imageHeight from actual image.'
-            )
-            imageHeight = img_arr.shape[0]
-        if imageWidth is not None and img_arr.shape[1] != imageWidth:
-            logger.error(
-                'imageWidth does not match with imageData or imagePath, '
-                'so getting imageWidth from actual image.'
-            )
-            imageWidth = img_arr.shape[1]
-        return imageHeight, imageWidth
-
-    def save(
-        self,
-        filename,
-        shapes,
-        imagePath,
-        imageHeight,
-        imageWidth,
-        imageData=None,
-        lineColor=None,
-        fillColor=None,
-        otherData=None,
-        flags=None,
-    ):
-        if imageData is not None:
-            imageData = base64.b64encode(imageData).decode('utf-8')
-            imageHeight, imageWidth = self._check_image_height_and_width(
-                imageData, imageHeight, imageWidth
-            )
-        if otherData is None:
-            otherData = {}
-        if flags is None:
-            flags = {}
-        data = dict(
-            version=__version__,
-            flags=flags,
-            shapes=shapes,
-            lineColor=lineColor,
-            fillColor=fillColor,
-            imagePath=imagePath,
-            imageData=imageData,
-            imageHeight=imageHeight,
-            imageWidth=imageWidth,
-        )
-        for key, value in otherData.items():
-            data[key] = value
-        try:
-            with open(filename, 'wb' if PY2 else 'w') as f:
-                json.dump(data, f, ensure_ascii=False, indent=2)
-            self.filename = filename
-        except Exception as e:
-            raise LabelFileError(e)
-
-    @staticmethod
-    def is_label_file(filename):
-        return osp.splitext(filename)[1].lower() == LabelFile.suffix

DataAnnotation/labelme/labelme/logger.py

-import logging
-
-import termcolor
-
-from . import __appname__
-
-
-COLORS = {
-    'WARNING': 'yellow',
-    'INFO': 'white',
-    'DEBUG': 'blue',
-    'CRITICAL': 'red',
-    'ERROR': 'red',
-}
-
-
-class ColoredFormatter(logging.Formatter):
-
-    def __init__(self, msg, use_color=True):
-        logging.Formatter.__init__(self, msg)
-        self.use_color = use_color
-
-    def format(self, record):
-        levelname = record.levelname
-        if self.use_color and levelname in COLORS:
-            colored_levelname = termcolor.colored(
-                '[{}]'.format(levelname), color=COLORS[levelname]
-            )
-            record.levelname = colored_levelname
-        return logging.Formatter.format(self, record)
-
-
-class ColoredLogger(logging.Logger):
-
-    fmt_filename = termcolor.colored('%(filename)s', attrs={'bold': True})
-    FORMAT = '%(levelname)s %(message)s ({}:%(lineno)d)'.format(fmt_filename)
-
-    def __init__(self, name):
-        logging.Logger.__init__(self, name, logging.INFO)
-
-        color_formatter = ColoredFormatter(self.FORMAT)
-
-        console = logging.StreamHandler()
-        console.setFormatter(color_formatter)
-
-        self.addHandler(console)
-        return
-
-
-logging.setLoggerClass(ColoredLogger)
-logger = logging.getLogger(__appname__)

DataAnnotation/labelme/labelme/main.py

-import argparse
-import codecs
-import logging
-import os
-import sys
-import yaml
-
-from qtpy import QtWidgets
-
-from labelme import __appname__
-from labelme import __version__
-from labelme.app import MainWindow
-from labelme.config import get_config
-from labelme.logger import logger
-from labelme.utils import newIcon
-
-
-def main():
-    parser = argparse.ArgumentParser()
-    parser.add_argument(
-        '--version', '-V', action='store_true', help='show version'
-    )
-    parser.add_argument(
-        '--reset-config', action='store_true', help='reset qt config'
-    )
-    parser.add_argument(
-        '--logger-level',
-        default='info',
-        choices=['debug', 'info', 'warning', 'fatal', 'error'],
-        help='logger level',
-    )
-    parser.add_argument('filename', nargs='?', help='image or label filename')
-    parser.add_argument(
-        '--output',
-        '-O',
-        '-o',
-        help='output file or directory (if it ends with .json it is '
-             'recognized as file, else as directory)'
-    )
-    default_config_file = os.path.join(os.path.expanduser('~'), '.labelmerc')
-    parser.add_argument(
-        '--config',
-        dest='config_file',
-        help='config file (default: %s)' % default_config_file,
-        default=default_config_file,
-    )
-    # config for the gui
-    parser.add_argument(
-        '--nodata',
-        dest='store_data',
-        action='store_false',
-        help='stop storing image data to JSON file',
-        default=argparse.SUPPRESS,
-    )
-    parser.add_argument(
-        '--autosave',
-        dest='auto_save',
-        action='store_true',
-        help='auto save',
-        default=argparse.SUPPRESS,
-    )
-    parser.add_argument(
-        '--nosortlabels',
-        dest='sort_labels',
-        action='store_false',
-        help='stop sorting labels',
-        default=argparse.SUPPRESS,
-    )
-    parser.add_argument(
-        '--flags',
-        help='comma separated list of flags OR file containing flags',
-        default=argparse.SUPPRESS,
-    )
-    parser.add_argument(
-        '--labelflags',
-        dest='label_flags',
-        help='yaml string of label specific flags OR file containing json '
-             'string of label specific flags (ex. {person-\d+: [male, tall], '
-             'dog-\d+: [black, brown, white], .*: [occluded]})',
-        default=argparse.SUPPRESS,
-    )
-    parser.add_argument(
-        '--labels',
-        help='comma separated list of labels OR file containing labels',
-        default=argparse.SUPPRESS,
-    )
-    parser.add_argument(
-        '--validatelabel',
-        dest='validate_label',
-        choices=['exact', 'instance'],
-        help='label validation types',
-        default=argparse.SUPPRESS,
-    )
-    parser.add_argument(
-        '--keep-prev',
-        action='store_true',
-        help='keep annotation of previous frame',
-        default=argparse.SUPPRESS,
-    )
-    parser.add_argument(
-        '--epsilon',
-        type=float,
-        help='epsilon to find nearest vertex on canvas',
-        default=argparse.SUPPRESS,
-    )
-    args = parser.parse_args()
-
-    if args.version:
-        print('{0} {1}'.format(__appname__, __version__))
-        sys.exit(0)
-
-    logger.setLevel(getattr(logging, args.logger_level.upper()))
-
-    if hasattr(args, 'flags'):
-        if os.path.isfile(args.flags):
-            with codecs.open(args.flags, 'r', encoding='utf-8') as f:
-                args.flags = [l.strip() for l in f if l.strip()]
-        else:
-            args.flags = [l for l in args.flags.split(',') if l]
-
-    if hasattr(args, 'labels'):
-        if os.path.isfile(args.labels):
-            with codecs.open(args.labels, 'r', encoding='utf-8') as f:
-                args.labels = [l.strip() for l in f if l.strip()]
-        else:
-            args.labels = [l for l in args.labels.split(',') if l]
-
-    if hasattr(args, 'label_flags'):
-        if os.path.isfile(args.label_flags):
-            with codecs.open(args.label_flags, 'r', encoding='utf-8') as f:
-                args.label_flags = yaml.load(f)
-        else:
-            args.label_flags = yaml.load(args.label_flags)
-
-    config_from_args = args.__dict__
-    config_from_args.pop('version')
-    reset_config = config_from_args.pop('reset_config')
-    filename = config_from_args.pop('filename')
-    output = config_from_args.pop('output')
-    config_file = config_from_args.pop('config_file')
-    config = get_config(config_from_args, config_file)
-
-    if not config['labels'] and config['validate_label']:
-        logger.error('--labels must be specified with --validatelabel or '
-                     'validate_label: true in the config file '
-                     '(ex. ~/.labelmerc).')
-        sys.exit(1)
-
-    output_file = None
-    output_dir = None
-    if output is not None:
-        if output.endswith('.json'):
-            output_file = output
-        else:
-            output_dir = output
-
-    app = QtWidgets.QApplication(sys.argv)
-    app.setApplicationName(__appname__)
-    app.setWindowIcon(newIcon('icon'))
-    win = MainWindow(
-        config=config,
-        filename=filename,
-        output_file=output_file,
-        output_dir=output_dir,
-    )
-
-    if reset_config:
-        logger.info('Resetting Qt config: %s' % win.settings.fileName())
-        win.settings.clear()
-        sys.exit(0)
-
-    win.show()
-    win.raise_()
-    sys.exit(app.exec_())
-
-
-# this main block is required to generate executable by pyinstaller
-if __name__ == '__main__':
-    main()

DataAnnotation/labelme/labelme/shape.py

-import copy
-import math
-
-from qtpy import QtCore
-from qtpy import QtGui
-
-import labelme.utils
-
-
-# TODO(unknown):
-# - [opt] Store paths instead of creating new ones at each paint.
-
-
-DEFAULT_LINE_COLOR = QtGui.QColor(0, 255, 0, 128)
-DEFAULT_FILL_COLOR = QtGui.QColor(255, 0, 0, 128)
-DEFAULT_SELECT_LINE_COLOR = QtGui.QColor(255, 255, 255)
-DEFAULT_SELECT_FILL_COLOR = QtGui.QColor(0, 128, 255, 155)
-DEFAULT_VERTEX_FILL_COLOR = QtGui.QColor(0, 255, 0, 255)
-DEFAULT_HVERTEX_FILL_COLOR = QtGui.QColor(255, 0, 0)
-
-
-class Shape(object):
-
-    P_SQUARE, P_ROUND = 0, 1
-
-    MOVE_VERTEX, NEAR_VERTEX = 0, 1
-
-    # The following class variables influence the drawing of all shape objects.
-    line_color = DEFAULT_LINE_COLOR
-    fill_color = DEFAULT_FILL_COLOR
-    select_line_color = DEFAULT_SELECT_LINE_COLOR
-    select_fill_color = DEFAULT_SELECT_FILL_COLOR
-    vertex_fill_color = DEFAULT_VERTEX_FILL_COLOR
-    hvertex_fill_color = DEFAULT_HVERTEX_FILL_COLOR
-    point_type = P_ROUND
-    point_size = 8
-    scale = 1.0
-
-    def __init__(self, label=None, line_color=None, shape_type=None,
-                 flags=None):
-        self.label = label
-        self.points = []
-        self.fill = False
-        self.selected = False
-        self.shape_type = shape_type
-        self.flags = flags
-
-        self._highlightIndex = None
-        self._highlightMode = self.NEAR_VERTEX
-        self._highlightSettings = {
-            self.NEAR_VERTEX: (4, self.P_ROUND),
-            self.MOVE_VERTEX: (1.5, self.P_SQUARE),
-        }
-
-        self._closed = False
-
-        if line_color is not None:
-            # Override the class line_color attribute
-            # with an object attribute. Currently this
-            # is used for drawing the pending line a different color.
-            self.line_color = line_color
-
-        self.shape_type = shape_type
-
-    @property
-    def shape_type(self):
-        return self._shape_type
-
-    @shape_type.setter
-    def shape_type(self, value):
-        if value is None:
-            value = 'polygon'
-        if value not in ['polygon', 'rectangle', 'point',
-           'line', 'circle', 'linestrip']:
-            raise ValueError('Unexpected shape_type: {}'.format(value))
-        self._shape_type = value
-
-    def close(self):
-        self._closed = True
-
-    def addPoint(self, point):
-        if self.points and point == self.points[0]:
-            self.close()
-        else:
-            self.points.append(point)
-
-    def popPoint(self):
-        if self.points:
-            return self.points.pop()
-        return None
-
-    def insertPoint(self, i, point):
-        self.points.insert(i, point)
-
-    def isClosed(self):
-        return self._closed
-
-    def setOpen(self):
-        self._closed = False
-
-    def getRectFromLine(self, pt1, pt2):
-        x1, y1 = pt1.x(), pt1.y()
-        x2, y2 = pt2.x(), pt2.y()
-        return QtCore.QRectF(x1, y1, x2 - x1, y2 - y1)
-
-    def paint(self, painter):
-        if self.points:
-            color = self.select_line_color \
-                if self.selected else self.line_color
-            pen = QtGui.QPen(color)
-            # Try using integer sizes for smoother drawing(?)
-            pen.setWidth(max(1, int(round(2.0 / self.scale))))
-            painter.setPen(pen)
-
-            line_path = QtGui.QPainterPath()
-            vrtx_path = QtGui.QPainterPath()
-
-            if self.shape_type == 'rectangle':
-                assert len(self.points) in [1, 2]
-                if len(self.points) == 2:
-                    rectangle = self.getRectFromLine(*self.points)
-                    line_path.addRect(rectangle)
-                for i in range(len(self.points)):
-                    self.drawVertex(vrtx_path, i)
-            elif self.shape_type == "circle":
-                assert len(self.points) in [1, 2]
-                if len(self.points) == 2:
-                    rectangle = self.getCircleRectFromLine(self.points)
-                    line_path.addEllipse(rectangle)
-                for i in range(len(self.points)):
-                    self.drawVertex(vrtx_path, i)
-            elif self.shape_type == "linestrip":
-                line_path.moveTo(self.points[0])
-                for i, p in enumerate(self.points):
-                    line_path.lineTo(p)
-                    self.drawVertex(vrtx_path, i)
-            else:
-                line_path.moveTo(self.points[0])
-                # Uncommenting the following line will draw 2 paths
-                # for the 1st vertex, and make it non-filled, which
-                # may be desirable.
-                # self.drawVertex(vrtx_path, 0)
-
-                for i, p in enumerate(self.points):
-                    line_path.lineTo(p)
-                    self.drawVertex(vrtx_path, i)
-                if self.isClosed():
-                    line_path.lineTo(self.points[0])
-
-            painter.drawPath(line_path)
-            painter.drawPath(vrtx_path)
-            painter.fillPath(vrtx_path, self.vertex_fill_color)
-            if self.fill:
-                color = self.select_fill_color \
-                    if self.selected else self.fill_color
-                painter.fillPath(line_path, color)
-
-    def drawVertex(self, path, i):
-        d = self.point_size / self.scale
-        shape = self.point_type
-        point = self.points[i]
-        if i == self._highlightIndex:
-            size, shape = self._highlightSettings[self._highlightMode]
-            d *= size
-        if self._highlightIndex is not None:
-            self.vertex_fill_color = self.hvertex_fill_color
-        else:
-            self.vertex_fill_color = Shape.vertex_fill_color
-        if shape == self.P_SQUARE:
-            path.addRect(point.x() - d / 2, point.y() - d / 2, d, d)
-        elif shape == self.P_ROUND:
-            path.addEllipse(point, d / 2.0, d / 2.0)
-        else:
-            assert False, "unsupported vertex shape"
-
-    def nearestVertex(self, point, epsilon):
-        min_distance = float('inf')
-        min_i = None
-        for i, p in enumerate(self.points):
-            dist = labelme.utils.distance(p - point)
-            if dist <= epsilon and dist < min_distance:
-                min_distance = dist
-                min_i = i
-        return min_i
-
-    def nearestEdge(self, point, epsilon):
-        min_distance = float('inf')
-        post_i = None
-        for i in range(len(self.points)):
-            line = [self.points[i - 1], self.points[i]]
-            dist = labelme.utils.distancetoline(point, line)
-            if dist <= epsilon and dist < min_distance:
-                min_distance = dist
-                post_i = i
-        return post_i
-
-    def containsPoint(self, point):
-        return self.makePath().contains(point)
-
-    def getCircleRectFromLine(self, line):
-        """Computes parameters to draw with `QPainterPath::addEllipse`"""
-        if len(line) != 2:
-            return None
-        (c, point) = line
-        r = line[0] - line[1]
-        d = math.sqrt(math.pow(r.x(), 2) + math.pow(r.y(), 2))
-        rectangle = QtCore.QRectF(c.x() - d, c.y() - d, 2 * d, 2 * d)
-        return rectangle
-
-    def makePath(self):
-        if self.shape_type == 'rectangle':
-            path = QtGui.QPainterPath()
-            if len(self.points) == 2:
-                rectangle = self.getRectFromLine(*self.points)
-                path.addRect(rectangle)
-        elif self.shape_type == "circle":
-            path = QtGui.QPainterPath()
-            if len(self.points) == 2:
-                rectangle = self.getCircleRectFromLine(self.points)
-                path.addEllipse(rectangle)
-        else:
-            path = QtGui.QPainterPath(self.points[0])
-            for p in self.points[1:]:
-                path.lineTo(p)
-        return path
-
-    def boundingRect(self):
-        return self.makePath().boundingRect()
-
-    def moveBy(self, offset):
-        self.points = [p + offset for p in self.points]
-
-    def moveVertexBy(self, i, offset):
-        self.points[i] = self.points[i] + offset
-
-    def highlightVertex(self, i, action):
-        self._highlightIndex = i
-        self._highlightMode = action
-
-    def highlightClear(self):
-        self._highlightIndex = None
-
-    def copy(self):
-        return copy.deepcopy(self)
-
-    def __len__(self):
-        return len(self.points)
-
-    def __getitem__(self, key):
-        return self.points[key]
-
-    def __setitem__(self, key, value):
-        self.points[key] = value

DataAnnotation/labelme/labelme/testing.py

-import json
-import os.path as osp
-
-import labelme.utils
-
-
-def assert_labelfile_sanity(filename):
-    assert osp.exists(filename)
-
-    data = json.load(open(filename))
-
-    assert 'imagePath' in data
-    imageData = data.get('imageData', None)
-    if imageData is None:
-        assert osp.exists(data['imagePath'])
-    img = labelme.utils.img_b64_to_arr(imageData)
-
-    H, W = img.shape[:2]
-    assert 'shapes' in data
-    for shape in data['shapes']:
-        assert 'label' in shape
-        assert 'points' in shape
-        for x, y in shape['points']:
-            assert 0 <= x <= W
-            assert 0 <= y <= H

DataAnnotation/labelme/labelme/utils/__init__.py

-# flake8: noqa
-
-from ._io import lblsave
-
-from .image import apply_exif_orientation
-from .image import img_arr_to_b64
-from .image import img_b64_to_arr
-from .image import img_data_to_png_data
-
-from .shape import labelme_shapes_to_label
-from .shape import masks_to_bboxes
-from .shape import polygons_to_mask
-from .shape import shape_to_mask
-from .shape import shapes_to_label
-
-from .draw import draw_instances
-from .draw import draw_label
-from .draw import label_colormap
-from .draw import label2rgb
-
-from .qt import newIcon
-from .qt import newButton
-from .qt import newAction
-from .qt import addActions
-from .qt import labelValidator
-from .qt import struct
-from .qt import distance
-from .qt import distancetoline
-from .qt import fmtShortcut

DataAnnotation/labelme/labelme/utils/_io.py

-import os.path as osp
-
-import numpy as np
-import PIL.Image
-
-from labelme.utils.draw import label_colormap
-
-
-def lblsave(filename, lbl):
-    if osp.splitext(filename)[1] != '.png':
-        filename += '.png'
-    # Assume label ranses [-1, 254] for int32,
-    # and [0, 255] for uint8 as VOC.
-    if lbl.min() >= -1 and lbl.max() < 255:
-        lbl_pil = PIL.Image.fromarray(lbl.astype(np.uint8), mode='P')
-        colormap = label_colormap(255)
-        lbl_pil.putpalette((colormap * 255).astype(np.uint8).flatten())
-        lbl_pil.save(filename)
-    else:
-        raise ValueError(
-            '[%s] Cannot save the pixel-wise class label as PNG. '
-            'Please consider using the .npy format.' % filename
-        )

DataAnnotation/labelme/labelme/utils/draw.py

-import io
-import os.path as osp
-
-import numpy as np
-import PIL.Image
-import PIL.ImageDraw
-import PIL.ImageFont
-
-
-def label_colormap(N=256):
-
-    def bitget(byteval, idx):
-        return ((byteval & (1 << idx)) != 0)
-
-    cmap = np.zeros((N, 3))
-    for i in range(0, N):
-        id = i
-        r, g, b = 0, 0, 0
-        for j in range(0, 8):
-            r = np.bitwise_or(r, (bitget(id, 0) << 7 - j))
-            g = np.bitwise_or(g, (bitget(id, 1) << 7 - j))
-            b = np.bitwise_or(b, (bitget(id, 2) << 7 - j))
-            id = (id >> 3)
-        cmap[i, 0] = r
-        cmap[i, 1] = g
-        cmap[i, 2] = b
-    cmap = cmap.astype(np.float32) / 255
-    return cmap
-
-
-def _validate_colormap(colormap, n_labels):
-    if colormap is None:
-        colormap = label_colormap(n_labels)
-    else:
-        assert colormap.shape == (colormap.shape[0], 3), \
-            'colormap must be sequence of RGB values'
-        assert 0 <= colormap.min() and colormap.max() <= 1, \
-            'colormap must ranges 0 to 1'
-    return colormap
-
-
-# similar function as skimage.color.label2rgb
-def label2rgb(
-    lbl, img=None, n_labels=None, alpha=0.5, thresh_suppress=0, colormap=None,
-):
-    if n_labels is None:
-        n_labels = len(np.unique(lbl))
-
-    colormap = _validate_colormap(colormap, n_labels)
-    colormap = (colormap * 255).astype(np.uint8)
-
-    lbl_viz = colormap[lbl]
-    lbl_viz[lbl == -1] = (0, 0, 0)  # unlabeled
-
-    if img is not None:
-        img_gray = PIL.Image.fromarray(img).convert('LA')
-        img_gray = np.asarray(img_gray.convert('RGB'))
-        # img_gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
-        # img_gray = cv2.cvtColor(img_gray, cv2.COLOR_GRAY2RGB)
-        lbl_viz = alpha * lbl_viz + (1 - alpha) * img_gray
-        lbl_viz = lbl_viz.astype(np.uint8)
-
-    return lbl_viz
-
-
-def draw_label(label, img=None, label_names=None, colormap=None, **kwargs):
-    """Draw pixel-wise label with colorization and label names.
-
-    label: ndarray, (H, W)
-        Pixel-wise labels to colorize.
-    img: ndarray, (H, W, 3), optional
-        Image on which the colorized label will be drawn.
-    label_names: iterable
-        List of label names.
-    """
-    import matplotlib.pyplot as plt
-
-    backend_org = plt.rcParams['backend']
-    plt.switch_backend('agg')
-
-    plt.subplots_adjust(left=0, right=1, top=1, bottom=0,
-                        wspace=0, hspace=0)
-    plt.margins(0, 0)
-    plt.gca().xaxis.set_major_locator(plt.NullLocator())
-    plt.gca().yaxis.set_major_locator(plt.NullLocator())
-
-    if label_names is None:
-        label_names = [str(l) for l in range(label.max() + 1)]
-
-    colormap = _validate_colormap(colormap, len(label_names))
-
-    label_viz = label2rgb(
-        label, img, n_labels=len(label_names), colormap=colormap, **kwargs
-    )
-    plt.imshow(label_viz)
-    plt.axis('off')
-
-    plt_handlers = []
-    plt_titles = []
-    for label_value, label_name in enumerate(label_names):
-        if label_value not in label:
-            continue
-        fc = colormap[label_value]
-        p = plt.Rectangle((0, 0), 1, 1, fc=fc)
-        plt_handlers.append(p)
-        plt_titles.append('{value}: {name}'
-                          .format(value=label_value, name=label_name))
-    plt.legend(plt_handlers, plt_titles, loc='lower right', framealpha=.5)
-
-    f = io.BytesIO()
-    plt.savefig(f, bbox_inches='tight', pad_inches=0)
-    plt.cla()
-    plt.close()
-
-    plt.switch_backend(backend_org)
-
-    out_size = (label_viz.shape[1], label_viz.shape[0])
-    out = PIL.Image.open(f).resize(out_size, PIL.Image.BILINEAR).convert('RGB')
-    out = np.asarray(out)
-    return out
-
-
-def draw_instances(
-    image=None,
-    bboxes=None,
-    labels=None,
-    masks=None,
-    captions=None,
-):
-    import matplotlib
-
-    # TODO(wkentaro)
-    assert image is not None
-    assert bboxes is not None
-    assert labels is not None
-    assert masks is None
-    assert captions is not None
-
-    viz = PIL.Image.fromarray(image)
-    draw = PIL.ImageDraw.ImageDraw(viz)
-
-    font_path = osp.join(
-        osp.dirname(matplotlib.__file__),
-        'mpl-data/fonts/ttf/DejaVuSans.ttf'
-    )
-    font = PIL.ImageFont.truetype(font_path)
-
-    colormap = label_colormap(255)
-    for bbox, label, caption in zip(bboxes, labels, captions):
-        color = colormap[label]
-        color = tuple((color * 255).astype(np.uint8).tolist())
-
-        xmin, ymin, xmax, ymax = bbox
-        draw.rectangle((xmin, ymin, xmax, ymax), outline=color)
-        draw.text((xmin, ymin), caption, font=font)
-
-    return np.asarray(viz)

DataAnnotation/labelme/labelme/utils/image.py

-import base64
-import io
-
-import numpy as np
-import PIL.ExifTags
-import PIL.Image
-import PIL.ImageOps
-
-
-def img_b64_to_arr(img_b64):
-    f = io.BytesIO()
-    f.write(base64.b64decode(img_b64))
-    img_arr = np.array(PIL.Image.open(f))
-    return img_arr
-
-
-def img_arr_to_b64(img_arr):
-    img_pil = PIL.Image.fromarray(img_arr)
-    f = io.BytesIO()
-    img_pil.save(f, format='PNG')
-    img_bin = f.getvalue()
-    if hasattr(base64, 'encodebytes'):
-        img_b64 = base64.encodebytes(img_bin)
-    else:
-        img_b64 = base64.encodestring(img_bin)
-    return img_b64
-
-
-def img_data_to_png_data(img_data):
-    with io.BytesIO() as f:
-        f.write(img_data)
-        img = PIL.Image.open(f)
-
-        with io.BytesIO() as f:
-            img.save(f, 'PNG')
-            f.seek(0)
-            return f.read()
-
-
-def apply_exif_orientation(image):
-    try:
-        exif = image._getexif()
-    except AttributeError:
-        exif = None
-
-    if exif is None:
-        return image
-
-    exif = {
-        PIL.ExifTags.TAGS[k]: v
-        for k, v in exif.items()
-        if k in PIL.ExifTags.TAGS
-    }
-
-    orientation = exif.get('Orientation', None)
-
-    if orientation == 1:
-        # do nothing
-        return image
-    elif orientation == 2:
-        # left-to-right mirror
-        return PIL.ImageOps.mirror(image)
-    elif orientation == 3:
-        # rotate 180
-        return image.transpose(PIL.Image.ROTATE_180)
-    elif orientation == 4:
-        # top-to-bottom mirror
-        return PIL.ImageOps.flip(image)
-    elif orientation == 5:
-        # top-to-left mirror
-        return PIL.ImageOps.mirror(image.transpose(PIL.Image.ROTATE_270))
-    elif orientation == 6:
-        # rotate 270
-        return image.transpose(PIL.Image.ROTATE_270)
-    elif orientation == 7:
-        # top-to-right mirror
-        return PIL.ImageOps.mirror(image.transpose(PIL.Image.ROTATE_90))
-    elif orientation == 8:
-        # rotate 90
-        return image.transpose(PIL.Image.ROTATE_90)
-    else:
-        return image

DataAnnotation/labelme/labelme/utils/qt.py

-from math import sqrt
-import os.path as osp
-
-import numpy as np
-
-from qtpy import QtCore
-from qtpy import QtGui
-from qtpy import QtWidgets
-
-
-here = osp.dirname(osp.abspath(__file__))
-
-
-def newIcon(icon):
-    icons_dir = osp.join(here, '../icons')
-    return QtGui.QIcon(osp.join(':/', icons_dir, '%s.png' % icon))
-
-
-def newButton(text, icon=None, slot=None):
-    b = QtWidgets.QPushButton(text)
-    if icon is not None:
-        b.setIcon(newIcon(icon))
-    if slot is not None:
-        b.clicked.connect(slot)
-    return b
-
-
-def newAction(parent, text, slot=None, shortcut=None, icon=None,
-              tip=None, checkable=False, enabled=True):
-    """Create a new action and assign callbacks, shortcuts, etc."""
-    a = QtWidgets.QAction(text, parent)
-    if icon is not None:
-        a.setIconText(text.replace(' ', '\n'))
-        a.setIcon(newIcon(icon))
-    if shortcut is not None:
-        if isinstance(shortcut, (list, tuple)):
-            a.setShortcuts(shortcut)
-        else:
-            a.setShortcut(shortcut)
-    if tip is not None:
-        a.setToolTip(tip)
-        a.setStatusTip(tip)
-    if slot is not None:
-        a.triggered.connect(slot)
-    if checkable:
-        a.setCheckable(True)
-    a.setEnabled(enabled)
-    return a
-
-
-def addActions(widget, actions):
-    for action in actions:
-        if action is None:
-            widget.addSeparator()
-        elif isinstance(action, QtWidgets.QMenu):
-            widget.addMenu(action)
-        else:
-            widget.addAction(action)
-
-
-def labelValidator():
-    return QtGui.QRegExpValidator(QtCore.QRegExp(r'^[^ \t].+'), None)
-
-
-class struct(object):
-    def __init__(self, **kwargs):
-        self.__dict__.update(kwargs)
-
-
-def distance(p):
-    return sqrt(p.x() * p.x() + p.y() * p.y())
-
-
-def distancetoline(point, line):
-    p1, p2 = line
-    p1 = np.array([p1.x(), p1.y()])
-    p2 = np.array([p2.x(), p2.y()])
-    p3 = np.array([point.x(), point.y()])
-    if np.dot((p3 - p1), (p2 - p1)) < 0:
-        return np.linalg.norm(p3 - p1)
-    if np.dot((p3 - p2), (p1 - p2)) < 0:
-        return np.linalg.norm(p3 - p2)
-    return np.linalg.norm(np.cross(p2 - p1, p1 - p3)) / np.linalg.norm(p2 - p1)
-
-
-def fmtShortcut(text):
-    mod, key = text.split('+', 1)
-    return '<b>%s</b>+<b>%s</b>' % (mod, key)

DataAnnotation/labelme/labelme/utils/shape.py

-import math
-
-import numpy as np
-import PIL.Image
-import PIL.ImageDraw
-
-from labelme.logger import logger
-
-
-def polygons_to_mask(img_shape, polygons, shape_type=None):
-    logger.warning(
-        "The 'polygons_to_mask' function is deprecated, "
-        "use 'shape_to_mask' instead."
-    )
-    return shape_to_mask(img_shape, points=polygons, shape_type=shape_type)
-
-
-def shape_to_mask(img_shape, points, shape_type=None,
-                  line_width=10, point_size=5):
-    mask = np.zeros(img_shape[:2], dtype=np.uint8)
-    mask = PIL.Image.fromarray(mask)
-    draw = PIL.ImageDraw.Draw(mask)
-    xy = [tuple(point) for point in points]
-    if shape_type == 'circle':
-        assert len(xy) == 2, 'Shape of shape_type=circle must have 2 points'
-        (cx, cy), (px, py) = xy
-        d = math.sqrt((cx - px) ** 2 + (cy - py) ** 2)
-        draw.ellipse([cx - d, cy - d, cx + d, cy + d], outline=1, fill=1)
-    elif shape_type == 'rectangle':
-        assert len(xy) == 2, 'Shape of shape_type=rectangle must have 2 points'
-        draw.rectangle(xy, outline=1, fill=1)
-    elif shape_type == 'line':
-        assert len(xy) == 2, 'Shape of shape_type=line must have 2 points'
-        draw.line(xy=xy, fill=1, width=line_width)
-    elif shape_type == 'linestrip':
-        draw.line(xy=xy, fill=1, width=line_width)
-    elif shape_type == 'point':
-        assert len(xy) == 1, 'Shape of shape_type=point must have 1 points'
-        cx, cy = xy[0]
-        r = point_size
-        draw.ellipse([cx - r, cy - r, cx + r, cy + r], outline=1, fill=1)
-    else:
-        assert len(xy) > 2, 'Polygon must have points more than 2'
-        draw.polygon(xy=xy, outline=1, fill=1)
-    mask = np.array(mask, dtype=bool)
-    return mask
-
-
-def shapes_to_label(img_shape, shapes, label_name_to_value, type='class'):
-    assert type in ['class', 'instance']
-
-    cls = np.zeros(img_shape[:2], dtype=np.int32)
-    if type == 'instance':
-        ins = np.zeros(img_shape[:2], dtype=np.int32)
-        instance_names = ['_background_']
-    for shape in shapes:
-        points = shape['points']
-        label = shape['label']
-        shape_type = shape.get('shape_type', None)
-        if type == 'class':
-            cls_name = label
-        elif type == 'instance':
-            cls_name = label.split('-')[0]
-            if label not in instance_names:
-                instance_names.append(label)
-            ins_id = instance_names.index(label)
-        cls_id = label_name_to_value[cls_name]
-        mask = shape_to_mask(img_shape[:2], points, shape_type)
-        cls[mask] = cls_id
-        if type == 'instance':
-            ins[mask] = ins_id
-
-    if type == 'instance':
-        return cls, ins
-    return cls
-
-
-def labelme_shapes_to_label(img_shape, shapes):
-    logger.warn('labelme_shapes_to_label is deprecated, so please use '
-                'shapes_to_label.')
-
-    label_name_to_value = {'_background_': 0}
-    for shape in shapes:
-        label_name = shape['label']
-        if label_name in label_name_to_value:
-            label_value = label_name_to_value[label_name]
-        else:
-            label_value = len(label_name_to_value)
-            label_name_to_value[label_name] = label_value
-
-    lbl = shapes_to_label(img_shape, shapes, label_name_to_value)
-    return lbl, label_name_to_value
-
-
-def masks_to_bboxes(masks):
-    if masks.ndim != 3:
-        raise ValueError(
-            'masks.ndim must be 3, but it is {}'
-            .format(masks.ndim)
-        )
-    if masks.dtype != bool:
-        raise ValueError(
-            'masks.dtype must be bool type, but it is {}'
-            .format(masks.dtype)
-        )
-    bboxes = []
-    for mask in masks:
-        where = np.argwhere(mask)
-        (y1, x1), (y2, x2) = where.min(0), where.max(0) + 1
-        bboxes.append((y1, x1, y2, x2))
-    bboxes = np.asarray(bboxes, dtype=np.float32)
-    return bboxes

DataAnnotation/labelme/labelme/widgets/__init__.py

-# flake8: noqa
-
-from .canvas import Canvas
-
-from .color_dialog import ColorDialog
-
-from .escapable_qlist_widget import EscapableQListWidget
-
-from .label_dialog import LabelDialog
-from .label_dialog import LabelQLineEdit
-
-from .label_qlist_widget import LabelQListWidget
-
-from .tool_bar import ToolBar
-
-from .zoom_widget import ZoomWidget

DataAnnotation/labelme/labelme/widgets/canvas.py

-from qtpy import QtCore
-from qtpy import QtGui
-from qtpy import QtWidgets
-
-from labelme import QT5
-from labelme.shape import Shape
-import labelme.utils
-
-
-# TODO(unknown):
-# - [maybe] Find optimal epsilon value.
-
-
-CURSOR_DEFAULT = QtCore.Qt.ArrowCursor
-CURSOR_POINT = QtCore.Qt.PointingHandCursor
-CURSOR_DRAW = QtCore.Qt.CrossCursor
-CURSOR_MOVE = QtCore.Qt.ClosedHandCursor
-CURSOR_GRAB = QtCore.Qt.OpenHandCursor
-
-
-class Canvas(QtWidgets.QWidget):
-
-    zoomRequest = QtCore.Signal(int, QtCore.QPoint)
-    scrollRequest = QtCore.Signal(int, int)
-    newShape = QtCore.Signal()
-    selectionChanged = QtCore.Signal(list)
-    shapeMoved = QtCore.Signal()
-    drawingPolygon = QtCore.Signal(bool)
-    edgeSelected = QtCore.Signal(bool)
-
-    CREATE, EDIT = 0, 1
-
-    # polygon, rectangle, line, or point
-    _createMode = 'polygon'
-
-    _fill_drawing = False
-
-    def __init__(self, *args, **kwargs):
-        self.epsilon = kwargs.pop('epsilon', 10.0)
-        super(Canvas, self).__init__(*args, **kwargs)
-        # Initialise local state.
-        self.mode = self.EDIT
-        self.shapes = []
-        self.shapesBackups = []
-        self.current = None
-        self.selectedShapes = []  # save the selected shapes here
-        self.selectedShapesCopy = []
-        self.lineColor = QtGui.QColor(0, 0, 255)
-        # self.line represents:
-        #   - createMode == 'polygon': edge from last point to current
-        #   - createMode == 'rectangle': diagonal line of the rectangle
-        #   - createMode == 'line': the line
-        #   - createMode == 'point': the point
-        self.line = Shape(line_color=self.lineColor)
-        self.prevPoint = QtCore.QPoint()
-        self.prevMovePoint = QtCore.QPoint()
-        self.offsets = QtCore.QPoint(), QtCore.QPoint()
-        self.scale = 1.0
-        self.pixmap = QtGui.QPixmap()
-        self.visible = {}
-        self._hideBackround = False
-        self.hideBackround = False
-        self.hShape = None
-        self.hVertex = None
-        self.hEdge = None
-        self.movingShape = False
-        self._painter = QtGui.QPainter()
-        self._cursor = CURSOR_DEFAULT
-        # Menus:
-        # 0: right-click without selection and dragging of shapes
-        # 1: right-click with selection and dragging of shapes
-        self.menus = (QtWidgets.QMenu(), QtWidgets.QMenu())
-        # Set widget options.
-        self.setMouseTracking(True)
-        self.setFocusPolicy(QtCore.Qt.WheelFocus)
-
-    def fillDrawing(self):
-        return self._fill_drawing
-
-    def setFillDrawing(self, value):
-        self._fill_drawing = value
-
-    @property
-    def createMode(self):
-        return self._createMode
-
-    @createMode.setter
-    def createMode(self, value):
-        if value not in ['polygon', 'rectangle', 'circle',
-           'line', 'point', 'linestrip']:
-            raise ValueError('Unsupported createMode: %s' % value)
-        self._createMode = value
-
-    def storeShapes(self):
-        shapesBackup = []
-        for shape in self.shapes:
-            shapesBackup.append(shape.copy())
-        if len(self.shapesBackups) >= 10:
-            self.shapesBackups = self.shapesBackups[-9:]
-        self.shapesBackups.append(shapesBackup)
-
-    @property
-    def isShapeRestorable(self):
-        if len(self.shapesBackups) < 2:
-            return False
-        return True
-
-    def restoreShape(self):
-        if not self.isShapeRestorable:
-            return
-        self.shapesBackups.pop()  # latest
-        shapesBackup = self.shapesBackups.pop()
-        self.shapes = shapesBackup
-        self.selectedShapes = []
-        for shape in self.shapes:
-            shape.selected = False
-        self.repaint()
-
-    def enterEvent(self, ev):
-        self.overrideCursor(self._cursor)
-
-    def leaveEvent(self, ev):
-        self.restoreCursor()
-
-    def focusOutEvent(self, ev):
-        self.restoreCursor()
-
-    def isVisible(self, shape):
-        return self.visible.get(shape, True)
-
-    def drawing(self):
-        return self.mode == self.CREATE
-
-    def editing(self):
-        return self.mode == self.EDIT
-
-    def setEditing(self, value=True):
-        self.mode = self.EDIT if value else self.CREATE
-        if not value:  # Create
-            self.unHighlight()
-            self.deSelectShape()
-
-    def unHighlight(self):
-        if self.hShape:
-            self.hShape.highlightClear()
-        self.hVertex = self.hShape = None
-
-    def selectedVertex(self):
-        return self.hVertex is not None
-
-    def mouseMoveEvent(self, ev):
-        """Update line with last point and current coordinates."""
-        try:
-            if QT5:
-                pos = self.transformPos(ev.localPos())
-            else:
-                pos = self.transformPos(ev.posF())
-        except AttributeError:
-            return
-
-        self.prevMovePoint = pos
-        self.restoreCursor()
-
-        # Polygon drawing.
-        if self.drawing():
-            self.line.shape_type = self.createMode
-
-            self.overrideCursor(CURSOR_DRAW)
-            if not self.current:
-                return
-
-            color = self.lineColor
-            if self.outOfPixmap(pos):
-                # Don't allow the user to draw outside the pixmap.
-                # Project the point to the pixmap's edges.
-                pos = self.intersectionPoint(self.current[-1], pos)
-            elif len(self.current) > 1 and self.createMode == 'polygon' and\
-                    self.closeEnough(pos, self.current[0]):
-                # Attract line to starting point and
-                # colorise to alert the user.
-                pos = self.current[0]
-                color = self.current.line_color
-                self.overrideCursor(CURSOR_POINT)
-                self.current.highlightVertex(0, Shape.NEAR_VERTEX)
-            if self.createMode in ['polygon', 'linestrip']:
-                self.line[0] = self.current[-1]
-                self.line[1] = pos
-            elif self.createMode == 'rectangle':
-                self.line.points = [self.current[0], pos]
-                self.line.close()
-            elif self.createMode == 'circle':
-                self.line.points = [self.current[0], pos]
-                self.line.shape_type = "circle"
-            elif self.createMode == 'line':
-                self.line.points = [self.current[0], pos]
-                self.line.close()
-            elif self.createMode == 'point':
-                self.line.points = [self.current[0]]
-                self.line.close()
-            self.line.line_color = color
-            self.repaint()
-            self.current.highlightClear()
-            return
-
-        # Polygon copy moving.
-        if QtCore.Qt.RightButton & ev.buttons():
-            if self.selectedShapesCopy and self.prevPoint:
-                self.overrideCursor(CURSOR_MOVE)
-                self.boundedMoveShapes(self.selectedShapesCopy, pos)
-                self.repaint()
-            elif self.selectedShapes:
-                self.selectedShapesCopy = \
-                    [s.copy() for s in self.selectedShapes]
-                self.repaint()
-            return
-
-        # Polygon/Vertex moving.
-        self.movingShape = False
-        if QtCore.Qt.LeftButton & ev.buttons():
-            if self.selectedVertex():
-                self.boundedMoveVertex(pos)
-                self.repaint()
-                self.movingShape = True
-            elif self.selectedShapes and self.prevPoint:
-                self.overrideCursor(CURSOR_MOVE)
-                self.boundedMoveShapes(self.selectedShapes, pos)
-                self.repaint()
-                self.movingShape = True
-            return
-
-        # Just hovering over the canvas, 2 posibilities:
-        # - Highlight shapes
-        # - Highlight vertex
-        # Update shape/vertex fill and tooltip value accordingly.
-        self.setToolTip("Image")
-        for shape in reversed([s for s in self.shapes if self.isVisible(s)]):
-            # Look for a nearby vertex to highlight. If that fails,
-            # check if we happen to be inside a shape.
-            index = shape.nearestVertex(pos, self.epsilon / self.scale)
-            index_edge = shape.nearestEdge(pos, self.epsilon / self.scale)
-            if index is not None:
-                if self.selectedVertex():
-                    self.hShape.highlightClear()
-                self.hVertex = index
-                self.hShape = shape
-                self.hEdge = index_edge
-                shape.highlightVertex(index, shape.MOVE_VERTEX)
-                self.overrideCursor(CURSOR_POINT)
-                self.setToolTip("Click & drag to move point")
-                self.setStatusTip(self.toolTip())
-                self.update()
-                break
-            elif shape.containsPoint(pos):
-                if self.selectedVertex():
-                    self.hShape.highlightClear()
-                self.hVertex = None
-                self.hShape = shape
-                self.hEdge = index_edge
-                self.setToolTip(
-                    "Click & drag to move shape '%s'" % shape.label)
-                self.setStatusTip(self.toolTip())
-                self.overrideCursor(CURSOR_GRAB)
-                self.update()
-                break
-        else:  # Nothing found, clear highlights, reset state.
-            if self.hShape:
-                self.hShape.highlightClear()
-                self.update()
-            self.hVertex, self.hShape, self.hEdge = None, None, None
-        self.edgeSelected.emit(self.hEdge is not None)
-
-    def addPointToEdge(self):
-        if (self.hShape is None and
-                self.hEdge is None and
-                self.prevMovePoint is None):
-            return
-        shape = self.hShape
-        index = self.hEdge
-        point = self.prevMovePoint
-        shape.insertPoint(index, point)
-        shape.highlightVertex(index, shape.MOVE_VERTEX)
-        self.hShape = shape
-        self.hVertex = index
-        self.hEdge = None
-
-    def mousePressEvent(self, ev):
-        if QT5:
-            pos = self.transformPos(ev.localPos())
-        else:
-            pos = self.transformPos(ev.posF())
-        if ev.button() == QtCore.Qt.LeftButton:
-            if self.drawing():
-                if self.current:
-                    # Add point to existing shape.
-                    if self.createMode == 'polygon':
-                        self.current.addPoint(self.line[1])
-                        self.line[0] = self.current[-1]
-                        if self.current.isClosed():
-                            self.finalise()
-                    elif self.createMode in ['rectangle', 'circle', 'line']:
-                        assert len(self.current.points) == 1
-                        self.current.points = self.line.points
-                        self.finalise()
-                    elif self.createMode == 'linestrip':
-                        self.current.addPoint(self.line[1])
-                        self.line[0] = self.current[-1]
-                        if int(ev.modifiers()) == QtCore.Qt.ControlModifier:
-                            self.finalise()
-                elif not self.outOfPixmap(pos):
-                    # Create new shape.
-                    self.current = Shape(shape_type=self.createMode)
-                    self.current.addPoint(pos)
-                    if self.createMode == 'point':
-                        self.finalise()
-                    else:
-                        if self.createMode == 'circle':
-                            self.current.shape_type = 'circle'
-                        self.line.points = [pos, pos]
-                        self.setHiding()
-                        self.drawingPolygon.emit(True)
-                        self.update()
-            else:
-                group_mode = (int(ev.modifiers()) == QtCore.Qt.ControlModifier)
-                self.selectShapePoint(pos, multiple_selection_mode=group_mode)
-                self.prevPoint = pos
-                self.repaint()
-        elif ev.button() == QtCore.Qt.RightButton and self.editing():
-            group_mode = (int(ev.modifiers()) == QtCore.Qt.ControlModifier)
-            self.selectShapePoint(pos, multiple_selection_mode=group_mode)
-            self.prevPoint = pos
-            self.repaint()
-
-    def mouseReleaseEvent(self, ev):
-        if ev.button() == QtCore.Qt.RightButton:
-            menu = self.menus[len(self.selectedShapesCopy) > 0]
-            self.restoreCursor()
-            if not menu.exec_(self.mapToGlobal(ev.pos())) \
-                    and self.selectedShapesCopy:
-                # Cancel the move by deleting the shadow copy.
-                self.selectedShapesCopy = []
-                self.repaint()
-        elif ev.button() == QtCore.Qt.LeftButton and self.selectedShapes:
-            self.overrideCursor(CURSOR_GRAB)
-        if self.movingShape:
-            self.storeShapes()
-            self.shapeMoved.emit()
-
-    def endMove(self, copy):
-        assert self.selectedShapes and self.selectedShapesCopy
-        assert len(self.selectedShapesCopy) == len(self.selectedShapes)
-        # del shape.fill_color
-        # del shape.line_color
-        if copy:
-            for i, shape in enumerate(self.selectedShapesCopy):
-                self.shapes.append(shape)
-                self.selectedShapes[i].selected = False
-                self.selectedShapes[i] = shape
-        else:
-            for i, shape in enumerate(self.selectedShapesCopy):
-                self.selectedShapes[i].points = shape.points
-        self.selectedShapesCopy = []
-        self.repaint()
-        self.storeShapes()
-        return True
-
-    def hideBackroundShapes(self, value):
-        self.hideBackround = value
-        if self.selectedShapes:
-            # Only hide other shapes if there is a current selection.
-            # Otherwise the user will not be able to select a shape.
-            self.setHiding(True)
-            self.repaint()
-
-    def setHiding(self, enable=True):
-        self._hideBackround = self.hideBackround if enable else False
-
-    def canCloseShape(self):
-        return self.drawing() and self.current and len(self.current) > 2
-
-    def mouseDoubleClickEvent(self, ev):
-        # We need at least 4 points here, since the mousePress handler
-        # adds an extra one before this handler is called.
-        if self.canCloseShape() and len(self.current) > 3:
-            self.current.popPoint()
-            self.finalise()
-
-    def selectShapes(self, shapes):
-        self.setHiding()
-        self.selectionChanged.emit(shapes)
-        self.update()
-
-    def selectShapePoint(self, point, multiple_selection_mode):
-        """Select the first shape created which contains this point."""
-        if self.selectedVertex():  # A vertex is marked for selection.
-            index, shape = self.hVertex, self.hShape
-            shape.highlightVertex(index, shape.MOVE_VERTEX)
-        else:
-            for shape in reversed(self.shapes):
-                if self.isVisible(shape) and shape.containsPoint(point):
-                    self.calculateOffsets(shape, point)
-                    self.setHiding()
-                    if multiple_selection_mode:
-                        if shape not in self.selectedShapes:
-                            self.selectionChanged.emit(
-                                self.selectedShapes + [shape])
-                    else:
-                        self.selectionChanged.emit([shape])
-                    return
-        self.deSelectShape()
-
-    def calculateOffsets(self, shape, point):
-        rect = shape.boundingRect()
-        x1 = rect.x() - point.x()
-        y1 = rect.y() - point.y()
-        x2 = (rect.x() + rect.width() - 1) - point.x()
-        y2 = (rect.y() + rect.height() - 1) - point.y()
-        self.offsets = QtCore.QPoint(x1, y1), QtCore.QPoint(x2, y2)
-
-    def boundedMoveVertex(self, pos):
-        index, shape = self.hVertex, self.hShape
-        point = shape[index]
-        if self.outOfPixmap(pos):
-            pos = self.intersectionPoint(point, pos)
-        shape.moveVertexBy(index, pos - point)
-
-    def boundedMoveShapes(self, shapes, pos):
-        if self.outOfPixmap(pos):
-            return False  # No need to move
-        o1 = pos + self.offsets[0]
-        if self.outOfPixmap(o1):
-            pos -= QtCore.QPoint(min(0, o1.x()), min(0, o1.y()))
-        o2 = pos + self.offsets[1]
-        if self.outOfPixmap(o2):
-            pos += QtCore.QPoint(min(0, self.pixmap.width() - o2.x()),
-                                 min(0, self.pixmap.height() - o2.y()))
-        # XXX: The next line tracks the new position of the cursor
-        # relative to the shape, but also results in making it
-        # a bit "shaky" when nearing the border and allows it to
-        # go outside of the shape's area for some reason.
-        # self.calculateOffsets(self.selectedShapes, pos)
-        dp = pos - self.prevPoint
-        if dp:
-            for shape in shapes:
-                shape.moveBy(dp)
-            self.prevPoint = pos
-            return True
-        return False
-
-    def deSelectShape(self):
-        if self.selectedShapes:
-            self.setHiding(False)
-            self.selectionChanged.emit([])
-            self.update()
-
-    def deleteSelected(self):
-        deleted_shapes = []
-        if self.selectedShapes:
-            for shape in self.selectedShapes:
-                self.shapes.remove(shape)
-                deleted_shapes.append(shape)
-            self.storeShapes()
-            self.selectedShapes = []
-            self.update()
-        return deleted_shapes
-
-    def copySelectedShapes(self):
-        if self.selectedShapes:
-            self.selectedShapesCopy = [s.copy() for s in self.selectedShapes]
-            self.boundedShiftShapes(self.selectedShapesCopy)
-            self.endMove(copy=True)
-        return self.selectedShapes
-
-    def boundedShiftShapes(self, shapes):
-        # Try to move in one direction, and if it fails in another.
-        # Give up if both fail.
-        point = shapes[0][0]
-        offset = QtCore.QPoint(2.0, 2.0)
-        self.offsets = QtCore.QPoint(), QtCore.QPoint()
-        self.prevPoint = point
-        if not self.boundedMoveShapes(shapes, point - offset):
-            self.boundedMoveShapes(shapes, point + offset)
-
-    def paintEvent(self, event):
-        if not self.pixmap:
-            return super(Canvas, self).paintEvent(event)
-
-        p = self._painter
-        p.begin(self)
-        p.setRenderHint(QtGui.QPainter.Antialiasing)
-        p.setRenderHint(QtGui.QPainter.HighQualityAntialiasing)
-        p.setRenderHint(QtGui.QPainter.SmoothPixmapTransform)
-
-        p.scale(self.scale, self.scale)
-        p.translate(self.offsetToCenter())
-
-        p.drawPixmap(0, 0, self.pixmap)
-        Shape.scale = self.scale
-        for shape in self.shapes:
-            if (shape.selected or not self._hideBackround) and \
-                    self.isVisible(shape):
-                shape.fill = shape.selected or shape == self.hShape
-                shape.paint(p)
-        if self.current:
-            self.current.paint(p)
-            self.line.paint(p)
-        if self.selectedShapesCopy:
-            for s in self.selectedShapesCopy:
-                s.paint(p)
-
-        if (self.fillDrawing() and self.createMode == 'polygon' and
-                self.current is not None and len(self.current.points) >= 2):
-            drawing_shape = self.current.copy()
-            drawing_shape.addPoint(self.line[1])
-            drawing_shape.fill = True
-            drawing_shape.fill_color.setAlpha(64)
-            drawing_shape.paint(p)
-
-        p.end()
-
-    def transformPos(self, point):
-        """Convert from widget-logical coordinates to painter-logical ones."""
-        return point / self.scale - self.offsetToCenter()
-
-    def offsetToCenter(self):
-        s = self.scale
-        area = super(Canvas, self).size()
-        w, h = self.pixmap.width() * s, self.pixmap.height() * s
-        aw, ah = area.width(), area.height()
-        x = (aw - w) / (2 * s) if aw > w else 0
-        y = (ah - h) / (2 * s) if ah > h else 0
-        return QtCore.QPoint(x, y)
-
-    def outOfPixmap(self, p):
-        w, h = self.pixmap.width(), self.pixmap.height()
-        return not (0 <= p.x() <= w - 1 and 0 <= p.y() <= h - 1)
-
-    def finalise(self):
-        assert self.current
-        self.current.close()
-        self.shapes.append(self.current)
-        self.storeShapes()
-        self.current = None
-        self.setHiding(False)
-        self.newShape.emit()
-        self.update()
-
-    def closeEnough(self, p1, p2):
-        # d = distance(p1 - p2)
-        # m = (p1-p2).manhattanLength()
-        # print "d %.2f, m %d, %.2f" % (d, m, d - m)
-        # divide by scale to allow more precision when zoomed in
-        return labelme.utils.distance(p1 - p2) < (self.epsilon / self.scale)
-
-    def intersectionPoint(self, p1, p2):
-        # Cycle through each image edge in clockwise fashion,
-        # and find the one intersecting the current line segment.
-        # http://paulbourke.net/geometry/lineline2d/
-        size = self.pixmap.size()
-        points = [(0, 0),
-                  (size.width() - 1, 0),
-                  (size.width() - 1, size.height() - 1),
-                  (0, size.height() - 1)]
-        x1, y1 = p1.x(), p1.y()
-        x2, y2 = p2.x(), p2.y()
-        d, i, (x, y) = min(self.intersectingEdges((x1, y1), (x2, y2), points))
-        x3, y3 = points[i]
-        x4, y4 = points[(i + 1) % 4]
-        if (x, y) == (x1, y1):
-            # Handle cases where previous point is on one of the edges.
-            if x3 == x4:
-                return QtCore.QPoint(x3, min(max(0, y2), max(y3, y4)))
-            else:  # y3 == y4
-                return QtCore.QPoint(min(max(0, x2), max(x3, x4)), y3)
-        return QtCore.QPoint(x, y)
-
-    def intersectingEdges(self, point1, point2, points):
-        """Find intersecting edges.
-
-        For each edge formed by `points', yield the intersection
-        with the line segment `(x1,y1) - (x2,y2)`, if it exists.
-        Also return the distance of `(x2,y2)' to the middle of the
-        edge along with its index, so that the one closest can be chosen.
-        """
-        (x1, y1) = point1
-        (x2, y2) = point2
-        for i in range(4):
-            x3, y3 = points[i]
-            x4, y4 = points[(i + 1) % 4]
-            denom = (y4 - y3) * (x2 - x1) - (x4 - x3) * (y2 - y1)
-            nua = (x4 - x3) * (y1 - y3) - (y4 - y3) * (x1 - x3)
-            nub = (x2 - x1) * (y1 - y3) - (y2 - y1) * (x1 - x3)
-            if denom == 0:
-                # This covers two cases:
-                #   nua == nub == 0: Coincident
-                #   otherwise: Parallel
-                continue
-            ua, ub = nua / denom, nub / denom
-            if 0 <= ua <= 1 and 0 <= ub <= 1:
-                x = x1 + ua * (x2 - x1)
-                y = y1 + ua * (y2 - y1)
-                m = QtCore.QPoint((x3 + x4) / 2, (y3 + y4) / 2)
-                d = labelme.utils.distance(m - QtCore.QPoint(x2, y2))
-                yield d, i, (x, y)
-
-    # These two, along with a call to adjustSize are required for the
-    # scroll area.
-    def sizeHint(self):
-        return self.minimumSizeHint()
-
-    def minimumSizeHint(self):
-        if self.pixmap:
-            return self.scale * self.pixmap.size()
-        return super(Canvas, self).minimumSizeHint()
-
-    def wheelEvent(self, ev):
-        if QT5:
-            mods = ev.modifiers()
-            delta = ev.angleDelta()
-            if QtCore.Qt.ControlModifier == int(mods):
-                # with Ctrl/Command key
-                # zoom
-                self.zoomRequest.emit(delta.y(), ev.pos())
-            else:
-                # scroll
-                self.scrollRequest.emit(delta.x(), QtCore.Qt.Horizontal)
-                self.scrollRequest.emit(delta.y(), QtCore.Qt.Vertical)
-        else:
-            if ev.orientation() == QtCore.Qt.Vertical:
-                mods = ev.modifiers()
-                if QtCore.Qt.ControlModifier == int(mods):
-                    # with Ctrl/Command key
-                    self.zoomRequest.emit(ev.delta(), ev.pos())
-                else:
-                    self.scrollRequest.emit(
-                        ev.delta(),
-                        QtCore.Qt.Horizontal
-                        if (QtCore.Qt.ShiftModifier == int(mods))
-                        else QtCore.Qt.Vertical)
-            else:
-                self.scrollRequest.emit(ev.delta(), QtCore.Qt.Horizontal)
-        ev.accept()
-
-    def keyPressEvent(self, ev):
-        key = ev.key()
-        if key == QtCore.Qt.Key_Escape and self.current:
-            self.current = None
-            self.drawingPolygon.emit(False)
-            self.update()
-        elif key == QtCore.Qt.Key_Return and self.canCloseShape():
-            self.finalise()
-
-    def setLastLabel(self, text, flags):
-        assert text
-        self.shapes[-1].label = text
-        self.shapes[-1].flags = flags
-        self.shapesBackups.pop()
-        self.storeShapes()
-        return self.shapes[-1]
-
-    def undoLastLine(self):
-        assert self.shapes
-        self.current = self.shapes.pop()
-        self.current.setOpen()
-        if self.createMode in ['polygon', 'linestrip']:
-            self.line.points = [self.current[-1], self.current[0]]
-        elif self.createMode in ['rectangle', 'line', 'circle']:
-            self.current.points = self.current.points[0:1]
-        elif self.createMode == 'point':
-            self.current = None
-        self.drawingPolygon.emit(True)
-
-    def undoLastPoint(self):
-        if not self.current or self.current.isClosed():
-            return
-        self.current.popPoint()
-        if len(self.current) > 0:
-            self.line[0] = self.current[-1]
-        else:
-            self.current = None
-            self.drawingPolygon.emit(False)
-        self.repaint()
-
-    def loadPixmap(self, pixmap):
-        self.pixmap = pixmap
-        self.shapes = []
-        self.repaint()
-
-    def loadShapes(self, shapes, replace=True):
-        if replace:
-            self.shapes = list(shapes)
-        else:
-            self.shapes.extend(shapes)
-        self.storeShapes()
-        self.current = None
-        self.repaint()
-
-    def setShapeVisible(self, shape, value):
-        self.visible[shape] = value
-        self.repaint()
-
-    def overrideCursor(self, cursor):
-        self.restoreCursor()
-        self._cursor = cursor
-        QtWidgets.QApplication.setOverrideCursor(cursor)
-
-    def restoreCursor(self):
-        QtWidgets.QApplication.restoreOverrideCursor()
-
-    def resetState(self):
-        self.restoreCursor()
-        self.pixmap = None
-        self.shapesBackups = []
-        self.update()

DataAnnotation/labelme/labelme/widgets/color_dialog.py

-from qtpy import QtWidgets
-
-
-class ColorDialog(QtWidgets.QColorDialog):
-
-    def __init__(self, parent=None):
-        super(ColorDialog, self).__init__(parent)
-        self.setOption(QtWidgets.QColorDialog.ShowAlphaChannel)
-        # The Mac native dialog does not support our restore button.
-        self.setOption(QtWidgets.QColorDialog.DontUseNativeDialog)
-        # Add a restore defaults button.
-        # The default is set at invocation time, so that it
-        # works across dialogs for different elements.
-        self.default = None
-        self.bb = self.layout().itemAt(1).widget()
-        self.bb.addButton(QtWidgets.QDialogButtonBox.RestoreDefaults)
-        self.bb.clicked.connect(self.checkRestore)
-
-    def getColor(self, value=None, title=None, default=None):
-        self.default = default
-        if title:
-            self.setWindowTitle(title)
-        if value:
-            self.setCurrentColor(value)
-        return self.currentColor() if self.exec_() else None
-
-    def checkRestore(self, button):
-        if self.bb.buttonRole(button) & \
-                QtWidgets.QDialogButtonBox.ResetRole and self.default:
-            self.setCurrentColor(self.default)

DataAnnotation/labelme/labelme/widgets/escapable_qlist_widget.py

-from qtpy.QtCore import Qt
-from qtpy import QtWidgets
-
-
-class EscapableQListWidget(QtWidgets.QListWidget):
-
-    def keyPressEvent(self, event):
-        if event.key() == Qt.Key_Escape:
-            self.clearSelection()

DataAnnotation/labelme/labelme/widgets/label_dialog.py

-import re
-
-from qtpy import QT_VERSION
-from qtpy import QtCore
-from qtpy import QtGui
-from qtpy import QtWidgets
-
-QT5 = QT_VERSION[0] == '5'  # NOQA
-
-from labelme.logger import logger
-import labelme.utils
-
-
-# TODO(unknown):
-# - Calculate optimal position so as not to go out of screen area.
-
-
-class LabelQLineEdit(QtWidgets.QLineEdit):
-
-    def setListWidget(self, list_widget):
-        self.list_widget = list_widget
-
-    def keyPressEvent(self, e):
-        if e.key() in [QtCore.Qt.Key_Up, QtCore.Qt.Key_Down]:
-            self.list_widget.keyPressEvent(e)
-        else:
-            super(LabelQLineEdit, self).keyPressEvent(e)
-
-
-class LabelDialog(QtWidgets.QDialog):
-
-    def __init__(self, text="Enter object label", parent=None, labels=None,
-                 sort_labels=True, show_text_field=True,
-                 completion='startswith', fit_to_content=None, flags=None):
-        if fit_to_content is None:
-            fit_to_content = {'row': False, 'column': True}
-        self._fit_to_content = fit_to_content
-
-        super(LabelDialog, self).__init__(parent)
-        self.edit = LabelQLineEdit()
-        self.edit.setPlaceholderText(text)
-        self.edit.setValidator(labelme.utils.labelValidator())
-        self.edit.editingFinished.connect(self.postProcess)
-        if flags:
-            self.edit.textChanged.connect(self.updateFlags)
-        layout = QtWidgets.QVBoxLayout()
-        if show_text_field:
-            layout.addWidget(self.edit)
-        # buttons
-        self.buttonBox = bb = QtWidgets.QDialogButtonBox(
-            QtWidgets.QDialogButtonBox.Ok | QtWidgets.QDialogButtonBox.Cancel,
-            QtCore.Qt.Horizontal,
-            self,
-        )
-        bb.button(bb.Ok).setIcon(labelme.utils.newIcon('done'))
-        bb.button(bb.Cancel).setIcon(labelme.utils.newIcon('undo'))
-        bb.accepted.connect(self.validate)
-        bb.rejected.connect(self.reject)
-        layout.addWidget(bb)
-        # label_list
-        self.labelList = QtWidgets.QListWidget()
-        if self._fit_to_content['row']:
-            self.labelList.setHorizontalScrollBarPolicy(
-                QtCore.Qt.ScrollBarAlwaysOff
-            )
-        if self._fit_to_content['column']:
-            self.labelList.setVerticalScrollBarPolicy(
-                QtCore.Qt.ScrollBarAlwaysOff
-            )
-        self._sort_labels = sort_labels
-        if labels:
-            self.labelList.addItems(labels)
-        if self._sort_labels:
-            self.labelList.sortItems()
-        else:
-            self.labelList.setDragDropMode(
-                QtWidgets.QAbstractItemView.InternalMove)
-        self.labelList.currentItemChanged.connect(self.labelSelected)
-        self.edit.setListWidget(self.labelList)
-        layout.addWidget(self.labelList)
-        # label_flags
-        if flags is None:
-            flags = {}
-        self._flags = flags
-        self.flagsLayout = QtWidgets.QVBoxLayout()
-        self.resetFlags()
-        layout.addItem(self.flagsLayout)
-        self.edit.textChanged.connect(self.updateFlags)
-        self.setLayout(layout)
-        # completion
-        completer = QtWidgets.QCompleter()
-        if not QT5 and completion != 'startswith':
-            logger.warn(
-                "completion other than 'startswith' is only "
-                "supported with Qt5. Using 'startswith'"
-            )
-            completion = 'startswith'
-        if completion == 'startswith':
-            completer.setCompletionMode(QtWidgets.QCompleter.InlineCompletion)
-            # Default settings.
-            # completer.setFilterMode(QtCore.Qt.MatchStartsWith)
-        elif completion == 'contains':
-            completer.setCompletionMode(QtWidgets.QCompleter.PopupCompletion)
-            completer.setFilterMode(QtCore.Qt.MatchContains)
-        else:
-            raise ValueError('Unsupported completion: {}'.format(completion))
-        completer.setModel(self.labelList.model())
-        self.edit.setCompleter(completer)
-
-    def addLabelHistory(self, label):
-        if self.labelList.findItems(label, QtCore.Qt.MatchExactly):
-            return
-        self.labelList.addItem(label)
-        if self._sort_labels:
-            self.labelList.sortItems()
-
-    def labelSelected(self, item):
-        self.edit.setText(item.text())
-
-    def validate(self):
-        text = self.edit.text()
-        if hasattr(text, 'strip'):
-            text = text.strip()
-        else:
-            text = text.trimmed()
-        if text:
-            self.accept()
-
-    def postProcess(self):
-        text = self.edit.text()
-        if hasattr(text, 'strip'):
-            text = text.strip()
-        else:
-            text = text.trimmed()
-        self.edit.setText(text)
-
-    def updateFlags(self, label_new):
-        # keep state of shared flags
-        flags_old = self.getFlags()
-
-        flags_new = {}
-        for pattern, keys in self._flags.items():
-            if re.match(pattern, label_new):
-                for key in keys:
-                    flags_new[key] = flags_old.get(key, False)
-        self.setFlags(flags_new)
-
-    def deleteFlags(self):
-        for i in reversed(range(self.flagsLayout.count())):
-            item = self.flagsLayout.itemAt(i).widget()
-            self.flagsLayout.removeWidget(item)
-            item.setParent(None)
-
-    def resetFlags(self, label=''):
-        flags = {}
-        for pattern, keys in self._flags.items():
-            if re.match(pattern, label):
-                for key in keys:
-                    flags[key] = False
-        self.setFlags(flags)
-
-    def setFlags(self, flags):
-        self.deleteFlags()
-        for key in flags:
-            item = QtWidgets.QCheckBox(key, self)
-            item.setChecked(flags[key])
-            self.flagsLayout.addWidget(item)
-            item.show()
-
-    def getFlags(self):
-        flags = {}
-        for i in range(self.flagsLayout.count()):
-            item = self.flagsLayout.itemAt(i).widget()
-            flags[item.text()] = item.isChecked()
-        return flags
-
-    def popUp(self, text=None, move=True, flags=None):
-        if self._fit_to_content['row']:
-            self.labelList.setMinimumHeight(
-                self.labelList.sizeHintForRow(0) * self.labelList.count() + 2
-            )
-        if self._fit_to_content['column']:
-            self.labelList.setMinimumWidth(
-                self.labelList.sizeHintForColumn(0) + 2
-            )
-        # if text is None, the previous label in self.edit is kept
-        if text is None:
-            text = self.edit.text()
-        if flags:
-            self.setFlags(flags)
-        else:
-            self.resetFlags(text)
-        self.edit.setText(text)
-        self.edit.setSelection(0, len(text))
-        items = self.labelList.findItems(text, QtCore.Qt.MatchFixedString)
-        if items:
-            if len(items) != 1:
-                logger.warning("Label list has duplicate '{}'".format(text))
-            self.labelList.setCurrentItem(items[0])
-            row = self.labelList.row(items[0])
-            self.edit.completer().setCurrentRow(row)
-        self.edit.setFocus(QtCore.Qt.PopupFocusReason)
-        if move:
-            self.move(QtGui.QCursor.pos())
-        if self.exec_():
-            return self.edit.text(), self.getFlags()
-        else:
-            return None, None

DataAnnotation/labelme/labelme/widgets/label_qlist_widget.py

-from qtpy import QtWidgets
-
-
-class LabelQListWidget(QtWidgets.QListWidget):
-
-    def __init__(self, *args, **kwargs):
-        super(LabelQListWidget, self).__init__(*args, **kwargs)
-        self.canvas = None
-        self.itemsToShapes = []
-        self.setSelectionMode(QtWidgets.QAbstractItemView.ExtendedSelection)
-
-    def get_shape_from_item(self, item):
-        for index, (item_, shape) in enumerate(self.itemsToShapes):
-            if item_ is item:
-                return shape
-
-    def get_item_from_shape(self, shape):
-        for index, (item, shape_) in enumerate(self.itemsToShapes):
-            if shape_ is shape:
-                return item
-
-    def clear(self):
-        super(LabelQListWidget, self).clear()
-        self.itemsToShapes = []
-
-    def setParent(self, parent):
-        self.parent = parent
-
-    def dropEvent(self, event):
-        shapes = self.shapes
-        super(LabelQListWidget, self).dropEvent(event)
-        if self.shapes == shapes:
-            return
-        if self.canvas is None:
-            raise RuntimeError('self.canvas must be set beforehand.')
-        self.parent.setDirty()
-        self.canvas.loadShapes(self.shapes)
-
-    @property
-    def shapes(self):
-        shapes = []
-        for i in range(self.count()):
-            item = self.item(i)
-            shape = self.get_shape_from_item(item)
-            shapes.append(shape)
-        return shapes

DataAnnotation/labelme/labelme/widgets/tool_bar.py

-from qtpy import QtCore
-from qtpy import QtWidgets
-
-
-class ToolBar(QtWidgets.QToolBar):
-
-    def __init__(self, title):
-        super(ToolBar, self).__init__(title)
-        layout = self.layout()
-        m = (0, 0, 0, 0)
-        layout.setSpacing(0)
-        layout.setContentsMargins(*m)
-        self.setContentsMargins(*m)
-        self.setWindowFlags(self.windowFlags() | QtCore.Qt.FramelessWindowHint)
-
-    def addAction(self, action):
-        if isinstance(action, QtWidgets.QWidgetAction):
-            return super(ToolBar, self).addAction(action)
-        btn = ToolButton()
-        btn.setDefaultAction(action)
-        btn.setToolButtonStyle(self.toolButtonStyle())
-        self.addWidget(btn)
-
-
-class ToolButton(QtWidgets.QToolButton):
-
-    """ToolBar companion class which ensures all buttons have the same size."""
-
-    minSize = (60, 60)
-
-    def minimumSizeHint(self):
-        ms = super(ToolButton, self).minimumSizeHint()
-        w1, h1 = ms.width(), ms.height()
-        w2, h2 = self.minSize
-        self.minSize = max(w1, w2), max(h1, h2)
-        return QtCore.QSize(*self.minSize)

DataAnnotation/labelme/labelme/widgets/zoom_widget.py

-from qtpy import QtCore
-from qtpy import QtGui
-from qtpy import QtWidgets
-
-
-class ZoomWidget(QtWidgets.QSpinBox):
-
-    def __init__(self, value=100):
-        super(ZoomWidget, self).__init__()
-        self.setButtonSymbols(QtWidgets.QAbstractSpinBox.NoButtons)
-        self.setRange(10, 1000)
-        self.setSuffix(' %')
-        self.setValue(value)
-        self.setToolTip('Zoom Level')
-        self.setStatusTip(self.toolTip())
-        self.setAlignment(QtCore.Qt.AlignCenter)
-
-    def minimumSizeHint(self):
-        height = super(ZoomWidget, self).minimumSizeHint().height()
-        fm = QtGui.QFontMetrics(self.font())
-        width = fm.width(str(self.maximum()))
-        return QtCore.QSize(width, height)

DataAnnotation/labelme/setup.cfg

-[flake8]
-exclude = .anaconda3/*,.anaconda2/*,venv/*
-ignore = H304

DataAnnotation/labelme/setup.py

-from __future__ import print_function
-
-import distutils.spawn
-import os.path
-from setuptools import find_packages
-from setuptools import setup
-import shlex
-import subprocess
-import sys
-
-
-PY3 = sys.version_info[0] == 3
-PY2 = sys.version_info[0] == 2
-assert PY3 or PY2
-
-
-here = os.path.abspath(os.path.dirname(__file__))
-version_file = os.path.join(here, 'labelme', '_version.py')
-if PY3:
-    import importlib
-    version = importlib.machinery.SourceFileLoader(
-        '_version', version_file
-    ).load_module().__version__
-else:
-    assert PY2
-    import imp
-    version = imp.load_source('_version', version_file).__version__
-del here
-
-
-install_requires = [
-    'matplotlib',
-    'numpy',
-    'Pillow>=2.8.0',
-    'PyYAML',
-    'qtpy',
-    'termcolor',
-]
-
-# Find python binding for qt with priority:
-# PyQt5 -> PySide2 -> PyQt4,
-# and PyQt5 is automatically installed on Python3.
-QT_BINDING = None
-
-try:
-    import PyQt5  # NOQA
-    QT_BINDING = 'pyqt5'
-except ImportError:
-    pass
-
-if QT_BINDING is None:
-    try:
-        import PySide2  # NOQA
-        QT_BINDING = 'pyside2'
-    except ImportError:
-        pass
-
-if QT_BINDING is None:
-    try:
-        import PyQt4  # NOQA
-        QT_BINDING = 'pyqt4'
-    except ImportError:
-        if PY2:
-            print(
-                'Please install PyQt5, PySide2 or PyQt4 for Python2.\n'
-                'Note that PyQt5 can be installed via pip for Python3.',
-                file=sys.stderr,
-            )
-            sys.exit(1)
-        assert PY3
-        # PyQt5 can be installed via pip for Python3
-        install_requires.append('PyQt5')
-        QT_BINDING = 'pyqt5'
-del QT_BINDING
-
-
-if sys.argv[1] == 'release':
-    if not distutils.spawn.find_executable('twine'):
-        print(
-            'Please install twine:\n\n\tpip install twine\n',
-            file=sys.stderr,
-        )
-        sys.exit(1)
-
-    commands = [
-        'python tests/docs_tests/man_tests/test_labelme_1.py',
-        'git tag v{:s}'.format(version),
-        'git push origin master --tag',
-        'python setup.py sdist',
-        'twine upload dist/labelme-{:s}.tar.gz'.format(version),
-    ]
-    for cmd in commands:
-        subprocess.check_call(shlex.split(cmd))
-    sys.exit(0)
-
-
-def get_long_description():
-    with open('README.md') as f:
-        long_description = f.read()
-    try:
-        import github2pypi
-        return github2pypi.replace_url(
-            slug='wkentaro/labelme', content=long_description
-        )
-    except Exception:
-        return long_description
-
-
-setup(
-    name='labelme',
-    version=version,
-    packages=find_packages(),
-    description='Image Polygonal Annotation with Python',
-    long_description=get_long_description(),
-    long_description_content_type='text/markdown',
-    author='Kentaro Wada',
-    author_email='www.kentaro.wada@gmail.com',
-    url='https://github.com/wkentaro/labelme',
-    install_requires=install_requires,
-    license='GPLv3',
-    keywords='Image Annotation, Machine Learning',
-    classifiers=[
-        'Development Status :: 5 - Production/Stable',
-        'Intended Audience :: Developers',
-        'Natural Language :: English',
-        'Programming Language :: Python',
-        'Programming Language :: Python :: 2',
-        'Programming Language :: Python :: 3',
-        'Programming Language :: Python :: Implementation :: CPython',
-        'Programming Language :: Python :: Implementation :: PyPy',
-    ],
-    package_data={'labelme': ['icons/*', 'config/*.yaml']},
-    entry_points={
-        'console_scripts': [
-            'labelme=labelme.main:main',
-            'labelme_draw_json=labelme.cli.draw_json:main',
-            'labelme_draw_label_png=labelme.cli.draw_label_png:main',
-            'labelme_json_to_dataset=labelme.cli.json_to_dataset:main',
-            'labelme_on_docker=labelme.cli.on_docker:main',
-        ],
-    },
-    data_files=[('share/man/man1', ['docs/man/labelme.1'])],
-)

DataAnnotation/labelme/tests/docs_tests/man_tests/test_labelme_1.py

-#!/usr/bin/env python
-
-from __future__ import print_function
-
-import os.path as osp
-import re
-import shlex
-import subprocess
-import sys
-
-
-here = osp.dirname(osp.abspath(__file__))
-
-cmd = 'help2man labelme'
-man_expected = subprocess.check_output(shlex.split(cmd)).decode().splitlines()
-
-man_file = osp.realpath(osp.join(here, '../../../docs/man/labelme.1'))
-with open(man_file) as f:
-    man_actual = f.read().splitlines()
-
-patterns_exclude = [
-    r'^\.TH .*',
-    r'^config file.*',
-    r'^\.\\.*',
-]
-
-PASS = 1
-for line_expected, line_actual in zip(man_expected, man_actual):
-    for pattern in patterns_exclude:
-        if re.match(pattern, line_expected) or re.match(pattern, line_actual):
-            break
-    else:
-        if line_expected != line_actual:
-            print(repr('> {}'.format(line_expected)), file=sys.stderr)
-            print(repr('< {}'.format(line_actual)), file=sys.stderr)
-            PASS = 0
-
-if not PASS:
-    print(
-        'Please run:\n\n\thelp2man labelme > {}\n'.format(man_file),
-        file=sys.stderr,
-    )
-assert PASS

DataAnnotation/labelme/tests/labelme_tests/data/apc2016_obj3.jpg

-../../../examples/tutorial/apc2016_obj3.jpg
\ No newline at end of file

DataAnnotation/labelme/tests/labelme_tests/data/apc2016_obj3.json

-../../../examples/tutorial/apc2016_obj3.json
\ No newline at end of file

DataAnnotation/labelme/tests/labelme_tests/test_app.py

-import os.path as osp
-import shutil
-import tempfile
-
-import labelme.app
-import labelme.config
-import labelme.testing
-
-
-here = osp.dirname(osp.abspath(__file__))
-data_dir = osp.join(here, 'data')
-
-
-def test_MainWindow_open(qtbot):
-    win = labelme.app.MainWindow()
-    qtbot.addWidget(win)
-    win.show()
-    win.close()
-
-
-def test_MainWindow_open_json(qtbot):
-    filename = osp.join(data_dir, 'apc2016_obj3.json')
-    labelme.testing.assert_labelfile_sanity(filename)
-    win = labelme.app.MainWindow(filename=filename)
-    qtbot.addWidget(win)
-    win.show()
-    win.close()
-
-
-def test_MainWindow_annotate_jpg(qtbot):
-    tmp_dir = tempfile.mkdtemp()
-    filename = osp.join(tmp_dir, 'apc2016_obj3.jpg')
-    shutil.copy(osp.join(data_dir, 'apc2016_obj3.jpg'),
-                filename)
-    output_file = osp.join(tmp_dir, 'apc2016_obj3.json')
-
-    config = labelme.config.get_default_config()
-    win = labelme.app.MainWindow(
-        config=config,
-        filename=filename,
-        output_file=output_file,
-    )
-    qtbot.addWidget(win)
-    win.show()
-
-    def check_imageData():
-        assert hasattr(win, 'imageData')
-        assert win.imageData is not None
-
-    qtbot.waitUntil(check_imageData)  # wait for loadFile
-
-    label = 'shelf'
-    points = [
-        (26, 70),
-        (176, 730),
-        (986, 742),
-        (1184, 102),
-    ]
-    shape = label, points, None, None, 'polygon', {}
-    shapes = [shape]
-    win.loadLabels(shapes)
-    win.saveFile()
-
-    labelme.testing.assert_labelfile_sanity(output_file)

DataAnnotation/labelme/tests/labelme_tests/utils_tests/test_draw.py

-import numpy as np
-
-from labelme.utils import draw as draw_module
-from labelme.utils import shape as shape_module
-
-from .util import get_img_and_lbl
-
-
-# -----------------------------------------------------------------------------
-
-
-def test_label_colormap():
-    N = 255
-    colormap = draw_module.label_colormap(N=N)
-    assert colormap.shape == (N, 3)
-
-
-def test_label2rgb():
-    img, lbl, label_names = get_img_and_lbl()
-    n_labels = len(label_names)
-
-    viz = draw_module.label2rgb(lbl=lbl, n_labels=n_labels)
-    assert lbl.shape == viz.shape[:2]
-    assert viz.dtype == np.uint8
-
-    viz = draw_module.label2rgb(lbl=lbl, img=img, n_labels=n_labels)
-    assert img.shape[:2] == lbl.shape == viz.shape[:2]
-    assert viz.dtype == np.uint8
-
-
-def test_draw_label():
-    img, lbl, label_names = get_img_and_lbl()
-
-    viz = draw_module.draw_label(lbl, img, label_names=label_names)
-    assert viz.shape[:2] == img.shape[:2] == lbl.shape[:2]
-    assert viz.dtype == np.uint8
-
-
-def test_draw_instances():
-    img, lbl, label_names = get_img_and_lbl()
-    labels_and_masks = {l: lbl == l for l in np.unique(lbl) if l != 0}
-    labels, masks = zip(*labels_and_masks.items())
-    masks = np.asarray(masks)
-    bboxes = shape_module.masks_to_bboxes(masks)
-    captions = [label_names[l] for l in labels]
-    viz = draw_module.draw_instances(img, bboxes, labels, captions=captions)
-    assert viz.shape[:2] == img.shape[:2]
-    assert viz.dtype == np.uint8

DataAnnotation/labelme/tests/labelme_tests/utils_tests/test_image.py

-import os.path as osp
-
-import numpy as np
-import PIL.Image
-
-from labelme.utils import image as image_module
-
-from .util import data_dir
-from .util import get_img_and_data
-
-
-def test_img_b64_to_arr():
-    img, _ = get_img_and_data()
-    assert img.dtype == np.uint8
-    assert img.shape == (907, 1210, 3)
-
-
-def test_img_arr_to_b64():
-    img_file = osp.join(data_dir, 'apc2016_obj3.jpg')
-    img_arr = np.asarray(PIL.Image.open(img_file))
-    img_b64 = image_module.img_arr_to_b64(img_arr)
-    img_arr2 = image_module.img_b64_to_arr(img_b64)
-    np.testing.assert_allclose(img_arr, img_arr2)
-
-
-def test_img_data_to_png_data():
-    img_file = osp.join(data_dir, 'apc2016_obj3.jpg')
-    with open(img_file, 'rb') as f:
-        img_data = f.read()
-    png_data = image_module.img_data_to_png_data(img_data)
-    assert isinstance(png_data, bytes)

DataAnnotation/labelme/tests/labelme_tests/utils_tests/test_shape.py

-from .util import get_img_and_data
-
-from labelme.utils import shape as shape_module
-
-
-def test_shapes_to_label():
-    img, data = get_img_and_data()
-    label_name_to_value = {}
-    for shape in data['shapes']:
-        label_name = shape['label']
-        label_value = len(label_name_to_value)
-        label_name_to_value[label_name] = label_value
-    cls = shape_module.shapes_to_label(
-        img.shape, data['shapes'], label_name_to_value)
-    assert cls.shape == img.shape[:2]
-
-
-def test_shape_to_mask():
-    img, data = get_img_and_data()
-    for shape in data['shapes']:
-        points = shape['points']
-        mask = shape_module.shape_to_mask(img.shape[:2], points)
-        assert mask.shape == img.shape[:2]

DataAnnotation/labelme/tests/labelme_tests/utils_tests/util.py

-import json
-import os.path as osp
-
-from labelme.utils import image as image_module
-from labelme.utils import shape as shape_module
-
-
-here = osp.dirname(osp.abspath(__file__))
-data_dir = osp.join(here, '../data')
-
-
-def get_img_and_data():
-    json_file = osp.join(data_dir, 'apc2016_obj3.json')
-    data = json.load(open(json_file))
-    img_b64 = data['imageData']
-    img = image_module.img_b64_to_arr(img_b64)
-    return img, data
-
-
-def get_img_and_lbl():
-    img, data = get_img_and_data()
-
-    label_name_to_value = {'__background__': 0}
-    for shape in data['shapes']:
-        label_name = shape['label']
-        label_value = len(label_name_to_value)
-        label_name_to_value[label_name] = label_value
-
-    n_labels = max(label_name_to_value.values()) + 1
-    label_names = [None] * n_labels
-    for label_name, label_value in label_name_to_value.items():
-        label_names[label_value] = label_name
-
-    lbl = shape_module.shapes_to_label(
-        img.shape, data['shapes'], label_name_to_value
-    )
-    return img, lbl, label_names

DataAnnotation/labelme/tests/labelme_tests/widgets_tests/test_label_dialog.py

-from qtpy import QtCore
-from qtpy import QtWidgets
-
-from labelme.widgets import LabelDialog
-from labelme.widgets import LabelQLineEdit
-
-
-def test_LabelQLineEdit(qtbot):
-    list_widget = QtWidgets.QListWidget()
-    list_widget.addItems([
-        'cat',
-        'dog',
-        'person',
-    ])
-    widget = LabelQLineEdit()
-    widget.setListWidget(list_widget)
-    qtbot.addWidget(widget)
-
-    # key press to navigate in label list
-    item = widget.list_widget.findItems('cat', QtCore.Qt.MatchExactly)[0]
-    widget.list_widget.setCurrentItem(item)
-    assert widget.list_widget.currentItem().text() == 'cat'
-    qtbot.keyPress(widget, QtCore.Qt.Key_Down)
-    assert widget.list_widget.currentItem().text() == 'dog'
-
-    # key press to enter label
-    qtbot.keyPress(widget, QtCore.Qt.Key_P)
-    qtbot.keyPress(widget, QtCore.Qt.Key_E)
-    qtbot.keyPress(widget, QtCore.Qt.Key_R)
-    qtbot.keyPress(widget, QtCore.Qt.Key_S)
-    qtbot.keyPress(widget, QtCore.Qt.Key_O)
-    qtbot.keyPress(widget, QtCore.Qt.Key_N)
-    assert widget.text() == 'person'
-
-
-def test_LabelDialog_addLabelHistory(qtbot):
-    labels = ['cat', 'dog', 'person']
-    widget = LabelDialog(labels=labels, sort_labels=True)
-    qtbot.addWidget(widget)
-
-    widget.addLabelHistory('bicycle')
-    assert widget.labelList.count() == 4
-    widget.addLabelHistory('bicycle')
-    assert widget.labelList.count() == 4
-    item = widget.labelList.item(0)
-    assert item.text() == 'bicycle'
-
-
-def test_LabelDialog_popUp(qtbot):
-    labels = ['cat', 'dog', 'person']
-    widget = LabelDialog(labels=labels, sort_labels=True)
-    qtbot.addWidget(widget)
-
-    # popUp(text='cat')
-
-    def interact():
-        qtbot.keyClick(widget.edit, QtCore.Qt.Key_P)  # enter 'p' for 'person'  # NOQA
-        qtbot.keyClick(widget.edit, QtCore.Qt.Key_Enter)  # NOQA
-        qtbot.keyClick(widget.edit, QtCore.Qt.Key_Enter)  # NOQA
-
-    QtCore.QTimer.singleShot(500, interact)
-    label, flags = widget.popUp('cat')
-    assert label == 'person'
-    assert flags == {}
-
-    # popUp()
-
-    def interact():
-        qtbot.keyClick(widget.edit, QtCore.Qt.Key_Enter)  # NOQA
-        qtbot.keyClick(widget.edit, QtCore.Qt.Key_Enter)  # NOQA
-
-    QtCore.QTimer.singleShot(500, interact)
-    label, flags = widget.popUp()
-    assert label == 'person'
-    assert flags == {}
-
-    # popUp() + key_Up
-
-    def interact():
-        qtbot.keyClick(widget.edit, QtCore.Qt.Key_Up)  # 'person' -> 'dog'  # NOQA
-        qtbot.keyClick(widget.edit, QtCore.Qt.Key_Enter)  # NOQA
-        qtbot.keyClick(widget.edit, QtCore.Qt.Key_Enter)  # NOQA
-
-    QtCore.QTimer.singleShot(500, interact)
-    label, flags = widget.popUp()
-    assert label == 'dog'
-    assert flags == {}

README.md

@@ -10,7 +10,7 @@
 
 
 
-飞桨全流程开发客户端，集飞桨核心框架、模型库、工具及组件等深度学习开发全流程所需能力于一身，不仅为您提供一键安装的客户端，开源开放的技术内核更方便您根据实际生产需求进行直接调用或二次开发，是提升深度学习项目开发效率的最佳辅助工具。
+飞桨全流程开发客户端，集成飞桨核心框架、模型库、工具及组件等核心模块，打通深度学习开发全流程。不仅提供一键安装的客户端，开源开放的技术内核更方便您根据实际生产需求进行直接调用或二次开发，为开发者提供飞桨全流程开发的最佳实践。
 
 PaddleX由PaddleX Client可视化前端和PaddleX Core后端技术内核两个部分组成。