Update README.md and setup.py

HISTORY.rst

@@ -1,7 +1,12 @@
-=======
 History
 =======
 
+1.8.2 (2018-12-02)
+------------------
+
+* Fix pip depolyment issue
+
+
 1.8.1 (2018-12-02)
 ------------------
 

Makefile

@@ -1,6 +1,6 @@
 # ex: set ts=8 noet:
 
-all: qt5
+all: qt5 test
 
 test: testpy3
 
@@ -24,6 +24,12 @@ qt5py3:
 	pyrcc5 -o libs/resources.py resources.qrc
 
 clean:
-	rm -f ~/.labelImgSettings.pkl resources.pyc
+	rm -rf ~/.labelImgSettings.pkl *.pyc dist labelImg.egg-info __pycache__ build
 
-.PHONY: test
+pip_upload:
+	python3 setup.py upload
+
+long_description:
+	restview --long-description
+
+.PHONY: all

README.rst

@@ -16,7 +16,7 @@ LabelImg is a graphical image annotation tool.
 It is written in Python and uses Qt for its graphical interface.
 
 Annotations are saved as XML files in PASCAL VOC format, the format used
-by `ImageNet <http://www.image-net.org/>`__.  Besdies, it also supports YOLO format
+by `ImageNet <http://www.image-net.org/>`__.  Besides, it also supports YOLO format
 
 .. image:: https://raw.githubusercontent.com/tzutalin/labelImg/master/demo/demo3.jpg
      :alt: Demo Image
@@ -29,19 +29,14 @@ by `ImageNet <http://www.image-net.org/>`__.  Besdies, it also supports YOLO for
 Installation
 ------------------
 
-Download prebuilt binaries
-~~~~~~~~~~~~~~~~~~~~~~~~~~
-
--  `Windows <https://github.com/tzutalin/labelImg/releases>`__
-
--  macOS. Binaries for macOS are not yet available. Help would be appreciated. At present, it must be `built from source <#macos>`__.
 
 Build from source
 ~~~~~~~~~~~~~~~~~
 
 Linux/Ubuntu/Mac requires at least `Python
 2.6 <https://www.python.org/getit/>`__ and has been tested with `PyQt
-4.8 <https://www.riverbankcomputing.com/software/pyqt/intro>`__.
+4.8 <https://www.riverbankcomputing.com/software/pyqt/intro>`__. However, `Python
+3 or above <https://www.python.org/getit/>`__ and  `PyQt5 <https://pypi.org/project/PyQt5/>`__ are strongly recommended.
 
 
 Ubuntu Linux
@@ -56,7 +51,7 @@ Python 2 + Qt4
     python labelImg.py
     python labelImg.py [IMAGE_PATH] [PRE-DEFINED CLASS FILE]
 
-Python 3 + Qt5 (Recommanded)
+Python 3 + Qt5 (Recommended)
 
 .. code:: shell
 
@@ -78,14 +73,14 @@ Python 2 + Qt4
     python labelImg.py
     python labelImg.py [IMAGE_PATH] [PRE-DEFINED CLASS FILE]
 
-Python 3 + Qt5 (Recommanded)
+Python 3 + Qt5 (Recommended)
 
 .. code:: shell
 
     brew install qt  # Install qt-5.x.x by Homebrew
     brew install libxml2
 
-    or
+    or using pip
 
     pip3 install pyqt5 lxml # Install qt and lxml by pip
 
@@ -94,23 +89,21 @@ Python 3 + Qt5 (Recommanded)
     python3 labelImg.py [IMAGE_PATH] [PRE-DEFINED CLASS FILE]
 
 
-**NEW** Python 3 Virtualenv + Binary
+Python 3 Virtualenv (Recommended)
 
-This can avoid a lot of the QT / Python version issues, and gives you a nice .app file with a new SVG Icon
+Virtualenv can avoid a lot of the QT / Python version issues
-in your /Applications folder. You can consider this script: build-tools/build-for-macos.sh
 
 .. code:: shell
 
     brew install python3
-    pip install pipenv
+    pip3 install pipenv
-    pipenv --three
+    pipenv --three # or pipenv install pyqt5 lxml
-    pipenv shell
+    pipenv run pip install pyqt5 lxml
-    pip install py2app
+    pipenv run make qt5py3
-    pip install PyQt5 lxml
+    python3 labelImg.py
-    make qt5py3
+    [Optional] rm -rf build dist; python setup.py py2app -A;mv "dist/labelImg.app" /Applications
-    rm -rf build dist
+
-    python setup.py py2app -A
+Note: The Last command gives you a nice .app file with a new SVG Icon in your /Applications folder. You can consider using the script: build-tools/build-for-macos.sh
-    mv "dist/labelImg.app" /Applications
 
 
 Windows
@@ -142,15 +135,14 @@ Open the Anaconda Prompt and go to the `labelImg <#labelimg>`__ directory
     python labelImg.py
     python labelImg.py [IMAGE_PATH] [PRE-DEFINED CLASS FILE]
 
-Get from PyPI
+Get from PyPI but only python3.0 or above
-~~~~~~~~~~~~~~~~~
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 .. code:: shell
 
-    pip install labelImg
+    pip3 install labelImg
     labelImg
     labelImg [IMAGE_PATH] [PRE-DEFINED CLASS FILE]
 
-I tested pip on Ubuntu 14.04 and 16.04. However, I didn't test pip on macOS and Windows
 
 Use Docker
 ~~~~~~~~~~~~~~~~~
@@ -198,15 +190,15 @@ Steps (YOLO)
 
 2. Build and launch using the instructions above.
 
-3. Right below "Save" button in toolbar, click "PascalVOC" button to switch to YOLO format.
+3. Right below "Save" button in the toolbar, click "PascalVOC" button to switch to YOLO format.
 
-4. You may use Open/OpenDIR to process single or multiple images. When finished with single image, click save.
+4. You may use Open/OpenDIR to process single or multiple images. When finished with a single image, click save.
 
-A txt file of yolo format will be saved in the same folder as your image with same name. A file named "classes.txt" is saved to that folder too. "classes.txt" defines the list of class names that your yolo label refers to.
+A txt file of YOLO format will be saved in the same folder as your image with same name. A file named "classes.txt" is saved to that folder too. "classes.txt" defines the list of class names that your YOLO label refers to.
 
 Note:
 
-- Your label list shall not change in the middle of processing a list of images. When you save a image, classes.txt will also get updated, while previous annotations will not be updated.
+- Your label list shall not change in the middle of processing a list of images. When you save an image, classes.txt will also get updated, while previous annotations will not be updated.
 
 - You shouldn't use "default class" function when saving to YOLO format, it will not be referred.
 
@@ -255,7 +247,7 @@ This is used when creating a dataset automatically, the user can then through al
 
 **Difficult:**
 
-The difficult field being set to 1 indicates that the object has been annotated as "difficult", for example an object which is clearly visible but difficult to recognize without substantial use of context.
+The difficult field is set to 1 indicates that the object has been annotated as "difficult", for example, an object which is clearly visible but difficult to recognize without substantial use of context.
 According to your deep neural network implementation, you can include or exclude difficult objects during training.
 
 How to contribute
@@ -276,6 +268,7 @@ Related
    download image, create a label text for machine learning, etc
 2. `Use Docker to run labelImg <https://hub.docker.com/r/tzutalin/py2qt4>`__
 3. `Generating the PASCAL VOC TFRecord files <https://github.com/tensorflow/models/blob/4f32535fe7040bb1e429ad0e3c948a492a89482d/research/object_detection/g3doc/preparing_inputs.md#generating-the-pascal-voc-tfrecord-files>`__
-4. `App Icon based on Icon by Nick Roach (GPL)` <https://www.elegantthemes.com/> <https://www.iconfinder.com/icons/1054978/shop_tag_icon> __
+4. `App Icon based on Icon by Nick Roach (GPL) <https://www.elegantthemes.com/>`__
+5. `Setup python development in vscode <https://tzutalin.blogspot.com/2019/04/set-up-visual-studio-code-for-python-in.html>`__
 
 

libs/__init__.py

@@ -1,2 +1,2 @@
-__version_info__ = ('1', '8', '1')
+__version_info__ = ('1', '8', '2')
 __version__ = '.'.join(__version_info__)

setup.py

@@ -9,6 +9,8 @@ import os
 
 here = os.path.abspath(os.path.dirname(__file__))
 NAME = 'labelImg'
+REQUIRES_PYTHON = '>=3.0.0'
+REQUIRED_DEP = ['pyqt5', 'lxml']
 about = {}
 
 with open(os.path.join(here, 'libs', '__init__.py')) as f:
@@ -21,14 +23,6 @@ with open('HISTORY.rst') as history_file:
     history = history_file.read()
 
 
-REQUIRED = []
-
-if (sys.version_info > (3, 0)):
-    REQUIRED = ['pyqt5', 'lxml']
-else:
-    print('\033[93m For py2, you are unable to installl pyqt4 by pip \033[0m')
-    REQUIRED = ['lxml']
-
 # OS specific settings
 SET_REQUIRES = []
 if _platform == "linux" or _platform == "linux2":
@@ -47,6 +41,47 @@ OPTIONS = {
     'iconfile': 'resources/icons/app.icns'
 }
 
+class UploadCommand(Command):
+    """Support setup.py upload."""
+
+    description=readme + '\n\n' + history,
+
+    user_options = []
+
+    @staticmethod
+    def status(s):
+        """Prints things in bold."""
+        print('\033[1m{0}\033[0m'.format(s))
+
+    def initialize_options(self):
+        pass
+
+    def finalize_options(self):
+        pass
+
+    def run(self):
+        try:
+            self.status('Removing previous builds…')
+            rmtree(os.path.join(here, 'dist'))
+        except OSError:
+            self.status('Fail to remove previous builds..')
+            pass
+
+        self.status('Building Source and Wheel (universal) distribution…')
+        os.system(
+            '{0} setup.py sdist bdist_wheel --universal'.format(sys.executable))
+
+        self.status('Uploading the package to PyPI via Twine…')
+        os.system('twine upload dist/*')
+
+        self.status('Pushing git tags…')
+        os.system('git tag -d v{0}'.format(about['__version__']))
+        os.system('git tag v{0}'.format(about['__version__']))
+        # os.system('git push --tags')
+
+        sys.exit()
+
+
 setup(
     app=APP,
     name=NAME,
@@ -56,6 +91,7 @@ setup(
     author="TzuTa Lin",
     author_email='tzu.ta.lin@gmail.com',
     url='https://github.com/tzutalin/labelImg',
+    python_requires=REQUIRES_PYTHON,
     package_dir={'labelImg': '.'},
     packages=required_packages,
     entry_points={
@@ -64,7 +100,7 @@ setup(
         ]
     },
     include_package_data=True,
-    install_requires=REQUIRED,
+    install_requires=REQUIRED_DEP,
     license="MIT license",
     zip_safe=False,
     keywords='labelImg labelTool development annotation deeplearning',
@@ -73,16 +109,18 @@ setup(
         'Intended Audience :: Developers',
         'License :: OSI Approved :: MIT License',
         'Natural Language :: English',
-        "Programming Language :: Python :: 2",
-        'Programming Language :: Python :: 2.6',
-        'Programming Language :: Python :: 2.7',
         'Programming Language :: Python :: 3',
         'Programming Language :: Python :: 3.3',
         'Programming Language :: Python :: 3.4',
         'Programming Language :: Python :: 3.5',
         'Programming Language :: Python :: 3.6',
+        'Programming Language :: Python :: 3.7',
     ],
     package_data={'data/predefined_classes.txt': ['data/predefined_classes.txt']},
     options={'py2app': OPTIONS},
-    setup_requires= SET_REQUIRES
+    setup_requires=SET_REQUIRES,
+    # $ setup.py publish support.
+    cmdclass={
+        'upload': UploadCommand,
+    }
 )