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LabelImg download for Windows

Free download LabelImg Windows app to run online win Wine in Ubuntu online, Fedora online or Debian online

This is the Windows app named LabelImg whose latest release can be downloaded as Binaryv1.8.1.zip. It can be run online in the free hosting provider OnWorks for workstations.

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- 6. Download the application and install it.

- 7. Download Wine from your Linux distributions software repositories. Once installed, you can then double-click the app to run them with Wine. You can also try PlayOnLinux, a fancy interface over Wine that will help you install popular Windows programs and games.

Wine is a way to run Windows software on Linux, but with no Windows required. Wine is an open-source Windows compatibility layer that can run Windows programs directly on any Linux desktop. Essentially, Wine is trying to re-implement enough of Windows from scratch so that it can run all those Windows applications without actually needing Windows.

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LabelImg


DESCRIPTION

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. Besides, it also supports YOLO and CreateML formats. Linux/Ubuntu/Mac requires at least Python 2.6 and has been tested with PyQt 4.8. However, Python 3 or above and PyQt5 are strongly recommended. Virtualenv can avoid a lot of the QT / Python version issues. Build and launch using the instructions. Click 'Change default saved annotation folder' in Menu/File. Click 'Open Dir'. Click 'Create RectBox'. Click and release left mouse to select a region to annotate the rect box. You can use right mouse to drag the rect box to copy or move it. The annotation will be saved to the folder you specify. You can refer to the hotkeys to speed up your workflow.



Features

  • 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 can edit the data/predefined_classes.txt to load pre-defined classes
  • When pressing space, the user can flag the image as verified, a green background will appear
  • The difficult field is set to 1 indicates that the object has been annotated as "difficult"
  • According to your deep neural network implementation, you can include or exclude difficult objects during training


Programming Language

Python


Categories

Image Recognition

This is an application that can also be fetched from https://sourceforge.net/projects/labelimg.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.


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