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</div>
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</div>
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<div align="center">
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<div align="center">
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- <a href="https://starter-guide.labelme.io"><b>Starter Guide</b></a>
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+ <a href="#starter-guide"><b>Starter Guide</b></a>
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| <a href="#installation"><b>Installation</b></a>
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| <a href="#installation"><b>Installation</b></a>
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| <a href="#usage"><b>Usage</b></a>
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| <a href="#usage"><b>Usage</b></a>
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| <a href="#examples"><b>Examples</b></a>
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| <a href="#examples"><b>Examples</b></a>
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- | <a href="https://twitter.com/labelmeai"><b>Twitter</b></a>
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+ | <a href="https://x.com/labelmeai"><b>X/Twitter</b></a>
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<!-- | <a href="https://github.com/wkentaro/labelme/discussions"><b>Community</b></a> -->
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<!-- | <a href="https://github.com/wkentaro/labelme/discussions"><b>Community</b></a> -->
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<!-- | <a href="https://www.youtube.com/playlist?list=PLI6LvFw0iflh3o33YYnVIfOpaO0hc5Dzw"><b>Youtube FAQ</b></a> -->
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<!-- | <a href="https://www.youtube.com/playlist?list=PLI6LvFw0iflh3o33YYnVIfOpaO0hc5Dzw"><b>Youtube FAQ</b></a> -->
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</div>
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</div>
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@@ -30,7 +30,7 @@
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## Description
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## Description
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-Labelme is a graphical image annotation tool.
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+Labelme is a graphical image annotation tool inspired by <http://labelme.csail.mit.edu>.
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It is written in Python and uses Qt for its graphical interface.
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It is written in Python and uses Qt for its graphical interface.
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<img src="examples/instance_segmentation/data_dataset_voc/JPEGImages/2011_000006.jpg" width="19%" /> <img src="examples/instance_segmentation/data_dataset_voc/SegmentationClass/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/SegmentationObject/2011_000006.png" width="19%" /> <img src="examples/instance_segmentation/data_dataset_voc/SegmentationObjectVisualization/2011_000006.jpg" width="19%" />
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<img src="examples/instance_segmentation/data_dataset_voc/JPEGImages/2011_000006.jpg" width="19%" /> <img src="examples/instance_segmentation/data_dataset_voc/SegmentationClass/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/SegmentationObject/2011_000006.png" width="19%" /> <img src="examples/instance_segmentation/data_dataset_voc/SegmentationObjectVisualization/2011_000006.jpg" width="19%" />
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@@ -53,6 +53,15 @@ It is written in Python and uses Qt for its graphical interface.
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- [x] Exporting COCO-format dataset for instance segmentation. ([instance segmentation](examples/instance_segmentation))
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- [x] Exporting COCO-format dataset for instance segmentation. ([instance segmentation](examples/instance_segmentation))
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+## Starter Guide
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+
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+If you're new to Labelme, you can get started with [Labelme Starter Guide](https://labelme.gumroad.com/l/starter-guide) (FREE), which contains:
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+
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+- **Installation guides** for all platforms: Windows, macOS, and Linux 💻
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+- **Step-by-step tutorials**: first annotation to editing, exporting, and integrating with other programs 📕
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+- **A compilation of valuable resources** for further exploration 🔗.
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+
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+
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## Installation
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## Installation
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There are options:
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There are options:
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