Labelbee Client Save

Out-of-the-box Annotation Toolbox

Project README


  • 📦 Out of the Box, built-in six annotation tools, simple configurations
  • 🪵 Flexible combinations, multiple tools can directly rely on each other
  • 💻 Multiple operating systems: Mac / Linux / Windows
  • 🏁 Support Data Formats
General Data COCO Semantic Segmentation Mask
Export ✔️ ✔️ ✔️
Import ✔️


Mac & Windows & Linux

Support Scenes

  • Detection: Detection scenes for vehicles, license plates, pedestrians, faces, industrial parts, etc.
  • Classification: Detection of object classification, target characteristics, right and wrong judgments, and other classification scenarios
  • Semantic segmentation: Human body segmentation, panoramic segmentation, drivable area segmentation, vehicle segmentation, etc.
  • Text transcription: Text detection and recognition of license plates, invoices, insurance policies, signs, etc.
  • Contour detection: positioning line scenes such as human contour lines, lane lines, etc.
  • Key point detection: positioning scenes such as human face key points, vehicle key points, road edge key points, etc.

Detection / Segmentation

Line / Point / Text


Annotation Format

  "width": 4368,
  "height": 2912,
  "valid": true,
  "rotate": 0,
  "step_1": {
    "toolName": "rectTool",
    "result": [
        "x": 530.7826086956522,
        "y": 1149.217391304348,
        "width": 1314.7826086956522,
        "height": 1655.6521739130435,
        "attribute": "",
        "valid": true,
        "id": "Rp1x6bZs",
        "sourceID": "",
        "textAttribute": "",
        "order": 1

For details, click to view LabelBee Annotation Format


js can't export 8bit unsign Int image, so a python script is provided to solve this problem


This project is released under the Apache 2.0 license.

Open Source Agenda is not affiliated with "Labelbee Client" Project. README Source: open-mmlab/labelbee-client
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Last Commit
7 months ago

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