GeoCOCO VS tree-labeller

Compare GeoCOCO vs tree-labeller and see what are their differences.

GeoCOCO

Tool for converting GIS annotations to Microsoft's Common Objects In Context (COCO) datasets (by jaspersiebring)

tree-labeller

Helps label training data using taxonomy information. (by dzieciou)
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GeoCOCO tree-labeller
1 1
4 3
- -
8.8 10.0
8 months ago about 1 year ago
Python Python
GNU General Public License v3.0 only BSD 3-clause "New" or "Revised" License
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GeoCOCO

Posts with mentions or reviews of GeoCOCO. We have used some of these posts to build our list of alternatives and similar projects.

tree-labeller

Posts with mentions or reviews of tree-labeller. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-01-05.
  • Sampling leaves from a tree
    2 projects | /r/AskStatistics | 5 Jan 2023
    I come from a similar application area, where I try to tag (annotation/label) a taxonomy of products iteratively. You are trying something slightly different, AFAIU, labeling a flat set of songs, each song with a set of tags from ontology (directed graph)From an application point of view, this is what taxonomists often do, when migrating products from one catalog to another: mapping one taxonomy to another. There was quite active research on matching ontologies. So, there are tools in both industry and research that help in that process, although I have never researched whether they do it iteratively and using sampling. Another related area is labeling data to train machine learning models (in your case it sounds a bit like multilabel classification, in my case, this is multiclass classification). This is often done iteratively, and tools like Explosion Prodigy samples for manual annotation only those items that the ML model is still not confident enough. This might be offtopic, but I looked at your library and your notation for defining relations between tags, reminded me of RDF and OWL languages for defining ontologies. They are quite well-defined and have tools for making inferences (reasoners).

What are some alternatives?

When comparing GeoCOCO and tree-labeller you can also consider the following projects:

datumaro - Dataset Management Framework, a Python library and a CLI tool to build, analyze and manage Computer Vision datasets.

qgis-earthengine-examples - A collection of 300+ Python examples for using Google Earth Engine in QGIS

WhiteboxTools-ArcGIS - ArcGIS Python Toolbox for WhiteboxTools

label-studio - Label Studio is a multi-type data labeling and annotation tool with standardized output format

sahi - Framework agnostic sliced/tiled inference + interactive ui + error analysis plots

labelme2coco - A lightweight package for converting your labelme annotations into COCO object detection format.

cvat - Annotate better with CVAT, the industry-leading data engine for machine learning. Used and trusted by teams at any scale, for data of any scale. [Moved to: https://github.com/opencv/cvat]

tpkutils - ArcGIS Tile Package Utilities