LabelMe setup and image annotation with Miniconda

This tutorial, uploaded May 13, 2025, demonstrates installing LabelMe on Windows and using it to prepare image annotations for segmentation. The recording date and LabelMe version are not supplied. The speaker selects a 64-bit Miniconda installer described as Python 3.12, while a later installer option refers to Python 3.13. These details describe the recorded setup rather than a current version recommendation.

The installation uses a separate Conda environment. LabelMe initially fails to launch with a missing Qt bindings error. The speaker then tries installing PyQt; after another error, an installation through conda-forge succeeds and LabelMe opens. The transcript does not reliably capture the full commands, so this is a walkthrough of the installation process rather than a command reference.

The annotation demonstration covers opening a large image, zooming and scrolling, drawing polygons, and moving their vertices. It also shows rectangle and circle annotations. The source description identifies the examples as satellite imagery and says annotations save in JSON format.

For a folder of images, the speaker uses Open Directory, moves between images, and enables automatic saving. The examples use rough outlines; the speaker advises greater precision when preparing annotations for deep learning.