3LC YOLO Integration
Ultralytics YOLO classification, object detection, instance segmentation, pose estimation and OBB with 3LC integrated.
About 3LC
3LC is a tool which enables data scientists to improve machine learning models in a data-centric fashion. It collects per-sample predictions and metrics, allows viewing and modifying the dataset in the context of those predictions in the 3LC Dashboard, and rerunning training with the revised dataset.
3LC is free for non-commercial use.
Quick Start
Installation
Install the package and requirements into a virtual environment (Python 3.10–3.14):
pip install 3lc-ultralytics
If you use uv, the equivalent commands are uv pip install 3lc-ultralytics, or uv add 3lc-ultralytics to add it to a uv project.
Dataset and Training
The integration is documented on the project GitHub Page, and details how to register datasets, run training and collect metrics.
Metadata
Release files for 3lc-ultralytics 0.5.3
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| 3lc_ultralytics-0.5.3.tar.gz | 1.5 MB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| 3lc_ultralytics-0.5.3-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 3.0 MB
Release files / 3lc_ultralytics-0.5.3.tar.gz
| Download URL | 3lc_ultralytics-0.5.3.tar.gz |
|---|---|
| Size | 1.5 MB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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Release files / 3lc_ultralytics-0.5.3-py3-none-any.whl
| Download URL | 3lc_ultralytics-0.5.3-py3-none-any.whl |
|---|---|
| Size | 1.5 MB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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Yes |
| Uploaded via |
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Security for 3lc-ultralytics 0.5.3
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