3LC integration with Ultralytics YOLO
Project description
3LC YOLO Integration
Ultralytics YOLO classification, object detection and segmentation 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:
pip install 3lc-ultralytics
Dataset and Training
The integration is documented on the project GitHub Page, and details how to register datasets and run training.
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file 3lc_ultralytics-0.2.0.tar.gz.
File metadata
- Download URL: 3lc_ultralytics-0.2.0.tar.gz
- Upload date:
- Size: 1.5 MB
- Tags: Source
- Uploaded using Trusted Publishing? Yes
- Uploaded via: uv/0.7.19
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
85758f88c6f2648759e87db41b54c1ead8c0457ef7248d82276e90248b218526
|
|
| MD5 |
5faaf6807a127fff914648eb285b2ff1
|
|
| BLAKE2b-256 |
0d8c6ace366733e6489abe63c027e35f302fc5344a85c8e242074659546efa00
|
File details
Details for the file 3lc_ultralytics-0.2.0-py3-none-any.whl.
File metadata
- Download URL: 3lc_ultralytics-0.2.0-py3-none-any.whl
- Upload date:
- Size: 1.5 MB
- Tags: Python 3
- Uploaded using Trusted Publishing? Yes
- Uploaded via: uv/0.7.19
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
3e0f99022a7736e17dba60a3093b4aea521637259f38dc2f58672dd32797a29a
|
|
| MD5 |
927370b49e0420c1412e050d26782b74
|
|
| BLAKE2b-256 |
97a6a692975c6bac66e606101f35b5f3dad76a8f4bc83181dd1b13d694cd88bb
|
