3lc-ai/3lc-ultralytics
3LC Integration with Ultralytics YOLO
This project helps data scientists fine-tune their computer vision models for tasks like object detection, image classification, or segmentation. It takes image datasets and model predictions as input, letting you visualize performance, identify problem areas in your data, and retrain models with improved datasets. The end-users are data scientists working on vision-based machine learning applications.
Use this if you are a data scientist using Ultralytics YOLO models and want to iteratively improve model performance by systematically refining your datasets.
Not ideal if you are not working with computer vision models or are not interested in data-centric model improvement workflows.
Stars
9
Forks
—
Language
Python
License
Apache-2.0
Category
Last pushed
Mar 20, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/computer-vision/3lc-ai/3lc-ultralytics"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
Sharpiless/Yolov5-deepsort-inference
Yolov5 deepsort inference，使用YOLOv5+Deepsort实现车辆行人追踪和计数，代码封装成一个Detector类，更容易嵌入到自己的项目中
laugh12321/TensorRT-YOLO
🚀 Easier & Faster YOLO Deployment Toolkit for NVIDIA 🛠️
facebookresearch/Ego4d
Ego4d dataset repository. Download the dataset, visualize, extract features & example usage of...
ultralytics/yolo-flutter-app
Flutter plugin for Ultralytics YOLO
ultralytics/yolo-ios-app
Ultralytics YOLO iOS App source code for running YOLO in your own iOS apps 🌟