mailcorahul/auto_labeler
auto_labeler - An all-in-one library to automatically label vision data
This helps computer vision practitioners or researchers quickly generate high-quality labels for their image and video datasets. You provide your unlabeled images, and it outputs automatically labeled data for tasks like classification, object detection, or OCR. This is perfect for data scientists, machine learning engineers, or anyone working with large visual datasets who wants to avoid manual labeling.
No commits in the last 6 months.
Use this if you need to label a large computer vision dataset for tasks such as image classification, object detection, instance segmentation, or optical character recognition without the extensive time and cost of manual labeling.
Not ideal if you require 100% human-level accuracy for highly specialized or nuanced labeling tasks where subtle contextual understanding is critical.
Stars
19
Forks
1
Language
Python
License
—
Category
Last pushed
Jan 17, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/mailcorahul/auto_labeler"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
cvat-ai/cvat
Annotate better with CVAT, the industry-leading data engine for machine learning. Used and...
HumanSignal/label-studio
Label Studio is a multi-type data labeling and annotation tool with standardized output format
wkentaro/labelme
Image annotation with Python. Supports polygon, rectangle, circle, line, point, and AI-assisted...
CVHub520/X-AnyLabeling
Effortless data labeling with AI support from Segment Anything and other awesome models.
doccano/doccano
Open source annotation tool for machine learning practitioners.