Universal Data Tool
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Universal Data Tool
Universal Data Tool Docs
Installation
Running On-Premise
Collaborative Labeling
Building and Labeling Datasets
Image Segmentation
Image Classification
Text Classification
Named Entity Recognition
Entity Relations / Part of Speech Tagging
Audio Transcription
Data Entry
Video Segmentation
Composite Interfaces
Landmark / Pose Annotation
Importing Data
Upload or Open Directories
Import File URLs
Import COCO Images
Import from Google Drive
Import from AWS S3 Bucket
Import from CSV or JSON
Import using AWS Cognito
Import Text Snippets
The Format .udt.json
What is the .udt.json format?
What is the .udt.csv format?
Machine Learning
Jupyter Notebook Integration
Import Datasets into Pandas
Fast.ai
Integrate with Any Web Page
Integrate with the Javascript Library
Getting Started with React
Train your Workforce
Getting Started with UDT Courses
Frequently Asked Questions
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GitBook
Installation
Usage on Web
Just go to
universaldatatool.com/app
!
Using on Desktop (Windows, Mac, Linux)
You can download the latest releases of the Universal Data Tool from the
Github Releases page
.
Our Windows Desktop application needs contributors! If you run into any issues, or better yet manage to resolve them,
send us a contribution!
​
Using with Python or Jupyter Notebook
If you use
Fast.ai
or
Tensorflow
,
Pytorch
, brat etc. look at the respective guides in the Machine Learning section of these docs.
1
import
universaldatatool
as
udt
2
​
3
ds
=
udt
.
Dataset
(
4
interface
=
"image_classification"
,
5
image_urls
=
[
"https://example.com/image1.png"
],
6
labels
=
[
"cat"
,
"dog"
]
7
)
8
​
9
ds
.
to_json
()
# Outputs .udt.json
10
​
11
udt
.
open
()
# Opens the Universal Data Tool in Jupyter Notebooks
Copied!
You can do much more! Check out the
Getting Started with Python
for more details!
Using with React or Embedded on Webpage
Check out the guide for
Getting Started with React
or
Integrate the Javascript Library
.
I recommend trying out the web tool before integrating. For many use cases, you can avoid the integration all together just by
using the online tool
!
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Running On-Premise
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1yr ago
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Contents
Usage on Web
Using on Desktop (Windows, Mac, Linux)
Using with Python or Jupyter Notebook
Using with React or Embedded on Webpage