unno | Video annotation platform | Data Labeling library

by futurewei-cloud Python Version: Current License: Apache-2.0

X-Ray Key Features Code Snippets Community Discussions(3)Vulnerabilities Install Support

kandi X-RAY | unno Summary

unno is a Python library typically used in Artificial Intelligence, Data Labeling applications. unno has no bugs, it has a Permissive License and it has low support. However unno has 1 vulnerabilities and it build file is not available. You can download it from GitHub.

The system is built upon individual modules, which are standalone services that can be containerized and deployed in different computing nodes. End-users only interact with the browser based UX Frontend. Communications across modules are achieved by RESTful APIs.

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Quality

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Support

unno has a low active ecosystem.

It has 3 star(s) with 0 fork(s). There are 6 watchers for this library.

It had no major release in the last 6 months.

unno has no issues reported. There are 15 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of unno is current.

Quality

unno has no bugs reported.

Security

unno has 1 vulnerability issues reported (1 critical, 0 high, 0 medium, 0 low).

License

unno is licensed under the Apache-2.0 License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

unno releases are not available. You will need to build from source code and install.

unno has no build file. You will be need to create the build yourself to build the component from source.

Installation instructions are available. Examples and code snippets are not available.

Top functions reviewed by kandi - BETA

kandi has reviewed unno and discovered the below as its top functions. This is intended to give you an instant insight into unno implemented functionality, and help decide if they suit your requirements.

Add or update annotations
Add an annotation
Validate input manager
Add related annotations to results
Create a new job
Add a new job
Fetch all jobs from a user
Call a user
Add a user
Start tracking a video
Start tracking the image
Delete a job from the database
Upload local object to bucket
Generates the UPDATE statement
Update user attributes
Save frames in a bucket
Start tracking the image
Create a new user
Run an SQL query and return a list of rows
Remove a bucket
Add a new server
Download all objects from a bucket
Get a list of jobs from the database
Create a tracking query
Add a video
Post a category
Create new entity

Get all kandi verified functions for this library.

unno Key Features

No Key Features are available at this moment for unno.

unno Examples and Code Snippets

No Code Snippets are available at this moment for unno.

Community Discussions

Trending Discussions on Data Labeling

How can I do this split process in Python?

Replacing a character with a space and dividing the string into two words in R

Azure ML FileDataset registers, but cannot be accessed for Data Labeling project

QUESTION

How can I do this split process in Python?

Asked 2021-Dec-30 at 14:06

I'm trying to make a data labeling in a table, and I need to do it in such a way that, in each row, the index is repeated, however, that in each column there is another Enum class.

What I've done so far is make this representation with the same enumerator class.

A solution using the column separately as a list would also be possible. But what would be the best way to resolve this?

...

ANSWER

Answered 2021-Dec-30 at 13:57

Instead of using Enum you can use a dict mapping. You can avoid loops if you flatten your dataframe:

Source https://stackoverflow.com/questions/70532286

QUESTION

Replacing a character with a space and dividing the string into two words in R

Asked 2020-Nov-18 at 07:32

I have a dataframe that contains a column that includes strings separeted with semi-colons and it is followed by a space. But unfortunately in some of the strings there is a semi-colon that is not followed by a space.

In this case, This is what i'd like to do: If there is a space after the semi-colon we do not need a change. However if there are letters before and after the semi-colon, we should change semi-colon with space

i have this:

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ANSWER

Answered 2020-Nov-16 at 07:24

Try something like:

Source https://stackoverflow.com/questions/64853962

QUESTION

Azure ML FileDataset registers, but cannot be accessed for Data Labeling project

Asked 2020-Oct-28 at 20:31

Objective: Generate a down-sampled FileDataset using random sampling from a larger FileDataset to be used in a Data Labeling project.

Details: I have a large FileDataset containing millions of images. Each filename contains details about the 'section' it was taken from. A section may contain thousands of images. I want to randomly select a specific number of sections and all the images associated with those sections. Then register the sample as a new dataset.

Please note that the code below is not a direct copy and paste as there are elements such as filepaths and variables that have been renamed for confidentiality reasons.

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ANSWER

Answered 2020-Oct-27 at 22:39

Is the data behind virtual network by any chance?

Source https://stackoverflow.com/questions/64546521

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install unno

To run the system, both backend and frontend modules should be started.
Follow database service instructions to set up base database, including Relationtional Database (MySQL) and Key-Value storage (MiniIO).
Start the data manager service following the instruction therein. This is the only service that frontend UX interacts with.
Start each of the AI Functionality modules: tracking module you can add your own AI capability as you need, following tracking module
Launch the job manager service to handle all AI prediction requests.
Build and publish the UX frontend with a web server with the detailed instructions
Open a web browser and hit your UX host. Enjoy data annotating!

Support

Video data import and managementBounding box annotation in videoCategory (class) annotation and entity (identification) annotation in videoModel-based automatic entity tracking within videoAnnotation result export

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