labelbox-python | Labelbox Python Client | Data Labeling library

by Labelbox Python Version: v.3.47.1 License: Apache-2.0

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

kandi X-RAY | labelbox-python Summary

labelbox-python is a Python library typically used in Artificial Intelligence, Data Labeling applications. labelbox-python has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can install using 'pip install labelbox-python' or download it from GitHub, PyPI.

Labelbox is the enterprise-grade training data solution with fast AI enabled labeling tools, labeling automation, human workforce, data management, a powerful API for integration & SDK for extensibility. Visit Labelbox for more information. The Labelbox Python API offers a simple, user-friendly way to interact with the Labelbox back-end.

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Support

labelbox-python has a low active ecosystem.

It has 73 star(s) with 46 fork(s). There are 8 watchers for this library.

There were 5 major release(s) in the last 12 months.

There are 2 open issues and 54 have been closed. On average issues are closed in 18 days. There are 12 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of labelbox-python is v.3.47.1

Quality

labelbox-python has no bugs reported.

Security

labelbox-python has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

labelbox-python 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

labelbox-python releases are available to install and integrate.

Deployable package is available in PyPI.

Build file is available. You can build the component from source.

Installation instructions, examples and code snippets are available.

Top functions reviewed by kandi - BETA

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

Generate a set of images from the given labels
Process a label
Create a CocoImage from a label
Gets the annotation lookup for the given annotations
Creates a new data row and returns it
Get a single resource from database
Gets the current user
Execute the query
Create a new project
Builds a relationship query
Update a relationship
Upload a document to a notebook
Create a webhook
Create a mask from a data row
Adds labels to the given dataset
Creates a mutation request
Validates that all cached fields are referenced by this Entity
Build an NDBase object from data
Bulk deletes data row metadata
Create a bulk import request
Separate a coco annotation from a panoptic json file
Creates a new DataRow from a dictionary
Create a BulkImportRequest from a file
Predict for a given image
Generate a list of coco images from the given labels
Create a bulk import request from a local file

Get all kandi verified functions for this library.

labelbox-python Key Features

No Key Features are available at this moment for labelbox-python.

labelbox-python Examples and Code Snippets

Labelbox Python SDK,Authentication

Python

Lines of Code : 13

License : Permissive (Apache-2.0)

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user@machine:~$ export LABELBOX_API_KEY=""
user@machine:~$ python3

from labelbox import Client
client = Client()

# On prem
client = Client( endpoint = "")

# Local
client = Client(api_key=os.environ['LABELBOX_TEST_API_KEY_LOCAL'], endpoint="http://

Labelbox Python SDK,Testing

Python

Lines of Code : 7

License : Permissive (Apache-2.0)

Copy

user@machine:~$ export LABELBOX_TEST_API_KEY_LOCAL=""
make test-local  # with an optional flag: PATH_TO_TEST=tests/integration/...etc LABELBOX_TEST_API_KEY_LOCAL=specify_here_or_export_me

user@machine:~$ export LABELBOX_TEST_API_KEY_STAGING=""
make

Labelbox Python SDK,Installation

Python

Lines of Code : 6

License : Permissive (Apache-2.0)

Copy

curl https://bootstrap.pypa.io/get-pip.py -o get-pip.py
python3 get-pip.py

export PATH=/Users//Library/Python/3.8/bin:$PATH

pip3 install -e .

pip3 install -r requirements.txt

pip install labelbox[data]

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:

...

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.

...

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 labelbox-python

pip is a package manager for Python. On macOS, you can set it up to use the default python3 install via -. If the installation completes with a warning re: pip not being in your path, you'll need to add it by modifying your shell config (.zshrc, .bashrc or similar). You might have to modify the command below depending on the version of python3 on your machine. Install SDK locally, using Python's Pip manager.