ipyannotations | Image annotations in python using jupyter notebooks | Data Labeling library

by janfreyberg Python Version: 0.5.1 License: MIT

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

kandi X-RAY | ipyannotations Summary

ipyannotations is a Python library typically used in Artificial Intelligence, Data Labeling, Jupyter applications. ipyannotations 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 'npm i ipyannotations' or download it from GitHub, npm.

Create rich adata annotations in jupyter notebooks. ipyannotations provides interactive UI elements, based on ipywidgets, to allow developers and scientists to label data right in the notebook. ipyannotations supports many common data labelling tasks, such as image and text classification and annotation. It also supports custom data presentation by leveraging the Jupyter ecosystem.

Support

Quality

Security

License

Reuse

Support

ipyannotations has a low active ecosystem.

It has 20 star(s) with 4 fork(s). There are 3 watchers for this library.

It had no major release in the last 12 months.

There are 4 open issues and 3 have been closed. On average issues are closed in 12 days. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of ipyannotations is 0.5.1

Quality

ipyannotations has no bugs reported.

Security

ipyannotations has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

ipyannotations is licensed under the MIT License. This license is Permissive.

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

Reuse

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

Deployable package is available in npm.

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

Decorator to restrict canvas coordinates to image coordinates
Convert canvas coordinates to image coordinates
List of annotation data
Rearrange all buttons
Update the value of the button
List of polygon data
The data of the mesh
Patch canvas
Compute the distance between two points
Load a file or URL
Load an image
Appends a function to undo
Display text
Clears the object s data
Submits buttons to buttons
Set the data
Display a numpy array
Return a function that can be used to display an image
Submits the button buttons
Setup builder
Handle keystrokes
Helper function to display image
Wrapper for image display function
Load an image from a URL
Load image from Pillow
Load image from ndarray

Get all kandi verified functions for this library.

ipyannotations Key Features

No Key Features are available at this moment for ipyannotations.

ipyannotations Examples and Code Snippets

No Code Snippets are available at this moment for ipyannotations.

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 ipyannotations

You can install using pip:.
Create a dev environment:. Install the python. This will also build the TS package.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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