open-images-annotation | Annotation project on top of the Open Images | Data Labeling library

by singnet Python Version: Current License: No License

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

kandi X-RAY | open-images-annotation Summary

open-images-annotation is a Python library typically used in Artificial Intelligence, Data Labeling, Deep Learning, Tensorflow applications. open-images-annotation has no bugs, it has no vulnerabilities, it has build file available and it has low support. You can download it from GitHub.

Google's Open Images dataset is wonderful resource for machine learning. It is not artificially hampered by licenses that assert non-commercial use.

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Quality

Security

License

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Support

open-images-annotation has a low active ecosystem.

It has 6 star(s) with 1 fork(s). There are 3 watchers for this library.

It had no major release in the last 6 months.

There are 6 open issues and 0 have been closed. On average issues are closed in 724 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of open-images-annotation is current.

Quality

open-images-annotation has no bugs reported.

Security

open-images-annotation has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

open-images-annotation does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

open-images-annotation releases are not available. You will need to build from source code and install.

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

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

Top functions reviewed by kandi - BETA

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

Convert a file to XML
Helper function for debugging
Convert coordinates to absolute
Return the path to the image
Write box and landmarks
Bulk annotation
Normalise image
Flush the annotation set
Binary search
Summarize a class label
Get the path to metadata file
Check all OpenImage annotation files exist
Go to the previous image
Changes the annotation set
Go to next image
Update the selected point
Resizes the image
Show an annotation
Return filename for training images
Return the path to metadata file
Visualize the results
Get an annotation for an image
Annotate an image with the given image
Get the boxes for an image id
Get the annotation for an image
Show random image
Download the given url and extract it
Load the class hierarchy

Get all kandi verified functions for this library.

open-images-annotation Key Features

No Key Features are available at this moment for open-images-annotation.

open-images-annotation Examples and Code Snippets

No Code Snippets are available at this moment for open-images-annotation.

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.

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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 open-images-annotation

You can download it from GitHub.
You can use open-images-annotation like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

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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