streamlit-label-studio-frontend | Streamlit component integrating Label Studio Frontend | Data Labeling library

 by   asehmi Python Version: Current License: MIT

kandi X-RAY | streamlit-label-studio-frontend Summary

kandi X-RAY | streamlit-label-studio-frontend Summary

streamlit-label-studio-frontend is a Python library typically used in Artificial Intelligence, Data Labeling applications. streamlit-label-studio-frontend has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

Label Studio is an open source data labeling tool providing flexible data annotation. Label Studio comprises Label Studio Backend (LSB) server and ML service and Label Studio Frontend (LSF) which is based on React and mobx-state-tree and distributed as an NPM package. LSF can be integrated in third-party applications without using LSB to provide data annotation support to users. LSF can be customized and extended to build custom UIs or used with pre-built labeling templates. This Streamlit application leverages Streamlit Components extensibilty with the simple architecture of Component Zero discussed in my article, Introduction to Streamlit and Streamlit Components. Using Component Zero as a template it was straight-forward to take the code snippet in Label Studio's Frontend integration guide and build the Streamlit component.
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              streamlit-label-studio-frontend has a low active ecosystem.
              It has 43 star(s) with 11 fork(s). There are 2 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              There are 1 open issues and 2 have been closed. On average issues are closed in 9 days. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of streamlit-label-studio-frontend is current.

            kandi-Quality Quality

              streamlit-label-studio-frontend has no bugs reported.

            kandi-Security Security

              streamlit-label-studio-frontend has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

            kandi-License License

              streamlit-label-studio-frontend is licensed under the MIT License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              streamlit-label-studio-frontend 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.

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            streamlit-label-studio-frontend Key Features

            No Key Features are available at this moment for streamlit-label-studio-frontend.

            streamlit-label-studio-frontend Examples and Code Snippets

            No Code Snippets are available at this moment for streamlit-label-studio-frontend.

            Community Discussions

            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

            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 streamlit-label-studio-frontend

            You can download it from GitHub.
            You can use streamlit-label-studio-frontend 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.

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            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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