MMAAT | Multimodal Multisensor Activity Annotation Tool | Data Labeling library

 by   DFKI-Interactive-Machine-Learning Python Version: Current License: GPL-3.0

kandi X-RAY | MMAAT Summary

kandi X-RAY | MMAAT Summary

MMAAT is a Python library typically used in Artificial Intelligence, Data Labeling applications. MMAAT has no bugs, it has no vulnerabilities, it has build file available, it has a Strong Copyleft License and it has low support. You can download it from GitHub.

The Multimodal Multisensor Activity Annotation Tool (MMAAT) allows for intuitive labeling of the data providing multiple viewports for visualizing data. The resulting supervised data can be exported for machine learning purposes.
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              MMAAT has a low active ecosystem.
              It has 2 star(s) with 0 fork(s). There are 2 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              There are 0 open issues and 1 have been closed. On average issues are closed in 110 days. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of MMAAT is current.

            kandi-Quality Quality

              MMAAT has no bugs reported.

            kandi-Security Security

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

            kandi-License License

              MMAAT is licensed under the GPL-3.0 License. This license is Strong Copyleft.
              Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.

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              MMAAT 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, examples and code snippets are available.

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            MMAAT Key Features

            No Key Features are available at this moment for MMAAT.

            MMAAT Examples and Code Snippets

            No Code Snippets are available at this moment for MMAAT.

            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 MMAAT

            Install wheels from http://www.lfd.uci.edu/~gohlke/pythonlibs/.
            install Python 2.7 (32-bit)
            install numpy
            install h5py
            install matplotlib
            install OpenCV 2.4
            install PyQt4
            install scipy

            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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          • HTTPS

            https://github.com/DFKI-Interactive-Machine-Learning/MMAAT.git

          • CLI

            gh repo clone DFKI-Interactive-Machine-Learning/MMAAT

          • sshUrl

            git@github.com:DFKI-Interactive-Machine-Learning/MMAAT.git

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