tfrecord-viewer | TFRecord Viewer for browsing contents | Data Labeling library

by sulc Python Version: Current License: Non-SPDX

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

kandi X-RAY | tfrecord-viewer Summary

tfrecord-viewer is a Python library typically used in Artificial Intelligence, Data Labeling applications. tfrecord-viewer has no vulnerabilities and it has low support. However tfrecord-viewer has 2 bugs, it build file is not available and it has a Non-SPDX License. You can download it from GitHub.

"How about checking your data before going deeper?". Use TFRecord Viewer to browse contents of TFRecords with object detection/classification annotations. The viewer runs a Flask server to provide a web gallery with annotation overlays. I.e. you can run it on your server machine, but browse on your local machine. The web gallery displayed with Fotorama.io.

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Quality

Security

License

Reuse

Support

tfrecord-viewer has a low active ecosystem.

It has 179 star(s) with 44 fork(s). There are 2 watchers for this library.

It had no major release in the last 6 months.

There are 4 open issues and 11 have been closed. On average issues are closed in 69 days. There are 3 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of tfrecord-viewer is current.

Quality

tfrecord-viewer has 2 bugs (0 blocker, 0 critical, 2 major, 0 minor) and 3 code smells.

Security

tfrecord-viewer has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

tfrecord-viewer code analysis shows 0 unresolved vulnerabilities.

There are 3 security hotspots that need review.

License

tfrecord-viewer has a Non-SPDX License.

Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

Reuse

tfrecord-viewer releases are not available. You will need to build from source code and install.

tfrecord-viewer has no build file. You will be need to create the build yourself to build the component from source.

tfrecord-viewer saves you 74 person hours of effort in developing the same functionality from scratch.

It has 339 lines of code, 27 functions and 7 files.

It has medium code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

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

Preload images
Apply overlay to image
Gets the segment map for the image
Apply colormap
Parse a tf record
Decorator for functions that require authentication
Authenticate the user
Checks if username and password match
Prepare the class path

Get all kandi verified functions for this library.

tfrecord-viewer Key Features

No Key Features are available at this moment for tfrecord-viewer.

tfrecord-viewer Examples and Code Snippets

No Code Snippets are available at this moment for tfrecord-viewer.

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 tfrecord-viewer

You can download it from GitHub.
You can use tfrecord-viewer 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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