ReceiptLabeler | Receipt labeler - Label receipt image | Data Labeling library

by urield94 Python Version: Current License: No License

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

kandi X-RAY | ReceiptLabeler Summary

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

Receipt labeler - Label receipt image into the following labels: Receipt, Logo, Shop detail, Parches summery , and Additional details, using trained TensorFlow object detection model.

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ReceiptLabeler has a low active ecosystem.

It has 4 star(s) with 1 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

ReceiptLabeler has no issues reported. There are 5 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of ReceiptLabeler is current.

Quality

ReceiptLabeler has no bugs reported.

Security

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

License

ReceiptLabeler 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

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

Returns the metrics for the estimator evaluation
Adds images
Create images from eval_dict
Load a label map
Loads the label map
Validates the label map
Pad tensor t
Set the dimension of t
Check whether t is a Tensor
Create a category index from a label map
Create categories from a label map
Flattens the first n dimensions
Flattens inputs
Draws bounding boxes on an image
Draws a bounding box on an image
Reshape the first dimension of inputs into a single dimension
Compute the combined shape of a tensor
Get the batch size of a tensor
Generates images from an evaluation dictionary
Label an image
Get the depth of a tensor
Get the width of a tensor
Return the height of a tensor
Handle label detection
Pad tensor
Clips tensor t into given length

Get all kandi verified functions for this library.

ReceiptLabeler Key Features

No Key Features are available at this moment for ReceiptLabeler.

ReceiptLabeler Examples and Code Snippets

No Code Snippets are available at this moment for ReceiptLabeler.

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?

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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:

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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 ReceiptLabeler

You can download it from GitHub.
You can use ReceiptLabeler 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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