gocr | OCR implementation with Golang | Computer Vision library

 by   Th1nkK1D Go Version: Current License: No License

kandi X-RAY | gocr Summary

kandi X-RAY | gocr Summary

gocr is a Go library typically used in Artificial Intelligence, Computer Vision applications. gocr has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.

Created by Withee Poositasai. Simple Thai OCR Project, CPE489 Image Processing and Computer Vision, KMUTT.

            kandi-support Support

              gocr has a low active ecosystem.
              It has 50 star(s) with 15 fork(s). There are 4 watchers for this library.
              It had no major release in the last 6 months.
              There are 2 open issues and 1 have been closed. On average issues are closed in 746 days. There are 1 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of gocr is current.

            kandi-Quality Quality

              gocr has 0 bugs and 0 code smells.

            kandi-Security Security

              gocr has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              gocr code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              gocr 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.

            kandi-Reuse Reuse

              gocr releases are not available. You will need to build from source code and install.
              Installation instructions are not available. Examples and code snippets are available.

            Top functions reviewed by kandi - BETA

            kandi has reviewed gocr and discovered the below as its top functions. This is intended to give you an instant insight into gocr implemented functionality, and help decide if they suit your requirements.
            • Main entry point
            • SplitLine splits an array of rows into an array of line numbers
            • GetSegmentChar returns the SegmentChar of the image array
            • writeGlyp draws a string to the glyph .
            • Resize resizes the given dimensions to the given dimensions .
            • MedianFilter returns the median filter
            • GetImgArray returns an array of image dimensions
            • getThresholdValue returns the threshold value
            • GenTemplate generate glyphs
            • GetImgMat builds an image mat from an array of dimensions .
            Get all kandi verified functions for this library.

            gocr Key Features

            No Key Features are available at this moment for gocr.

            gocr Examples and Code Snippets

            No Code Snippets are available at this moment for gocr.

            Community Discussions


            Using google cloud for image classification, cropping and OCR
            Asked 2021-Feb-26 at 15:49

            Please allow me to ask a rather newbie question. So far, I have been using local tools like imagemagick or GOCR to perform the job, but that is rather old-fashioned, and I am urged to "move to google cloud AI".

            The setup

            I have a (training) data set of various documents (as JPG and PDF) of different kinds, and by certain features (like prevailing color, repetitive layout) I intend to classify them, e.g. as invoice type 1, invoice type 2, not an invoice. In a 2nd step, I would like to OCR certain predefined areas of each document and extract e.g. the address of the company sending the invoice and the date.

            The architecture I am envisioning
            1. In a modern platform as a service (pass), I have already set up an UI where I can upload new files. These are then locally stored in a directory with filenames (or in a MongoDB). Meta info like upload timestamp, user, original file name is stored in a DB.
            2. The newly uploaded file should should then be submitted to google cloud which should do the classification step, and deliver back the label to be saved in the database.
            3. The document pages should be auto-cropped, i.e. black or white margins are removed, most probably with google cloud as well. The parameters of the crop should be persisted in the DB.
            4. In case it is e.g. an invoice, OCR should be performed (again by google cloud) for certain regions of the documents, e.g. a bounding box of spanning from the mid of the page to the right margin in the upper 10% of the cropped page. The results of the OCR should be again persisted locally.
            The problem

            I seem to be missing the correct search term to figure out how to do it with google cloud. Is there an google-API (e.g. REST), I can use to upload and which gives me back the results of steps 2 to 4?



            Answered 2021-Feb-26 at 15:49

            I think that your best option here is to use Document AI (REST API and Libraries).

            Using Document AI, you can:

            • Convert images to text
            • Classify documents
            • Analyze and extract entities

            Additionally, for your use case, we have a new Document AI feature that is still in preview and has limited access which is the Invoice parser.

            Invoice parser is similar to Form parser but for invoices instead of forms. Check out the Invoice parser page and you will see what I mean by preview and limited access.

            AFIK, there isn't any GCP tool for image edition.

            Source https://stackoverflow.com/questions/66348794

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network


            No vulnerabilities reported

            Install gocr

            You can download it from GitHub.


            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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