Document Digitization

Documet Digitization

This pipeline is used to extract text from a digital/scanned document. Lines and layouts (header, footer, paragraph, table, cell, image) are detected by a custom-trained Prima layout model and OCR is done using the Anuvaad OCR model.

Github repo: Anuvaad Document Processor

API contract: API Contract

How to Use

1. Upload a PDF or image file using the upload API:

   Upload URL: https://auth.anuvaad.org/anuvaad-api/file-uploader/v0/upload-file

   Get the upload ID and copy it to the DD2.0 input path.

2. Initiate the Workflow:

   WF URL: https://auth.anuvaad.org/anuvaad-etl/wf-manager/v1/workflow/async/initiate

   DD2.0 Input:

   {
       "files": [
           {
               "locale": "language",
               "path": "file_name",
               "type": "file_format",
               "config": {
                   "OCR": {
                       "option": "HIGH_ACCURACY",
                       "language": "language"
                   }
               }
           }
       ],
       "workflowCode": "WF_A_FCWDLDBSOD20TESOTK"
   }

Microservices

Word Detector

• Input: PDF or image

• Output: List of pages with detected lines and page information.

sample

Github repo: Word Detector Craft

API contract: Word Detector API Contract

How to use: Word Detector

1. Upload a PDF or image file using the upload API:

   Upload URL: https://auth.anuvaad.org/anuvaad-api/file-uploader/v0/upload-file
2. Initiate the Word Detector Workflow:

   WF URL: https://auth.anuvaad.org/anuvaad-etl/wf-manager/v1/workflow/async/initiate

   Word Detector Input:

   {
       "files": [
           {
               "locale": "language",
               "path": "file_name",
               "type": "file_format",
               "config": {
                   "OCR": {
                       "option": "HIGH_ACCURACY",
                       "language": "language"
                   }
               }
           }
       ],
       "workflowCode": "WF_A_WD"
   }

Layout Detector

• Input: Output of word detector

• Output: List of pages with detected layouts and lines.

sample

Github repo: Layout Detector Prima

API contract: Layout Detector API Contract

How to use: Layout Detector

1. Input JSON file of the word detector as an input path.

2. Initiate the Layout Detector Workflow:

   WF URL: https://auth.anuvaad.org/anuvaad-etl/wf-manager/v1/workflow/async/initiate

   Layout Detector Input:

   {
       "files": [
           {
               "locale": "language",
               "path": "word_detector_output",
               "type": "json",
               "config": {
                   "OCR": {
                       "option": "HIGH_ACCURACY",
                       "language": "language"
                   }
               }
           }
       ],
       "workflowCode": "WF_A_LD"
   }

Block Segmenter

• Input: Output of layout detector

• Output: Collation of line and word at layout level.

Github repo: Block Segmenter

API contract: Block Segmenter API Contract

How to use: Block Segmenter

1. Input JSON file of the layout detector as an input path.

2. Initiate the Block Segmenter Workflow:

   WF URL: https://auth.anuvaad.org/anuvaad-etl/wf-manager/v1/workflow/async/initiate

   Block Segmenter Input:

   {
       "files": [
           {
               "locale": "language",
               "path": "layout_detector_output",
               "type": "json",
               "config": {
                   "OCR": {
                       "option": "HIGH_ACCURACY",
                       "language": "language"
                   }
               }
           }
       ],
       "workflowCode": "WF_A_BS"
   }

• Input: Output of block segmenter

• Output: Text collation at word, line, and paragraph level using Google Vision as the OCR engine.

Tesseract OCR

• Input: Output of block segmenter

• Output: Text collation at word, line, and paragraph level using Anuvaad OCR model.

Github repo: OCR Tesseract Server

API contract: Google Vision API Contract

How to use: Tesseract OCR

1. Input JSON file of the block segmenter as an input path.

2. Initiate the Tesseract OCR Workflow:

   WF URL: https://auth.anuvaad.org/anuvaad-etl/wf-manager/v1/workflow/async/initiate

   Tesseract OCR Input:

   {
       "files": [
           {
               "locale": "language",
               "path": "block_segmenter_output",
               "type": "json",
               "config": {
                   "OCR": {
                       "option": "HIGH_ACCURACY",
                       "language": "language"
                   }
               }
           }
       ],
       "workflowCode": "WF_A_OD20TES"
   }

Google OCR (Tesseract Alternative)

How to use: Google Vision OCR

1. Input JSON file of the block segmenter as an input path.

2. Initiate the Google OCR Workflow:

   WF URL: https://auth.anuvaad.org/anuvaad-etl/wf-manager/v1/workflow/async/initiate

   Google OCR Input:

   {
       "files": [
           {
               "locale": "language",
               "path": "block_segmenter_output",
               "type": "json",
               "config": {
                   "OCR": {
                       "option": "HIGH_ACCURACY",
                       "language": "language"
                   }
               }
           }
       ],
       "workflowCode": "WF_A_OTES"
   }

Github repo: OCR Google Vision Server

API contract: Google Vision API Contract