検索：generate-data-table

. Adding a new table In order to create a new table, click [Add Field], select Data Type = “table

A basic element in the extraction schema is the data field. However, akaBot Vision enables the capture of even more complex structures like tables. Adding a predefined table field If you are missing

[4] Capture Custom Table Data

Capturing Custom Table Data in akaBot Vision

Customizing Data Extract

, click [Add Field], select Data Type = “table” and then input the value you want to create a new table

="wikigeneratedid" id="HParagraph1" %) A basic element in the extraction schema is the data field. However, akaBot Vision enables the capture of even more complex structures like tables. == **Adding a predefined table

Each Pipeline defines the structure of Data fields that akaBot Vision extracts. Description When editing this structure you have two options: Use pre-trained Data fields – AkaBot Vision’s Generic AI engine has been pre-trained to recognize specific Data fields and enables you to start extracting data

[3] Configure Fields for Data Extraction

Customizing Data Extract

Configuring Fields for Data Extraction

options: * Use pre-trained Data fields – AkaBot Vision’s Generic AI engine has been pre-trained to recognize specific Data fields and enables you to start extracting data without any additional training

="wikigeneratedid" id="HParagraph1" %) Each Pipeline defines the structure of Data fields that akaBot Vision

and choose data type is "Table". Step 3: (This step is optional) Turn on button "Required" to set require

and data type for each column Step 6: Click "Save" button Table of Content

and Table Field 1. Add Form Field Step 1: On Add Learning Instance screen, click "Add Field" button

the table name on "Label" field and choose data type is "Table". ))) [[image:image-20221028164141-11.png

types of fields: Form Field and Table Field == **1. Add Form Field** == (% class="box infomessage

the field name on "Label" field and choose data type for field on "Data Type" field ))) [[image:image

the documents, however, it can be changed later). Note: The default Document type for a new tenant is "General

for reviewing documents (if need). Step 5: Click "OK" button to complete creating a new pipeline. Table

is "General Invoice". If your company would like to use other document types, please contact our akaBot

" %) ((( Table of Content ))) {{toc depth="4" start="2"/}} ))) )))

Automation of Fields Capture Custom Table Data Configure Automation Type for Pipeline Configure Fields for Data Extraction

[6] Customize Data Extract

Customizing Data Extract

* [[Automation of Fields>>path:/bin/view/akaBot%20Vision/Customizing%20Data%20Extract/Automation%20of%20Fields%20in%20akaBot%20Vision/]] * [[Capture Custom Table Data>>path:/bin/view/akaBot%20Vision

/Configure%20Automation%20Type%20for%20Pipeline%20/]] * [[Configure Fields for Data Extraction>>path:/bin

After importing the document successfully and the data extraction process is successfully finished

, akaBot Vision provides users with the capability to add or remove rows in a table To insert a row, you can click "+" icon To delete a row, you can click "x" icon To add a new row at the end of the table

="wikigeneratedid" %) After importing the document successfully and the data extraction process is successfully

with this status in the “To review” tab in the user interface. [[image:image-20220420193327-1.png||data-xwiki

in each field that has been detected incorrectly [[image:image-20220420193327-2.png||data-xwiki-image

documents to extract data. Staff can create a new learning model by following these below steps: Step 1

choose base model, staff will have to create form fields and table from scratch Step 5: Click "Save

. With the Form Fields, staff should label both "Label" and "Value" for each field if having enough data

, send the learning models to production and use them to run on actual documents to extract data. Staff

||cursorshover="true"]] * If staff doesn't choose base model, staff will have to create form fields and table

" for each field if having enough data in documents. This helps the model will extract data more exactly

Vision: Going to Account/API Keys, generate and copy an API key. akaBot Studio: paste the key in the API

to a pipeline that has Automation Type is Confident, then export them and change the status. Table

akaBot Studio and akaBot Vision by API key. ))) * akaBot Vision: Going to Account/API Keys, generate

. (% style="text-align:center" %) [[image:image-20220420200751-2.png||cursorshover="true" data-xwiki-image

||cursorshover="true"]] ))) (% class="akb-toc" %) ((( (% class="akb-toc-title" %) ((( Table of Content

1. Create an Account Note: Although akaBot Vision currently supports Pre-trained data fields only for Invoice processing, the technology is documented agnostic and can extract data from any

customizable, so you can add/group/remove pipelines as needed. Table of Content

currently supports Pre-trained data fields only for Invoice processing, the technology is documented agnostic and can extract data from any structured document including receipts, purchase orders, shipping

-20220420182302-1.png||alt="image-20220420183141-4.png" data-xwiki-image-style-alignment="center"]] **Step 2

: Choose Automation Type and set conditions for required fields and data formats The Automation Type

will be bypassed Bypass wrong data formats: All the documents with wrong data formats inside will be moved

. If you turn this mode on, all the wrong data formats will be bypassed Step 3: Click [Save] to save

Customizing Data Extract

Automation Type and set conditions for required fields and data formats ))) * The Automation Type will have

fields will be bypassed * Bypass wrong data formats: All the documents with wrong data formats inside

these later. If you turn this mode on, all the wrong data formats will be bypassed [[image:image