Joget DX 8 Stable Released
The stable release for Joget DX 8 is now available, with a focus on UX and Governance.
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Table of Contents
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title | Definition | The Simple Tensorflow AI Decision plugin allows one to run an AI modelmap it on a process route, execute a pre-trained Tensorflow AI model and use the output result for decision making. |
Warning |
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The following are the list of required items before using Simple Tensorflow AI Decision:
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Warning |
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Please take note that the Decision Tool Plugin will take precedence over existing conventional conditional setup in the Process Builder |
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This is a new feature in Joget DX |
Warning |
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Please take note that the Decision Tool Plugin will take precedence over existing conventional conditional setup in the Process Builder |
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Properties
Name | Description | ||||||
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Tensorflow Session | The Tensorflow Session properties are defined here:
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Figure 2 : Simple Tensorflow AI Decision Properties - Add Session
Rules | The Rules properties are defined defined here:
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Sub-element | Description |
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Model |
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Delete Session |
Input Output | When hovering the mouse over the Add Input, a list of Pre-Processing Input types will be available as shown below:
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Add Output | see Add Output properties |
Figure 3 : Simple Tensorflow AI Decision Properties -
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Sub-element | Description |
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Input Name |
Defined Input Tensor | |
Script | Script in Java. Please see Bean Shell Programming Guide for code example. |
Delete Input |
Figure 4 : Simple Tensorflow AI Decision Properties - Add Input - Image properties are defined here:
Sub-element | Description |
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Input Name |
Defined Input Tensor | ||||||
Type |
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File Source |
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URL or Image Upload Field ID |
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Width | Width in Integer | |||||
Height | Height in Integer | |||||
Mean | Mean in Integer
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Scale | Scale in Integer
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Delete Input |
Figure 5 : Simple Tensorflow AI Decision Properties - Add Input - Image properties are defined here:
Sub-element | Description |
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Input Name |
Defined Input Tensor |
Type |
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Delete Input |
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Sub-element | Description |
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Input Name |
Defined Input Tensor | |
File Source |
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URL or |
File Upload Field ID |
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Width | Width in Integer |
Height | Height in Integer |
FFT Size | FFT Size in Integer |
Overlap Size | Overlap Size in Integer |
Min Frequency (Hz) | Minimum Frequency (Hz) in |
Max Frequency (Hz) | Maximum Frequency (Hz) in |
Delete Input |
Sub-element | Description |
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Input Name | Defined Input Tensor |
Type |
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Number Values (Separated by) | separate number values by ; |
Delete Input |
Sub-element | Description |
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Input |
The Add Output properties are defined here:
Name | Defined Input Tensor |
Type |
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Text Value | The text value inputted to be inserted into the Tensor. Can use Hash Variable. |
Dictionary (JSON/CSV) | Dictionary in JSON or CSV format |
Max Length | Maximum Length |
Leave Empty In Front | check to leave the front of the Value as Empty (or whatever value based on dictionary) |
Delete Input |
Sub-element | Description |
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Output Name |
Defined Output Tensor |
Temporary Variable Name |
The Output Tensor Value will be inserted into this user-defined Temporary Variable to be later used during Post-Processing | |
Delete Output |
The Add Post Processing properties are defined here:
Sub-element | Description |
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Post Processing Name | User-defined variable. Can be used as a Variable in the Rules |
Script | Script in Java. Please see Bean Shell Programming Guide for code example. Injected variables available for consumption are:-
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Delete Post-Processing |
Sub-element | Description |
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Post Processing Name | User-defined variable. Can be used as a Variable in the Rules |
Get Unique Only | Check to get only unique value only |
Labels (CSV) | Dictionary file in .csv format |
Temporary Variable Name | List of Temporary Variables from Output |
Number of Values | List of Temporary Variables from Output |
Delete Post-Processing |
Sub-element | Description |
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Post-Processing Name | User-defined variable. Can be used as a Variable in the Rules |
Temporary Variable Name | List of Temporary Variables from Output |
Temporary Variable Name | List of Temporary Variables from Output |
Delete Post-Processing |
Sub-element | Description |
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Figure : Simple Tensorflow AI Decision Properties - Add Rule properties are defined here:
Post Processing Name | User-defined variable. Can be used as a Variable in the Rules |
Threshold | set the Threshold value e.g. 0.01 |
Get Highest Only | Check to get the highest value only |
Labels (CSV) | Dictionary file in .csv format |
Temporary Variable Name | List of Temporary Variables from Output |
Delete Post-Processing |
Name | Description |
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Toggle between EQUAL and NOT EQUAL | |
Split Type |
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Add Condition | Adds a Condition within the IF statement. see Add Condition properties below |
Add Group | Adds a Group within the IF statement. Properties will be similar in Add Rule properties |
Delete Rule |
Sort - Click and drag to reorder Rule above or below another Rule | |
Add Action | Adds an Action within the THEN statement. |
Figure : Simple Tensorflow AI Decision Properties - Add Condition properties are defined here:
Sub-elementName | Description |
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Toggle between EQUAL and NOT EQUAL | |
Variable | User input the variable name. Also accepts the use Temporary Variable or Post Processing Name |
Operation |
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Value | User to input the value of the Variable |
Delete Condition |
Figure : Simple Tensorflow AI Decision Properties - Add Action properties are defined here:
Sub-elementName | Description | |||||
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Type |
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Transition | Will display a selection of all available transitions based on the selected Route inserted as part of the process flow
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Workflow Variable |
Will display a selection of all available workflow variables based on the current Process
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Value | User to input the value of the selected Workflow Variable. Also accepts the use Temporary Variable or Post Processing Name
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Delete Action |
Demo AI - Facial Recognition app:
APP_demo_ai_face_recog-demoApp_noPB.zip
Note: The pre-trained AI model below must be added to this app before ready to use.
Pre-trained AI model:
Note: Please download the AI model here, extract the zip, and add the 20180402-114759.pb file into the app's Resource in the Properties and Export app design menu.
Credits:
Facenet Tensorflow for pre-trained AI model: https://github.com/davidsandberg/facenet
VGGFace2 for the training dataset: https://github.com/ox-vgg/vgg_face2