AI Image Recognition: Difference between revisions
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Resco can integrate with Azure's Custom Vision service to classify images. This essentially allows functions similar to [[barcode scanning]] - except you don't need barcodes! | Resco can integrate with Azure's Custom Vision service to classify images. This essentially allows functions similar to [[barcode scanning]] - except you don't need barcodes! | ||
== Prerequisites == | |||
Mind the following prerequisites for using this function: | |||
* Azure Custom Vision license or subscription and at least one model for classifying images | |||
* Connection to the Internet to access Azure servers that perform the necessary image analysis | |||
* Proper configuration in [[Woodford]] (see below) | |||
== Change field format to barcode == | |||
The entity where you want to use AI Vision has to include a field with barcode format. | |||
# Using [[Woodford]], edit an [[app projects|app project]] and select the entity from the '''Project''' menu. | |||
# Select the field. It must have the type '''Single Line of Text'''. | |||
# On the '''Properties''' pane, set '''Formatting''' to '''Barcode'''. | |||
# Click '''Save'''. | |||
For more information about managing entities and fields in Woodford, see [[App_projects#Managing_entities|Managing entities]]. | |||
== Set up connection to Azure services == | == Set up connection to Azure services == | ||
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== Use case: Place image classifier to a field in a form == | == Use case: Place image classifier to a field in a form == | ||
If you add the field with barcode format to your form, the app displays a custom button that initiates camera and image classification. If the image matches the model (with a probability above a customizable threshold), the name of the model is saved to the field. | |||
[[Category:Woodford]] | [[Category:Woodford]] | ||
Revision as of 06:11, 11 September 2019
| Warning | This page describes a function that has not yet been publicly released, or has been released in beta / preview quality. Subject to change. |
Resco can integrate with Azure's Custom Vision service to classify images. This essentially allows functions similar to barcode scanning - except you don't need barcodes!
Prerequisites
Mind the following prerequisites for using this function:
- Azure Custom Vision license or subscription and at least one model for classifying images
- Connection to the Internet to access Azure servers that perform the necessary image analysis
- Proper configuration in Woodford (see below)
Change field format to barcode
The entity where you want to use AI Vision has to include a field with barcode format.
- Using Woodford, edit an app project and select the entity from the Project menu.
- Select the field. It must have the type Single Line of Text.
- On the Properties pane, set Formatting to Barcode.
- Click Save.
For more information about managing entities and fields in Woodford, see Managing entities.
Set up connection to Azure services
- Edit an app project and select Settings > AI Vision from the Project menu.
- Click New to define a new model.
- As Name, enter the name of the configuration model.
- As Entity, enter the entity where the model should be used.
- As Service type, use Azure.
- For Prediction key and URL, use the values from your Azure Custom Vision site.
- Click OK to save the model.
You can define multiple models as needed.
Use case: Find a record in a view
For entities that include a barcode field and have at least one model created, there's an additional button in the views for AI Vision. It allows you to take a photo. The picture is then analyzed by Azure. If the resulting tag equals the primary name of a record in the list, that record is opened. In effect, this is similar to barcode scanning, using image tag instead of a barcode for record identification.
Use case: Place image classifier to a field in a form
If you add the field with barcode format to your form, the app displays a custom button that initiates camera and image classification. If the image matches the model (with a probability above a customizable threshold), the name of the model is saved to the field.