AI Classification (Multi-Class)

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Function Description

This step performs intelligent multi-class classification of workpieces in images. Through image acquisition, target-region setup, and category labeling, combined with deep-learning training and validation, it can automatically identify the specific class of each workpiece.

Using this step requires a "Lite AI" feature license. Contact Mech-Mind sales to obtain it.

Usage Scenario

This step is suitable for scenarios requiring accurate object category differentiation. It is typically preceded by 2D Smart Camera or 2D Matching. The former is suitable when target positions are relatively fixed, where images are acquired and then classified. The latter is suitable when target positions are offset, where pose-transformation parameters are obtained through alignment steps and input to this step to synchronously adjust target-region positions for stable classification.

Input and Output

Input

Input Port	Data Type	Description
Image	Image	Workpiece images to be classified.
2D Alignment Parameter Group	Pose2D[]	Synchronously adjusts poses of target regions based on pose transformations of target objects.

Input Port

Data Type

Description

Image

Workpiece images to be classified.

2D Alignment Parameter Group

Pose2D[]

Synchronously adjusts poses of target regions based on pose transformations of target objects.

Output

Output Port Data Type Description

Output Port	Data Type	Description
Classification Result	String[]	Classified category names.
Classification Judgment Result	String[]	Classification judgment result: OK or NG.
Classification Status	Bool[]	Indicates whether classification succeeds. `true` for success and `false` for failure.
Classification Confidence	Number[]	Confidence of each classification result.
Detected Image	Image[]	Images with detection results.

Classification Result

String[]

Classified category names.

Classification Judgment Result

String[]

Classification judgment result: OK or NG.

Classification Status

Bool[]

Indicates whether classification succeeds. true for success and false for failure.

Classification Confidence

Number[]

Confidence of each classification result.

Detected Image

Image[]

Images with detection results.

Parameter Description

Parameter	Description
Model Name	Description: Select a configured model from the drop-down list. Models need to be added in the editor in advance. Adjustment instruction: Click Configuration Wizard (or the Configuration Wizard button on the step block) to enter the AI Classification (Multi-Class) Tool and configure models. For usage, refer to AI Classification (Multi-Class) Tool.
Visualize Detection Results	Description: After selection, this step outputs images with detection results for debugging and result review. Default value: Not selected.

Parameter

Description

Model Name

Description: Select a configured model from the drop-down list. Models need to be added in the editor in advance.

Adjustment instruction: Click Configuration Wizard (or the Configuration Wizard button on the step block) to enter the AI Classification (Multi-Class) Tool and configure models. For usage, refer to AI Classification (Multi-Class) Tool.

Visualize Detection Results

Description: After selection, this step outputs images with detection results for debugging and result review.

AI Classification (Multi-Class)

Function Description

Usage Scenario

Input and Output

Input

Output

Parameter Description

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