ODHUB-LV: API Functions Overview
This article will provide a quick introduction to each LabVIEW API of ODHUB
Create.vi
Activate object detection model. You need either a valid License Content to activate this API.
Inputs:
- Model Path: The path to the trained model
- License Content: The valid content of the license file to activate object detection API
- LabelMaps: List of objects with proper name and ID
Output:
Object Detection reference
Destroy.vi
Destroy an Object Detection reference and clean up resources and memory
DetectObjects.vi
Detect objects from an image in 1D array format.
Input:
- ByteData: An input image in 1D array format
- Row: Number of row of the input image.
- Col: Number of column of the input image.
- minScore: The threshold value to decide if an object is detected from an image data
Output:
Objects: The collection of detected objects. Each object has its own name, class where it belongs, score to show confident level and bounding box location.
DetectObjectsFrom2D.vi
Detect objects from LabVIEW IMAQ U32 - U8 bytes (2D array)
Input:
- Data (U32): An input image in 2D array format
- minScore: The threshold value to decide if an object is detected from an image data
Output:
Objects: The collection of detected objects. Each object has its own name, class where it belongs, score to show confident level and bounding box location.
DetectObjectsFromFile.vi
Detect objects from an image file
Inputs
• Input Image Path: The path to an input image
• minScore: The threshold min score value to decide if an object is detected.
Output:
Output Path: The output path that stores generated output image files with overlays.
DetectObjectsFromImage.vi
Detect objects from an image.
Input:
Image File: The path to an image file
minScore: The threshold value to decide if an object is detected from an image data
Output:
Objects: The collection of detected objects. Each object has its own name, class where it belongs, score to show confidence level and bounding box location.