Barcode Detection¶
Detect the location of barcodes in an image.
This block is useful for manufacturing and consumer packaged goods projects where you need to detect a barcode region in an image. You can then apply Crop block to isolate each barcode then apply further processing (i.e. OCR of the characters on a barcode).
Type identifier¶
Use the following identifier in step "type" field: roboflow_core/barcode_detector@v1to add the block as
as step in your workflow.
Properties¶
| Name | Type | Description | Refs |
|---|---|---|---|
name |
str |
Enter a unique identifier for this step.. | ❌ |
The Refs column marks possibility to parametrise the property with dynamic values available
in workflow runtime. See Bindings for more info.
Available Connections¶
Check what blocks you can connect to Barcode Detection in version v1.
- inputs:
Reference Path Visualization,Label Visualization,Polygon Zone Visualization,Stability AI Inpainting,Triangle Visualization,Absolute Static Crop,Trace Visualization,Halo Visualization,Ellipse Visualization,SIFT,SIFT Comparison,Pixelate Visualization,Image Blur,Dot Visualization,Model Comparison Visualization,Classification Label Visualization,Dynamic Crop,Image Slicer,Mask Visualization,Perspective Correction,Background Color Visualization,Crop Visualization,Grid Visualization,Relative Static Crop,Line Counter Visualization,Image Convert Grayscale,Image Contours,Stitch Images,Blur Visualization,Image Threshold,Color Visualization,Image Preprocessing,Polygon Visualization,Circle Visualization,Camera Focus,Bounding Box Visualization,Corner Visualization,Keypoint Visualization - outputs: None
Input and Output Bindings¶
The available connections depend on its binding kinds. Check what binding kinds
Barcode Detection in version v1 has.
Bindings
-
input
images(image): The image to infer on.
-
output
predictions(bar_code_detection): Prediction with barcode detection.
Example JSON definition of step Barcode Detection in version v1
{
"name": "<your_step_name_here>",
"type": "roboflow_core/barcode_detector@v1",
"images": "$inputs.image"
}