Continue If¶
Class: ContinueIfBlockV1
Source: inference.core.workflows.core_steps.flow_control.continue_if.v1.ContinueIfBlockV1
Based on provided configuration, block decides if it should follow to pointed execution path
Type identifier¶
Use the following identifier in step "type"
field: roboflow_core/continue_if@v1
to add the block as
as step in your workflow.
Properties¶
Name | Type | Description | Refs |
---|---|---|---|
name |
str |
Enter a unique identifier for this step.. | ❌ |
condition_statement |
StatementGroup |
Define the conditional logic.. | ❌ |
The Refs column marks possibility to parametrise the property with dynamic values available
in workflow
runtime. See Bindings for more info.
Available Connections¶
Compatible Blocks
Check what blocks you can connect to Continue If
in version v1
.
- inputs:
Cache Get
,Image Slicer
,Segment Anything 2 Model
,Stability AI Inpainting
,Environment Secrets Store
,Clip Comparison
,Perspective Correction
,Cache Set
,Object Detection Model
,Roboflow Custom Metadata
,Object Detection Model
,SIFT Comparison
,Detection Offset
,CogVLM
,Ellipse Visualization
,Grid Visualization
,SIFT
,VLM as Detector
,Image Contours
,Multi-Label Classification Model
,OpenAI
,Absolute Static Crop
,Camera Focus
,Trace Visualization
,Property Definition
,CLIP Embedding Model
,Multi-Label Classification Model
,VLM as Detector
,Dot Visualization
,Clip Comparison
,Google Vision OCR
,Identify Changes
,Polygon Zone Visualization
,Gaze Detection
,Identify Outliers
,Roboflow Dataset Upload
,First Non Empty Or Default
,Classification Label Visualization
,Corner Visualization
,VLM as Classifier
,Byte Tracker
,Llama 3.2 Vision
,Dynamic Crop
,Line Counter
,Reference Path Visualization
,Label Visualization
,Detections Stabilizer
,Mask Visualization
,Triangle Visualization
,Line Counter Visualization
,Template Matching
,Dynamic Zone
,Detections Transformation
,Dominant Color
,Time in Zone
,Barcode Detection
,Model Monitoring Inference Aggregator
,Blur Visualization
,Line Counter
,Anthropic Claude
,Webhook Sink
,Instance Segmentation Model
,SIFT Comparison
,Time in Zone
,Instance Segmentation Model
,Cosine Similarity
,Slack Notification
,Detections Filter
,Stitch OCR Detections
,Pixelate Visualization
,Path Deviation
,OpenAI
,Relative Static Crop
,Detections Consensus
,Twilio SMS Notification
,Delta Filter
,Dimension Collapse
,VLM as Classifier
,Roboflow Dataset Upload
,Keypoint Detection Model
,Google Gemini
,Rate Limiter
,Model Comparison Visualization
,Halo Visualization
,JSON Parser
,Crop Visualization
,Qwen2.5-VL
,Byte Tracker
,Expression
,Image Blur
,Distance Measurement
,Circle Visualization
,Velocity
,Buffer
,Keypoint Detection Model
,Image Preprocessing
,Background Color Visualization
,Continue If
,QR Code Detection
,Bounding Rectangle
,Pixel Color Count
,Size Measurement
,Florence-2 Model
,Single-Label Classification Model
,Bounding Box Visualization
,Florence-2 Model
,Local File Sink
,Byte Tracker
,Image Slicer
,LMM For Classification
,Stitch Images
,Stability AI Image Generation
,Image Threshold
,Detections Stitch
,OCR Model
,LMM
,Keypoint Visualization
,Email Notification
,Color Visualization
,Path Deviation
,Single-Label Classification Model
,YOLO-World Model
,Data Aggregator
,CSV Formatter
,Image Convert Grayscale
,Detections Classes Replacement
,Polygon Visualization
- outputs: None
Input and Output Bindings¶
The available connections depend on its binding kinds. Check what binding kinds
Continue If
in version v1
has.
Bindings
-
input
evaluation_parameters
(*
): Data to be used in the conditional logic..next_steps
(step): Steps to execute if the condition evaluates to true..
-
output
Example JSON definition of step Continue If
in version v1
{
"name": "<your_step_name_here>",
"type": "roboflow_core/continue_if@v1",
"condition_statement": {
"statements": [
{
"comparator": {
"type": "(Number) =="
},
"left_operand": {
"operand_name": "left",
"type": "DynamicOperand"
},
"right_operand": {
"type": "StaticOperand",
"value": 1
},
"type": "BinaryStatement"
}
],
"type": "StatementGroup"
},
"evaluation_parameters": {
"left": "$inputs.some"
},
"next_steps": [
"$steps.on_true"
]
}