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@v1to 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: Size Measurement, LMM, VLM as Detector, Absolute Static Crop, Multi-Label Classification Model, Distance Measurement, Line Counter Visualization, OCR Model, Image Slicer, Reference Path Visualization, Triangle Visualization, Path Deviation, Line Counter, Detections Transformation, Multi-Label Classification Model, Byte Tracker, Google Vision OCR, Llama 3.2 Vision, Dynamic Zone, Clip Comparison, Perspective Correction, Dot Visualization, Detections Filter, Model Comparison Visualization, Email Notification, Classification Label Visualization, Dimension Collapse, Instance Segmentation Model, Slack Notification, Stability AI Image Generation, Cache Set, Property Definition, Time in Zone, Line Counter, Time in Zone, Trace Visualization, Blur Visualization, Local File Sink, CogVLM, Stability AI Inpainting, Cosine Similarity, Circle Visualization, OpenAI, Moondream2, Stitch Images, Bounding Rectangle, Byte Tracker, SmolVLM2, Grid Visualization, Dominant Color, Polygon Zone Visualization, Keypoint Visualization, Bounding Box Visualization, OpenAI, Halo Visualization, Google Gemini, Ellipse Visualization, Single-Label Classification Model, Pixel Color Count, VLM as Detector, Velocity, Roboflow Dataset Upload, Segment Anything 2 Model, Single-Label Classification Model, Cache Get, VLM as Classifier, Clip Comparison, Delta Filter, Mask Visualization, VLM as Classifier, Byte Tracker, Detections Consensus, Detection Offset, Roboflow Custom Metadata, Buffer, First Non Empty Or Default, Image Convert Grayscale, Rate Limiter, Relative Static Crop, Detections Classes Replacement, Gaze Detection, Background Color Visualization, Camera Focus, Image Contours, Keypoint Detection Model, Instance Segmentation Model, SIFT Comparison, Object Detection Model, Detections Stabilizer, Depth Estimation, Roboflow Dataset Upload, Object Detection Model, Crop Visualization, Webhook Sink, Identify Changes, Camera Calibration, Continue If, Qwen2.5-VL, Detections Merge, Corner Visualization, Image Threshold, QR Code Detection, Keypoint Detection Model, SIFT, Overlap Filter, JSON Parser, Expression, Path Deviation, Florence-2 Model, Twilio SMS Notification, Label Visualization, Image Preprocessing, Detections Stitch, Template Matching, LMM For Classification, Stitch OCR Detections, CLIP Embedding Model, Image Blur, Color Visualization, Barcode Detection, Pixelate Visualization, SIFT Comparison, Data Aggregator, YOLO-World Model, Polygon Visualization, CSV Formatter, Model Monitoring Inference Aggregator, Image Slicer, Environment Secrets Store, Anthropic Claude, Florence-2 Model, Identify Outliers, Dynamic Crop
• 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"
    ]
}