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