Buffer

Class: BufferBlockV1

Source: inference.core.workflows.core_steps.fusion.buffer.v1.BufferBlockV1

Returns an array of the last length values passed to it. The newest elements are added to the beginning of the array.

Useful for keeping a sliding window of images or detections for later processing, visualization, or comparison.

Type identifier

Use the following identifier in step "type" field: roboflow_core/buffer@v1to add the block as as step in your workflow.

Properties

Name	Type	Description	Refs
name	str	Enter a unique identifier for this step..	❌
length	int	The number of elements to keep in the buffer. Older elements will be removed..	❌
pad	bool	If True, the end of the buffer will be padded with None values so its size is always exactly length..	❌

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 Buffer in version v1.

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

Input and Output Bindings

The available connections depend on its binding kinds. Check what binding kinds Buffer in version v1 has.

Bindings

• input

  • data (Union[*, image, list_of_values]): Reference to step outputs at depth level n to be concatenated and moved into level n-1..

• output

  • output (list_of_values): List of values of any type.

Example JSON definition of step Buffer in version v1

{
    "name": "<your_step_name_here>",
    "type": "roboflow_core/buffer@v1",
    "data": "$steps.visualization",
    "length": 5,
    "pad": true
}