Buffer
Returns an array of the last `length` values passed to it.
Maintain a sliding window buffer of the last N values by storing recent inputs in a FIFO (First-In-First-Out) queue, with newest elements added to the beginning and oldest elements automatically removed when the buffer exceeds the specified length, enabling temporal data collection, frame history tracking, batch processing preparation, and sliding window analysis workflows.
How This Block Works
This block maintains a rolling buffer that stores the most recent values passed to it, creating a sliding window of data over time. The block:
Receives input data of any type (images, detections, values, etc.) and configuration parameters (buffer length and padding option)
Maintains an internal buffer that persists across workflow executions:
Buffer is initialized as an empty list when the block is first created
Buffer state persists for the lifetime of the workflow execution
Each buffer block instance maintains its own separate buffer
Adds new data to the buffer:
Inserts the newest value at the beginning (index 0) of the buffer array
Most recent values appear first in the buffer
Older values are shifted to later positions in the array
Manages buffer size:
When buffer length exceeds the specified
lengthparameter, removes the oldest elementsKeeps only the most recent
lengthvaluesAutomatically maintains the sliding window size
Applies optional padding:
If
padis True: Fills the buffer withNonevalues until it reaches exactlylengthelementsEnsures consistent buffer size even when fewer than
lengthvalues have been receivedIf
padis False: Buffer size grows from 0 tolengthas values are added, then stays atlength
Returns the buffered array:
Outputs a list containing the buffered values in order (newest first)
List length equals
length(if padding enabled) or current buffer size (if padding disabled)Values are ordered from most recent (index 0) to oldest (last index)
The buffer implements a sliding window pattern where new data enters at the front and old data exits at the back when capacity is reached. This creates a temporal history of recent values, useful for operations that need to look back at previous frames, detections, or measurements. The buffer works with any data type, making it flexible for images, detections, numeric values, or other workflow outputs.
Common Use Cases
Frame History Tracking: Maintain a history of recent video frames for temporal analysis (e.g., track frame sequences, maintain recent image history, collect frames for comparison), enabling temporal frame analysis workflows
Detection History: Buffer recent detections for trend analysis or comparison (e.g., track detection changes over time, compare current vs previous detections, analyze detection patterns), enabling detection history workflows
Batch Processing Preparation: Collect multiple values before processing them together (e.g., batch process recent images, aggregate multiple detections, prepare data for batch operations), enabling batch processing workflows
Sliding Window Analysis: Perform analysis on a rolling window of data (e.g., analyze trends over recent frames, calculate moving averages, detect changes in sequences), enabling sliding window analysis workflows
Visualization Sequences: Maintain recent data for animation or sequence visualization (e.g., create frame sequences, visualize temporal changes, display recent history), enabling temporal visualization workflows
Temporal Comparison: Compare current values with recent historical values (e.g., compare current frame with previous frames, detect changes over time, analyze temporal patterns), enabling temporal comparison workflows
Connecting to Other Blocks
This block receives data of any type and produces a buffered output array:
After any block that produces values to buffer (e.g., buffer images from image sources, buffer detections from detection models, buffer values from analytics blocks), enabling data buffering workflows
Before blocks that process arrays to provide batched or historical data (e.g., process buffered images, analyze detection arrays, work with value sequences), enabling array processing workflows
Before visualization blocks to display sequences or temporal data (e.g., visualize frame sequences, display detection history, show temporal patterns), enabling temporal visualization workflows
Before analysis blocks that require historical data (e.g., analyze trends over time, compare current vs historical, process temporal sequences), enabling temporal analysis workflows
Before aggregation blocks to provide multiple values for aggregation (e.g., aggregate buffered values, process multiple detections, combine recent data), enabling aggregation workflows
In temporal processing pipelines where maintaining recent history is required (e.g., track changes over time, maintain frame sequences, collect data for temporal analysis), enabling temporal processing workflows
Requirements
This block works with any data type (images, detections, values, etc.). The buffer maintains state across workflow executions within the same workflow instance. The length parameter determines the maximum number of values to keep in the buffer. When pad is enabled, the buffer will always return exactly length elements (padded with None if needed). When pad is disabled, the buffer grows from 0 to length elements as values are added, then maintains length elements by removing oldest values. The buffer persists for the lifetime of the workflow execution and resets when the workflow is restarted.
Type identifier
Use the following identifier in step "type" field: roboflow_core/buffer@v1 to add the block as a step in your workflow.
Properties
Name
Type
Description
Refs
name
str
Enter a unique identifier for this step..
❌
length
int
Maximum number of elements to keep in the buffer. When the buffer exceeds this length, the oldest elements are automatically removed. Determines the size of the sliding window. Must be greater than 0. Typical values range from 2-10 for frame sequences, or higher for longer histories..
❌
pad
bool
Enable padding to maintain consistent buffer size. If True, the buffer is padded with None values until it reaches exactly length elements, ensuring the output always has length items even when fewer values have been received. If False, the buffer grows from 0 to length as values are added, then maintains length by removing oldest values. Use padding when downstream blocks require a fixed-size array..
❌
The Refs column marks possibility to parametrise the property with dynamic values available in workflow runtime. See Bindings for more info.
Runtime compatibility
soft - runtime hosted_serverless, dedicated_deployment; execution remote; input video : Block keeps per-video state in process memory (keyed by video_metadata.video_identifier). With remote step execution on stateless or multi-replica HTTP runtimes, successive requests may be served by different worker processes, so the state resets between calls and the output is meaningless for tracking / counting / aggregation. Use local step execution in a persistent WebRTC session for stable cross-frame results.
soft - input image : Block depends on temporal context from video or repeated-frame workflows. With a still image/photo, there is no meaningful history to track, compare, aggregate, or visualize, so the block provides little or no benefit.
Input and Output Bindings
The available connections depend on its binding kinds. Check what binding kinds Buffer in version v1 has.
Input and output bindings
input
data(Union[list_of_values,image,*]): Input data of any type to add to the buffer. Can be images, detections, values, or any other workflow output. Newest values are added to the beginning of the buffer array. The buffer maintains a sliding window of the most recent values..
output
output(list_of_values): List of values of any type.
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