Stitch OCR Detections

Class: StitchOCRDetectionsBlockV1

Source: inference.core.workflows.core_steps.transformations.stitch_ocr_detections.v1.StitchOCRDetectionsBlockV1

Combines OCR detection results into a coherent text string by organizing detections spatially. This transformation is perfect for turning individual OCR results into structured, readable text!

How It Works

This transformation reconstructs the original text from OCR detection results by:

1. 📐 Grouping text detections into rows based on their vertical (y) positions

2. 📏 Sorting detections within each row by horizontal (x) position

3. 📜 Concatenating the text in reading order (left-to-right, top-to-bottom)

Parameters

• tolerance: Controls how close detections need to be vertically to be considered part of the same line of text. A higher tolerance will group detections that are further apart vertically.

• reading_direction: Determines the order in which text is read. Available options:

  • "left_to_right": Standard left-to-right reading (e.g., English) ➡️

  • "right_to_left": Right-to-left reading (e.g., Arabic) ⬅️

  • "vertical_top_to_bottom": Vertical reading from top to bottom ⬇️

  • "vertical_bottom_to_top": Vertical reading from bottom to top ⬆️

  • "auto": Automatically detects the reading direction based on the spatial arrangement of text elements.

Why Use This Transformation?

This is especially useful for:

• 📖 Converting individual character/word detections into a readable text block

• 📝 Reconstructing multi-line text from OCR results

• 🔀 Maintaining proper reading order for detected text elements

• 🌏 Supporting different writing systems and text orientations

Example Usage

Use this transformation after an OCR model that outputs individual words or characters, so you can reconstruct the original text layout in its intended format.

Type identifier

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

Properties

Name	Type	Description	Refs
name	str	Enter a unique identifier for this step..	❌
reading_direction	str	The direction of the text in the image..	❌
tolerance	int	The tolerance for grouping detections into the same line of text..	✅

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 Stitch OCR Detections in version v1.

• inputs: Line Counter, Line Counter, PTZ Tracking (ONVIF).md), Detections Stabilizer, Image Contours, Byte Tracker, Path Deviation, SIFT Comparison, Overlap Filter, Pixel Color Count, VLM as Detector, Object Detection Model, Time in Zone, Google Vision OCR, Byte Tracker, Detections Consensus, Byte Tracker, Detection Offset, Detections Filter, Time in Zone, Object Detection Model, Detections Transformation, Detections Classes Replacement, YOLO-World Model, Detections Merge, Perspective Correction, Moondream2, Path Deviation, Template Matching, SIFT Comparison, Velocity, Detections Stitch, Distance Measurement, VLM as Detector, Dynamic Crop
• outputs: Anthropic Claude, Crop Visualization, Line Counter, Line Counter, LMM For Classification, PTZ Tracking (ONVIF).md), Line Counter Visualization, Color Visualization, Cache Set, Mask Visualization, Circle Visualization, Google Gemini, Trace Visualization, Image Preprocessing, Roboflow Custom Metadata, Cache Get, Polygon Zone Visualization, LMM, QR Code Generator, YOLO-World Model, Size Measurement, Halo Visualization, CLIP Embedding Model, Florence-2 Model, Moondream2, Perspective Correction, Stability AI Inpainting, Webhook Sink, Label Visualization, Distance Measurement, Pixel Color Count, Segment Anything 2 Model, Perception Encoder Embedding Model, Stability AI Image Generation, Triangle Visualization, Background Color Visualization, Slack Notification, Corner Visualization, Path Deviation, Icon Visualization, Image Blur, Model Comparison Visualization, Llama 3.2 Vision, Instance Segmentation Model, Time in Zone, Image Threshold, Google Vision OCR, Reference Path Visualization, Roboflow Dataset Upload, CogVLM, Roboflow Dataset Upload, OpenAI, Classification Label Visualization, Polygon Visualization, Stability AI Outpainting, Keypoint Visualization, Dot Visualization, Time in Zone, Email Notification, Local File Sink, OpenAI, Bounding Box Visualization, Detections Classes Replacement, Ellipse Visualization, OpenAI, Florence-2 Model, Path Deviation, Model Monitoring Inference Aggregator, Twilio SMS Notification, Instance Segmentation Model, SIFT Comparison, Detections Stitch, Clip Comparison, Dynamic Crop

Input and Output Bindings

The available connections depend on its binding kinds. Check what binding kinds Stitch OCR Detections in version v1 has.

Bindings

• input

  • predictions (object_detection_prediction): The output of an OCR detection model..
  • tolerance (integer): The tolerance for grouping detections into the same line of text..

• output

  • ocr_text (string): String value.

Example JSON definition of step Stitch OCR Detections in version v1

{
    "name": "<your_step_name_here>",
    "type": "roboflow_core/stitch_ocr_detections@v1",
    "predictions": "$steps.my_ocr_detection_model.predictions",
    "reading_direction": "right_to_left",
    "tolerance": 10
}