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

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
}