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

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
}