Stitch OCR Detections¶
Class: 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:
-
📐 Grouping text detections into rows based on their vertical (
y) positions -
📏 Sorting detections within each row by horizontal (
x) position -
📜 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 ⬆️
-
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:
Time in Zone,Detections Stitch,Path Deviation,Detection Offset,SIFT Comparison,Line Counter,SIFT Comparison,Image Contours,Object Detection Model,Perspective Correction,Byte Tracker,Time in Zone,Line Counter,Detections Stabilizer,Detections Filter,YOLO-World Model,Path Deviation,VLM as Detector,Distance Measurement,Byte Tracker,Pixel Color Count,VLM as Detector,Google Vision OCR,Detections Consensus,Object Detection Model,Byte Tracker,Detections Transformation,Detections Classes Replacement,Template Matching - outputs:
Path Deviation,LMM For Classification,Line Counter,Instance Segmentation Model,CLIP Embedding Model,Mask Visualization,Line Counter,YOLO-World Model,Model Monitoring Inference Aggregator,Cache Get,Polygon Visualization,Halo Visualization,Google Vision OCR,Model Comparison Visualization,Email Notification,CogVLM,Image Threshold,Keypoint Visualization,Image Preprocessing,Roboflow Dataset Upload,Slack Notification,Background Color Visualization,Bounding Box Visualization,Ellipse Visualization,Classification Label Visualization,Label Visualization,Line Counter Visualization,LMM,Stability AI Inpainting,Reference Path Visualization,Dynamic Crop,Triangle Visualization,Distance Measurement,Time in Zone,Detections Stitch,Florence-2 Model,SIFT Comparison,Corner Visualization,Perspective Correction,Local File Sink,Polygon Zone Visualization,Twilio SMS Notification,Trace Visualization,Webhook Sink,Size Measurement,OpenAI,Roboflow Custom Metadata,Cache Set,Crop Visualization,Instance Segmentation Model,Roboflow Dataset Upload,Clip Comparison,Anthropic Claude,Image Blur,Circle Visualization,Dot Visualization,Google Gemini,Segment Anything 2 Model,Florence-2 Model,Time in Zone,Path Deviation,OpenAI,Color Visualization,Pixel Color Count,Llama 3.2 Vision
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
}