OCR Model

Class: OCRModelBlockV1

Source: inference.core.workflows.core_steps.models.foundation.ocr.v1.OCRModelBlockV1

Retrieve the characters in an image using DocTR Optical Character Recognition (OCR).

This block returns the text within an image.

You may want to use this block in combination with a detections-based block (i.e. ObjectDetectionBlock). An object detection model could isolate specific regions from an image (i.e. a shipping container ID in a logistics use case) for further processing. You can then use a DynamicCropBlock to crop the region of interest before running OCR.

Using a detections model then cropping detections allows you to isolate your analysis on particular regions of an image.

Type identifier

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

Properties

Name	Type	Description	Refs
name	str	Unique name of step in workflows.	❌

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 OCR Model in version v1.

• inputs: Label Visualization, Blur Visualization, Background Color Visualization, Contrast Equalization, Bounding Box Visualization, Camera Calibration, Polygon Visualization, Stability AI Outpainting, Image Slicer, Keypoint Visualization, Reference Path Visualization, Pixelate Visualization, Icon Visualization, Triangle Visualization, Model Comparison Visualization, Corner Visualization, Image Preprocessing, Color Visualization, SIFT Comparison, Line Counter Visualization, Grid Visualization, Stitch Images, Halo Visualization, Stability AI Image Generation, QR Code Generator, Circle Visualization, Image Contours, Relative Static Crop, Dot Visualization, Polygon Zone Visualization, Ellipse Visualization, Image Blur, Absolute Static Crop, Depth Estimation, Image Slicer, Morphological Transformation, Stability AI Inpainting, Dynamic Crop, Camera Focus, Crop Visualization, Image Threshold, Perspective Correction, Image Convert Grayscale, Mask Visualization, Trace Visualization, Classification Label Visualization, SIFT
• outputs: Google Vision OCR, Label Visualization, LMM For Classification, Blur Visualization, Background Color Visualization, Contrast Equalization, Reference Path Visualization, Keypoint Visualization, Stability AI Outpainting, Bounding Box Visualization, Detections Filter, Pixelate Visualization, SAM 3, Perception Encoder Embedding Model, Seg Preview, Byte Tracker, Overlap Filter, Image Preprocessing, SAM 3, Color Visualization, SIFT Comparison, Path Deviation, Detections Combine, Email Notification, Cache Set, Anthropic Claude, Circle Visualization, Polygon Zone Visualization, Ellipse Visualization, Line Counter, Email Notification, Clip Comparison, Moondream2, Model Monitoring Inference Aggregator, Path Deviation, LMM, Time in Zone, Morphological Transformation, Roboflow Dataset Upload, Detections Consensus, Crop Visualization, OpenAI, Florence-2 Model, SAM 3, CogVLM, Roboflow Custom Metadata, Classification Label Visualization, Byte Tracker, Stitch OCR Detections, Segment Anything 2 Model, Time in Zone, Line Counter, YOLO-World Model, Polygon Visualization, PTZ Tracking (ONVIF).md), CLIP Embedding Model, Detection Offset, Detections Classes Replacement, Icon Visualization, Cache Get, Detections Transformation, Triangle Visualization, Roboflow Dataset Upload, Anthropic Claude, Model Comparison Visualization, Florence-2 Model, Distance Measurement, Corner Visualization, Google Gemini, Google Gemini, Line Counter Visualization, Halo Visualization, Size Measurement, Stability AI Image Generation, QR Code Generator, Twilio SMS Notification, Time in Zone, Dot Visualization, Detections Stitch, Llama 3.2 Vision, Image Blur, Slack Notification, Velocity, OpenAI, Local File Sink, Byte Tracker, Instance Segmentation Model, OpenAI, Stability AI Inpainting, Dynamic Crop, Pixel Color Count, Detections Stabilizer, Webhook Sink, Instance Segmentation Model, Image Threshold, Mask Visualization, OpenAI, Perspective Correction, Detections Merge, Trace Visualization

Input and Output Bindings

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

Bindings

• input

  • images (image): The image to infer on..

• output

  • result (string): String value.
  • predictions (object_detection_prediction): Prediction with detected bounding boxes in form of sv.Detections(...) object.
  • parent_id (parent_id): Identifier of parent for step output.
  • root_parent_id (parent_id): Identifier of parent for step output.
  • prediction_type (prediction_type): String value with type of prediction.

Example JSON definition of step OCR Model in version v1

{
    "name": "<your_step_name_here>",
    "type": "roboflow_core/ocr_model@v1",
    "images": "$inputs.image"
}