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