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:
Polygon Visualization,Polygon Visualization,SIFT,Circle Visualization,Classification Label Visualization,Line Counter Visualization,Stability AI Image Generation,Relative Static Crop,Image Blur,Grid Visualization,Reference Path Visualization,Camera Focus,Image Preprocessing,Keypoint Visualization,Icon Visualization,Color Visualization,Halo Visualization,Triangle Visualization,Dot Visualization,QR Code Generator,Contrast Enhancement,Absolute Static Crop,Dynamic Crop,Stability AI Inpainting,Image Slicer,Background Subtraction,Label Visualization,Background Color Visualization,Bounding Box Visualization,Polygon Zone Visualization,Stability AI Outpainting,Crop Visualization,Pixelate Visualization,Image Convert Grayscale,Mask Visualization,Halo Visualization,Heatmap Visualization,Image Slicer,Perspective Correction,Stitch Images,Text Display,Morphological Transformation,Morphological Transformation,Image Threshold,Blur Visualization,Depth Estimation,Trace Visualization,Camera Focus,Contrast Equalization,Camera Calibration,Corner Visualization,Ellipse Visualization,Model Comparison Visualization,SIFT Comparison,Image Contours - outputs:
Cache Set,MoonshotAI Kimi,Roboflow Asset Library Attributes,Path Deviation,Image Blur,Overlap Filter,Reference Path Visualization,PTZ Tracking (ONVIF),Event Writer,Slack Notification,SAM2 Video Tracker,Halo Visualization,CLIP Embedding Model,Google Gemma,Qwen 3.6 API,Dot Visualization,Label Visualization,Background Color Visualization,Llama 3.2 Vision,Email Notification,SAM 3 Interactive,Velocity,Pixelate Visualization,OpenAI-Compatible LLM,Google Gemini,Anthropic Claude,Track Class Lock,Cache Get,OpenAI,Trace Visualization,Llama 3.2 Vision,Detection Event Log,ByteTrack Tracker,OpenAI,Clip Comparison,GLM-OCR,Camera Focus,MQTT Writer,Webhook Sink,SIFT Comparison,Local File Sink,Google Gemini,MoonshotAI Kimi,Polygon Visualization,Classification Label Visualization,Instance Segmentation Model,Keypoint Visualization,Instance Segmentation Model,Icon Visualization,Seg Preview,Dynamic Crop,Stability AI Inpainting,Bounding Box Visualization,Polygon Zone Visualization,Stability AI Outpainting,Multi-Label Classification Model,Crop Visualization,BoT-SORT Tracker,Detections Transformation,Byte Tracker,Mask Visualization,Halo Visualization,Detections Stitch,Distance Measurement,Detection Offset,SORT Tracker,Anthropic Claude,Morphological Transformation,Text Display,Overlap Analysis,Roboflow Dataset Upload,Detections Consensus,Detections Filter,Ellipse Visualization,Detections Merge,Keypoint Detection Model,SAM3 Video Tracker,Time in Zone,SAM 3,Size Measurement,Circle Visualization,Semantic Segmentation Model,Path Deviation,Twilio SMS Notification,Email Notification,S3 Sink,Byte Tracker,SAM 3,LMM For Classification,Mask Area Measurement,Heatmap Visualization,Google Gemma API,OpenAI,Time in Zone,Morphological Transformation,Single-Label Classification Model,YOLO-World Model,Current Time,Blur Visualization,Stitch OCR Detections,Moondream2,Detections List Roll-Up,Florence-2 Model,Google Gemini,Corner Visualization,OpenRouter,Detections Stabilizer,Pixel Color Count,Model Comparison Visualization,SAM 3,Model Monitoring Inference Aggregator,Google Vision OCR,Image Threshold,Byte Tracker,Instance Segmentation Model,LMM,Polygon Visualization,Segment Anything 2 Model,Time in Zone,Stability AI Image Generation,Line Counter Visualization,Line Counter,CogVLM,Qwen3.5-VL,Per-Class Confidence Filter,Image Preprocessing,Stitch OCR Detections,Anthropic Claude,OPC UA Writer Sink,Color Visualization,Detections Combine,Triangle Visualization,QR Code Generator,Qwen 3.5 API,Roboflow Dataset Upload,OC-SORT Tracker,OpenAI,Qwen-VL,Florence-2 Model,Perspective Correction,Roboflow Vision Events,Microsoft SQL Server Sink,Twilio SMS/MMS Notification,Perception Encoder Embedding Model,Instance Segmentation Model,Depth Estimation,Roboflow Custom Metadata,Contrast Equalization,Detections Classes Replacement,Line Counter,Object Detection Model
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"
}