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