OCR Model¶
Class: OCRModelBlockV1
Source: inference.core.workflows.core_steps.models.foundation.ocr.v1.OCRModelBlockV1
Retrieve the characters in an image using 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:
Circle Visualization,Background Color Visualization,Corner Visualization,Bounding Box Visualization,Line Counter Visualization,Image Preprocessing,Trace Visualization,Label Visualization,Polygon Zone Visualization,Camera Focus,Image Slicer,Image Slicer,Image Blur,Crop Visualization,Dot Visualization,Relative Static Crop,Model Comparison Visualization,Stability AI Inpainting,Pixelate Visualization,Perspective Correction,Image Convert Grayscale,Absolute Static Crop,Mask Visualization,Stability AI Image Generation,Color Visualization,Image Threshold,Dynamic Crop,Halo Visualization,Polygon Visualization,Image Contours,Camera Calibration,SIFT,Reference Path Visualization,Classification Label Visualization,Triangle Visualization,SIFT Comparison,Keypoint Visualization,Grid Visualization,Ellipse Visualization,Stitch Images,Blur Visualization - outputs:
Circle Visualization,Background Color Visualization,Corner Visualization,Twilio SMS Notification,Slack Notification,LMM,Polygon Zone Visualization,Image Blur,Cache Set,Dot Visualization,Path Deviation,Google Gemini,Roboflow Dataset Upload,Stability AI Inpainting,Line Counter,OpenAI,Distance Measurement,Stability AI Image Generation,Webhook Sink,Color Visualization,Image Threshold,Halo Visualization,Polygon Visualization,CogVLM,Instance Segmentation Model,Email Notification,Classification Label Visualization,Llama 3.2 Vision,Google Vision OCR,Roboflow Dataset Upload,Ellipse Visualization,Size Measurement,Pixel Color Count,Cache Get,Bounding Box Visualization,Line Counter Visualization,Image Preprocessing,Trace Visualization,Label Visualization,Local File Sink,Anthropic Claude,Crop Visualization,Detections Stitch,YOLO-World Model,Model Comparison Visualization,Perspective Correction,OpenAI,Path Deviation,Mask Visualization,Time in Zone,Clip Comparison,Time in Zone,Dynamic Crop,Florence-2 Model,Instance Segmentation Model,Florence-2 Model,Reference Path Visualization,CLIP Embedding Model,Triangle Visualization,Model Monitoring Inference Aggregator,SIFT Comparison,Keypoint Visualization,LMM For Classification,Roboflow Custom Metadata,Line Counter,Segment Anything 2 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.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"
}