EasyOCR¶
Class: EasyOCRBlockV1
Source: inference.core.workflows.core_steps.models.foundation.easy_ocr.v1.EasyOCRBlockV1
Retrieve the characters in an image using EasyOCR 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.
Note that EasyOCR has limitations running within containers on Apple Silicon.
Type identifier¶
Use the following identifier in step "type" field: roboflow_core/easy_ocr@v1to add the block as
as step in your workflow.
Properties¶
| Name | Type | Description | Refs |
|---|---|---|---|
name |
str |
Unique name of step in workflows. | ❌ |
language |
str |
Language model to use for OCR. | ❌ |
quantize |
bool |
Quantized models are smaller and faster, but may be less accurate and won't work correctly on all hardware.. | ❌ |
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 EasyOCR in version v1.
- inputs:
Heatmap Visualization,Image Slicer,Polygon Zone Visualization,Contrast Enhancement,Stability AI Image Generation,Image Threshold,Line Counter Visualization,Trace Visualization,Blur Visualization,Camera Calibration,Depth Estimation,QR Code Generator,Stability AI Outpainting,Icon Visualization,SIFT Comparison,Morphological Transformation,Background Subtraction,Keypoint Visualization,Color Visualization,Perspective Correction,Bounding Box Visualization,Corner Visualization,Stitch Images,Halo Visualization,Image Blur,Image Convert Grayscale,Morphological Transformation,Camera Focus,Contrast Equalization,Halo Visualization,Stability AI Inpainting,Roboflow Visual Search,Classification Label Visualization,Triangle Visualization,Grid Visualization,Background Color Visualization,Mask Visualization,Ellipse Visualization,Pixelate Visualization,Reference Path Visualization,SIFT,Label Visualization,Image Slicer,Text Display,Dot Visualization,Polygon Visualization,Crop Visualization,Dynamic Crop,Absolute Static Crop,Circle Visualization,Image Contours,Image Preprocessing,Polygon Visualization,Relative Static Crop,Camera Focus,Model Comparison Visualization - outputs:
Line Counter,MoonshotAI Kimi,Stability AI Image Generation,Trace Visualization,Path Deviation,Anthropic Claude,Per-Class Confidence Filter,Icon Visualization,SIFT Comparison,Morphological Transformation,Color Visualization,LMM For Classification,Perspective Correction,Corner Visualization,Roboflow Custom Metadata,Detections Merge,Halo Visualization,Qwen-VL,Keypoint Detection Model,Email Notification,Halo Visualization,Google Gemma,Background Color Visualization,Email Notification,Ellipse Visualization,Twilio SMS/MMS Notification,Text Display,Polygon Visualization,Crop Visualization,Image Preprocessing,Model Monitoring Inference Aggregator,OpenRouter,OpenAI,Florence-2 Model,OpenAI,Heatmap Visualization,Detections Filter,Perception Encoder Embedding Model,Blur Visualization,Depth Estimation,Instance Segmentation Model,Stability AI Outpainting,Anthropic Claude,YOLO-World Model,Google Gemini,Clip Comparison,Google Gemini,Keypoint Visualization,Webhook Sink,Byte Tracker,Florence-2 Model,Current Time,Detections List Roll-Up,Contrast Equalization,OpenAI,Moondream2,Line Counter,Google Gemini,Triangle Visualization,Slack Notification,Overlap Filter,Time in Zone,CLIP Embedding Model,Detections Stabilizer,Multi-Label Classification Model,Local File Sink,Pixel Color Count,GLM-OCR,Roboflow Asset Library Attributes,Polygon Zone Visualization,Google Gemma API,Time in Zone,Stitch OCR Detections,Line Counter Visualization,Semantic Segmentation Model,Distance Measurement,Image Threshold,QR Code Generator,Detection Offset,ByteTrack Tracker,Detection Event Log,Detections Transformation,S3 Sink,Microsoft SQL Server Sink,Mask Area Measurement,Twilio SMS Notification,Google Vision OCR,Image Blur,Detections Combine,Morphological Transformation,Roboflow Vision Events,Size Measurement,PTZ Tracking (ONVIF),Stability AI Inpainting,Classification Label Visualization,Stitch OCR Detections,SAM2 Video Tracker,Event Writer,Qwen3.5-VL,Llama 3.2 Vision,Mask Visualization,Byte Tracker,Reference Path Visualization,Velocity,Label Visualization,Byte Tracker,OPC UA Writer Sink,Dot Visualization,Cache Set,Dynamic Crop,Detections Stitch,Circle Visualization,Llama 3.2 Vision,Path Deviation,SAM3 Video Tracker,BoT-SORT Tracker,Camera Focus,Segment Anything 2 Model,OpenAI-Compatible LLM,MoonshotAI Kimi,Overlap Analysis,CogVLM,Object Detection Model,SAM 3 Interactive,Qwen 3.6 API,Detections Consensus,Bounding Box Visualization,LMM,OpenAI,SAM 3,Instance Segmentation Model,Roboflow Visual Search,Roboflow Dataset Upload,SAM 3,Cache Get,Instance Segmentation Model,Detections Classes Replacement,Pixelate Visualization,Instance Segmentation Model,Roboflow Dataset Upload,SORT Tracker,Track Class Lock,Qwen 3.5 API,Anthropic Claude,Time in Zone,MQTT Writer,Polygon Visualization,OC-SORT Tracker,SAM 3,Model Comparison Visualization,Single-Label Classification Model,Seg Preview
Input and Output Bindings¶
The available connections depend on its binding kinds. Check what binding kinds
EasyOCR 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 EasyOCR in version v1
{
"name": "<your_step_name_here>",
"type": "roboflow_core/easy_ocr@v1",
"images": "$inputs.image",
"language": "<block_does_not_provide_example>",
"quantize": "<block_does_not_provide_example>"
}