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: Corner Visualization, Image Convert Grayscale, Label Visualization, Text Display, Blur Visualization, Image Slicer, Triangle Visualization, Image Blur, Relative Static Crop, SIFT Comparison, Camera Focus, Classification Label Visualization, Ellipse Visualization, Halo Visualization, Contrast Equalization, Image Threshold, Stability AI Outpainting, Camera Calibration, Dot Visualization, Background Color Visualization, Polygon Zone Visualization, Keypoint Visualization, Camera Focus, Model Comparison Visualization, Grid Visualization, Stitch Images, Polygon Visualization, Dynamic Crop, Stability AI Inpainting, Reference Path Visualization, Trace Visualization, Crop Visualization, Circle Visualization, Background Subtraction, Stability AI Image Generation, Absolute Static Crop, Icon Visualization, Line Counter Visualization, Image Preprocessing, Color Visualization, SIFT, Perspective Correction, Mask Visualization, Halo Visualization, Image Slicer, Depth Estimation, Pixelate Visualization, Morphological Transformation, Polygon Visualization, QR Code Generator, Image Contours, Bounding Box Visualization
• outputs: Corner Visualization, Label Visualization, Image Blur, Florence-2 Model, SIFT Comparison, Google Gemini, Ellipse Visualization, Halo Visualization, Webhook Sink, Contrast Equalization, Stability AI Outpainting, Perception Encoder Embedding Model, Model Comparison Visualization, Line Counter, Detections Filter, Distance Measurement, Polygon Visualization, Detection Offset, Detection Event Log, Stability AI Inpainting, Reference Path Visualization, OpenAI, OpenAI, Detections Stabilizer, Slack Notification, Circle Visualization, Stability AI Image Generation, Roboflow Dataset Upload, Path Deviation, Detections List Roll-Up, Icon Visualization, LMM For Classification, YOLO-World Model, Pixel Color Count, Cache Get, Twilio SMS/MMS Notification, Model Monitoring Inference Aggregator, Color Visualization, Clip Comparison, Detections Merge, SAM 3, Mask Visualization, Roboflow Dataset Upload, Anthropic Claude, Time in Zone, Detections Classes Replacement, Line Counter, OpenAI, Pixelate Visualization, Byte Tracker, CLIP Embedding Model, Instance Segmentation Model, Email Notification, Google Gemini, Stitch OCR Detections, Text Display, Blur Visualization, Roboflow Custom Metadata, Triangle Visualization, Google Vision OCR, Detections Consensus, Camera Focus, SAM 3, Classification Label Visualization, Detections Combine, Byte Tracker, Image Threshold, LMM, PTZ Tracking (ONVIF).md), Dot Visualization, Anthropic Claude, Time in Zone, Stitch OCR Detections, Background Color Visualization, Seg Preview, Polygon Zone Visualization, Keypoint Visualization, Anthropic Claude, Dynamic Crop, Trace Visualization, SAM 3, Crop Visualization, Detections Transformation, Line Counter Visualization, Florence-2 Model, Time in Zone, Google Gemini, Detections Stitch, Segment Anything 2 Model, Moondream2, Byte Tracker, Overlap Filter, Twilio SMS Notification, Image Preprocessing, Instance Segmentation Model, Perspective Correction, Email Notification, Halo Visualization, Path Deviation, Local File Sink, Depth Estimation, CogVLM, Morphological Transformation, Polygon Visualization, OpenAI, QR Code Generator, Cache Set, Velocity, Llama 3.2 Vision, Bounding Box Visualization, Size Measurement

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>"
}