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

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>"
}