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

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>"
}