Relative Static Crop

Class: RelativeStaticCropBlockV1

Source: inference.core.workflows.core_steps.transformations.relative_static_crop.v1.RelativeStaticCropBlockV1

Crop a Region of Interest (RoI) from an image, using relative coordinates.

This is useful when placed after an ObjectDetection block as part of a multi-stage workflow. For example, you could use an ObjectDetection block to detect objects, then the RelativeStaticCrop block to crop objects, then an OCR block to run character recognition on each of the individual cropped regions.

Type identifier

Use the following identifier in step "type" field: roboflow_core/relative_statoic_crop@v1to add the block as as step in your workflow.

Properties

Name	Type	Description	Refs
name	str	Enter a unique identifier for this step..	❌
x_center	float	Center X of static crop (relative coordinate 0.0-1.0).	✅
y_center	float	Center Y of static crop (relative coordinate 0.0-1.0).	✅
width	float	Width of static crop (relative value 0.0-1.0).	✅
height	float	Height of static crop (relative value 0.0-1.0).	✅

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 Relative Static Crop in version v1.

• inputs: Bounding Box Visualization, Stitch Images, SIFT, Color Visualization, Stability AI Outpainting, Blur Visualization, Image Threshold, Model Comparison Visualization, SIFT Comparison, Image Slicer, Corner Visualization, Background Color Visualization, Image Contours, Camera Focus, Absolute Static Crop, Label Visualization, Line Counter Visualization, Mask Visualization, QR Code Generator, Classification Label Visualization, Detections Consensus, Trace Visualization, Reference Path Visualization, Polygon Visualization, Perspective Correction, Camera Calibration, Image Blur, Dynamic Crop, Circle Visualization, Grid Visualization, Clip Comparison, Identify Outliers, Image Convert Grayscale, Image Slicer, Depth Estimation, Dot Visualization, Image Preprocessing, Relative Static Crop, Ellipse Visualization, Stability AI Inpainting, Keypoint Visualization, Identify Changes, Halo Visualization, Polygon Zone Visualization, Icon Visualization, Triangle Visualization, Crop Visualization, Stability AI Image Generation, Pixelate Visualization
• outputs: Bounding Box Visualization, Llama 3.2 Vision, Keypoint Detection Model, Stability AI Outpainting, Moondream2, Image Threshold, Detections Stabilizer, Model Comparison Visualization, SIFT Comparison, LMM, Gaze Detection, Image Slicer, Corner Visualization, Background Color Visualization, Image Contours, CogVLM, Mask Visualization, Classification Label Visualization, Buffer, Trace Visualization, Polygon Visualization, Florence-2 Model, Instance Segmentation Model, Perspective Correction, Clip Comparison, Instance Segmentation Model, Image Convert Grayscale, LMM For Classification, Dot Visualization, Google Gemini, Relative Static Crop, Keypoint Detection Model, Pixel Color Count, Object Detection Model, Ellipse Visualization, Halo Visualization, Polygon Zone Visualization, Time in Zone, VLM as Detector, Icon Visualization, Triangle Visualization, Crop Visualization, Pixelate Visualization, Single-Label Classification Model, CLIP Embedding Model, SIFT, Single-Label Classification Model, Stitch Images, Color Visualization, QR Code Detection, Blur Visualization, VLM as Classifier, Anthropic Claude, Camera Focus, Florence-2 Model, Absolute Static Crop, Label Visualization, Line Counter Visualization, Perception Encoder Embedding Model, Multi-Label Classification Model, Reference Path Visualization, Camera Calibration, Image Blur, Dynamic Crop, Qwen2.5-VL, OpenAI, VLM as Classifier, Roboflow Dataset Upload, Segment Anything 2 Model, Circle Visualization, Template Matching, Dominant Color, YOLO-World Model, OCR Model, Byte Tracker, Image Slicer, OpenAI, Depth Estimation, OpenAI, Image Preprocessing, Stability AI Inpainting, Keypoint Visualization, Barcode Detection, Multi-Label Classification Model, Roboflow Dataset Upload, Clip Comparison, Object Detection Model, Stability AI Image Generation, VLM as Detector, Detections Stitch, SmolVLM2, Google Vision OCR

Input and Output Bindings

The available connections depend on its binding kinds. Check what binding kinds Relative Static Crop in version v1 has.

Bindings

• input

  • images (image): The image to infer on..
  • x_center (float_zero_to_one): Center X of static crop (relative coordinate 0.0-1.0).
  • y_center (float_zero_to_one): Center Y of static crop (relative coordinate 0.0-1.0).
  • width (float_zero_to_one): Width of static crop (relative value 0.0-1.0).
  • height (float_zero_to_one): Height of static crop (relative value 0.0-1.0).

• output

  • crops (image): Image in workflows.

Example JSON definition of step Relative Static Crop in version v1

{
    "name": "<your_step_name_here>",
    "type": "roboflow_core/relative_statoic_crop@v1",
    "images": "$inputs.image",
    "x_center": 0.3,
    "y_center": 0.3,
    "width": 0.3,
    "height": 0.3
}