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

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
}