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

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
}