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

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
}