Absolute Static Crop

Class: AbsoluteStaticCropBlockV1

Source: inference.core.workflows.core_steps.transformations.absolute_static_crop.v1.AbsoluteStaticCropBlockV1

Crop a Region of Interest (RoI) from an image, using absolute 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 AbsoluteStaticCrop 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/absolute_static_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	int	Center X of static crop (absolute coordinate).	✅
y_center	int	Center Y of static crop (absolute coordinate).	✅
width	int	Width of static crop (absolute value).	✅
height	int	Height of static crop (absolute value).	✅

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 Absolute Static Crop in version v1.

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

Input and Output Bindings

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

Bindings

• input

  • images (image): The image to infer on..
  • x_center (integer): Center X of static crop (absolute coordinate).
  • y_center (integer): Center Y of static crop (absolute coordinate).
  • width (integer): Width of static crop (absolute value).
  • height (integer): Height of static crop (absolute value).

• output

  • crops (image): Image in workflows.

Example JSON definition of step Absolute Static Crop in version v1

{
    "name": "<your_step_name_here>",
    "type": "roboflow_core/absolute_static_crop@v1",
    "images": "$inputs.image",
    "x_center": 40,
    "y_center": 40,
    "width": 40,
    "height": 40
}