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

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
}