Perspective Correction

Class: PerspectiveCorrectionBlockV1

Source: inference.core.workflows.core_steps.transformations.perspective_correction.v1.PerspectiveCorrectionBlockV1

The PerspectiveCorrectionBlock is a transformer block designed to correct coordinates of detections based on transformation defined by two polygons. This block is best suited when produced coordinates should be considered as if camera was placed directly above the scene and was not introducing distortions.

Type identifier

Use the following identifier in step "type" field: roboflow_core/perspective_correction@v1to add the block as as step in your workflow.

Properties

Name	Type	Description	Refs
name	str	Enter a unique identifier for this step..	❌
perspective_polygons	List[Any]	Perspective polygons (for each batch at least one must be consisting of 4 vertices).	✅
transformed_rect_width	int	Transformed rect width.	✅
transformed_rect_height	int	Transformed rect height.	✅
extend_perspective_polygon_by_detections_anchor	str	If set, perspective polygons will be extended to contain all bounding boxes. Allowed values: CENTER, CENTER_LEFT, CENTER_RIGHT, TOP_CENTER, TOP_LEFT, TOP_RIGHT, BOTTOM_LEFT, BOTTOM_CENTER, BOTTOM_RIGHT, CENTER_OF_MASS and ALL to extend to contain whole bounding box.	✅
warp_image	bool	If set to True, image will be warped into transformed rect.	✅

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 Perspective Correction in version v1.

• inputs: Keypoint Visualization, Google Gemini, Keypoint Detection Model, Detections Stabilizer, Image Contours, Circle Visualization, Path Deviation, Image Threshold, Absolute Static Crop, Perspective Correction, Color Visualization, Instance Segmentation Model, Reference Path Visualization, Stitch Images, Image Blur, Florence-2 Model, PTZ Tracking (ONVIF).md), Blur Visualization, Local File Sink, Relative Static Crop, Halo Visualization, Clip Comparison, Stability AI Inpainting, SIFT Comparison, Detections Merge, Icon Visualization, Time in Zone, Roboflow Custom Metadata, Dimension Collapse, Polygon Zone Visualization, Depth Estimation, Identify Outliers, Template Matching, Instance Segmentation Model, Stability AI Image Generation, Dynamic Zone, Dynamic Crop, Grid Visualization, Crop Visualization, Stitch OCR Detections, Time in Zone, Detections Consensus, VLM as Classifier, Camera Calibration, Segment Anything 2 Model, VLM as Classifier, Pixel Color Count, QR Code Generator, SIFT, SIFT Comparison, Bounding Rectangle, Detection Offset, Camera Focus, Object Detection Model, Model Comparison Visualization, Detections Filter, Size Measurement, Twilio SMS Notification, Llama 3.2 Vision, Triangle Visualization, Line Counter Visualization, Clip Comparison, Email Notification, LMM, Roboflow Dataset Upload, Time in Zone, CSV Formatter, Image Slicer, Path Deviation, Detections Transformation, Mask Visualization, Byte Tracker, Byte Tracker, Single-Label Classification Model, OCR Model, Pixelate Visualization, JSON Parser, Webhook Sink, Byte Tracker, Object Detection Model, Velocity, Slack Notification, Dot Visualization, Image Slicer, Roboflow Dataset Upload, Detections Classes Replacement, YOLO-World Model, Classification Label Visualization, OpenAI, Model Monitoring Inference Aggregator, VLM as Detector, Polygon Visualization, OpenAI, Buffer, LMM For Classification, Line Counter, Moondream2, Stability AI Outpainting, Trace Visualization, Bounding Box Visualization, Image Preprocessing, Distance Measurement, Overlap Filter, Google Vision OCR, Image Convert Grayscale, Multi-Label Classification Model, Label Visualization, Line Counter, CogVLM, Corner Visualization, Detections Stitch, Background Color Visualization, Florence-2 Model, Identify Changes, VLM as Detector, Ellipse Visualization, OpenAI, Anthropic Claude
• outputs: Google Gemini, Keypoint Visualization, Detections Stabilizer, Path Deviation, Gaze Detection, Reference Path Visualization, Stitch Images, Image Blur, Florence-2 Model, Barcode Detection, Relative Static Crop, Clip Comparison, Icon Visualization, Time in Zone, Polygon Zone Visualization, Identify Outliers, Instance Segmentation Model, Dynamic Zone, Dynamic Crop, Grid Visualization, Detections Consensus, VLM as Classifier, Single-Label Classification Model, Camera Calibration, Perception Encoder Embedding Model, VLM as Classifier, Pixel Color Count, QR Code Generator, SIFT, Camera Focus, Detections Filter, Llama 3.2 Vision, Triangle Visualization, Line Counter Visualization, Multi-Label Classification Model, Email Notification, Roboflow Dataset Upload, Time in Zone, Image Slicer, Byte Tracker, Single-Label Classification Model, OCR Model, Pixelate Visualization, Byte Tracker, Object Detection Model, Dot Visualization, Image Slicer, Roboflow Dataset Upload, OpenAI, Model Monitoring Inference Aggregator, VLM as Detector, Buffer, Trace Visualization, Stability AI Outpainting, Multi-Label Classification Model, Overlap Filter, CogVLM, Corner Visualization, Background Color Visualization, Ellipse Visualization, Halo Visualization, OpenAI, Anthropic Claude, Keypoint Detection Model, Image Contours, Circle Visualization, Image Threshold, Absolute Static Crop, Perspective Correction, Color Visualization, QR Code Detection, Instance Segmentation Model, Blur Visualization, PTZ Tracking (ONVIF).md), Keypoint Detection Model, Stability AI Inpainting, SIFT Comparison, Detections Merge, Roboflow Custom Metadata, SmolVLM2, Depth Estimation, Template Matching, Stability AI Image Generation, Crop Visualization, Stitch OCR Detections, Time in Zone, Segment Anything 2 Model, Dominant Color, SIFT Comparison, Bounding Rectangle, Size Measurement, Detection Offset, Model Comparison Visualization, Object Detection Model, CLIP Embedding Model, Twilio SMS Notification, Clip Comparison, LMM, Path Deviation, Detections Transformation, Mask Visualization, Byte Tracker, Qwen2.5-VL, Webhook Sink, Velocity, Slack Notification, Detections Classes Replacement, YOLO-World Model, Classification Label Visualization, Polygon Visualization, OpenAI, LMM For Classification, Line Counter, Moondream2, Bounding Box Visualization, Distance Measurement, Image Preprocessing, Image Convert Grayscale, Google Vision OCR, Label Visualization, Line Counter, Detections Stitch, Florence-2 Model, Identify Changes, VLM as Detector

Input and Output Bindings

The available connections depend on its binding kinds. Check what binding kinds Perspective Correction in version v1 has.

Bindings

• input

  • predictions (Union[instance_segmentation_prediction, object_detection_prediction]): Predictions.
  • images (image): The input image for this step..
  • perspective_polygons (list_of_values): Perspective polygons (for each batch at least one must be consisting of 4 vertices).
  • transformed_rect_width (integer): Transformed rect width.
  • transformed_rect_height (integer): Transformed rect height.
  • extend_perspective_polygon_by_detections_anchor (string): If set, perspective polygons will be extended to contain all bounding boxes. Allowed values: CENTER, CENTER_LEFT, CENTER_RIGHT, TOP_CENTER, TOP_LEFT, TOP_RIGHT, BOTTOM_LEFT, BOTTOM_CENTER, BOTTOM_RIGHT, CENTER_OF_MASS and ALL to extend to contain whole bounding box.
  • warp_image (boolean): If set to True, image will be warped into transformed rect.

• output

  • corrected_coordinates (Union[object_detection_prediction, instance_segmentation_prediction]): Prediction with detected bounding boxes in form of sv.Detections(...) object if object_detection_prediction or Prediction with detected bounding boxes and segmentation masks in form of sv.Detections(...) object if instance_segmentation_prediction.
  • warped_image (image): Image in workflows.
  • extended_transformed_rect_width (integer): Integer value.
  • extended_transformed_rect_height (integer): Integer value.

Example JSON definition of step Perspective Correction in version v1

{
    "name": "<your_step_name_here>",
    "type": "roboflow_core/perspective_correction@v1",
    "predictions": "$steps.object_detection_model.predictions",
    "images": "$inputs.image",
    "perspective_polygons": "$steps.perspective_wrap.zones",
    "transformed_rect_width": 1000,
    "transformed_rect_height": 1000,
    "extend_perspective_polygon_by_detections_anchor": "CENTER",
    "warp_image": false
}