Camera Calibration

Class: CameraCalibrationBlockV1

Source: inference.core.workflows.core_steps.transformations.camera_calibration.v1.CameraCalibrationBlockV1

This block uses the OpenCV calibrateCamera function to remove lens distortions from an image. Please refer to OpenCV documentation where camera calibration methodology is described: https://docs.opencv.org/4.x/dc/dbb/tutorial_py_calibration.html

This block requires following parameters in order to perform the calibration: Lens focal length along the x-axis and y-axis (fx, fy) Lens optical centers along the x-axis and y-axis (cx, cy) Radial distortion coefficients (k1, k2, k3) Tangential distortion coefficients (p1, p2)

Based on above parameters, camera matrix will be built as follows: [[fx 0 cx][ 0 fy cy] [ 0 0 1 ]]

Distortions coefficient will be passed as 5-tuple (k1, k2, p1, p2, k3)

Type identifier

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

Properties

Name	Type	Description	Refs
name	str	Enter a unique identifier for this step..	❌
fx	float	Focal length along the x-axis.	✅
fy	float	Focal length along the y-axis.	✅
cx	float	Optical center along the x-axis.	✅
cy	float	Optical center along the y-axis.	✅
k1	float	Radial distortion coefficient k1.	✅
k2	float	Radial distortion coefficient k2.	✅
k3	float	Radial distortion coefficient k3.	✅
p1	float	Distortion coefficient p1.	✅
p2	float	Distortion coefficient p2.	✅

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 Camera Calibration in version v1.

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

Input and Output Bindings

The available connections depend on its binding kinds. Check what binding kinds Camera Calibration in version v1 has.

Bindings

• input

  • image (image): Image to remove distortions from.
  • fx (float): Focal length along the x-axis.
  • fy (float): Focal length along the y-axis.
  • cx (float): Optical center along the x-axis.
  • cy (float): Optical center along the y-axis.
  • k1 (float): Radial distortion coefficient k1.
  • k2 (float): Radial distortion coefficient k2.
  • k3 (float): Radial distortion coefficient k3.
  • p1 (float): Distortion coefficient p1.
  • p2 (float): Distortion coefficient p2.

• output

  • calibrated_image (image): Image in workflows.

Example JSON definition of step Camera Calibration in version v1

{
    "name": "<your_step_name_here>",
    "type": "roboflow_core/camera-calibration@v1",
    "image": "$inputs.image",
    "fx": 0.123,
    "fy": 0.123,
    "cx": 0.123,
    "cy": 0.123,
    "k1": 0.123,
    "k2": 0.123,
    "k3": 0.123,
    "p1": 0.123,
    "p2": 0.123
}