Stitch Images

Class: StitchImagesBlockV1

Source: inference.core.workflows.core_steps.transformations.stitch_images.v1.StitchImagesBlockV1

This block combines two related scenes both containing fair amount of details. Block is utilizing Scale Invariant Feature Transform (SIFT)

Type identifier

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

Properties

Name	Type	Description	Refs
name	str	Enter a unique identifier for this step..	❌
max_allowed_reprojection_error	float	Advanced parameter overwriting cv.findHomography ransacReprojThreshold parameter. Maximum allowed reprojection error to treat a point pair as an inlier. Increasing value of this parameter for low details photo may yield better results..	✅
count_of_best_matches_per_query_descriptor	int	Advanced parameter overwriting cv.BFMatcher.knnMatch k parameter. Count of best matches found per each query descriptor or less if a query descriptor has less than k possible matches in total..	✅

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 Stitch Images in version v1.

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

Input and Output Bindings

The available connections depend on its binding kinds. Check what binding kinds Stitch Images in version v1 has.

Bindings

• input

  • image1 (image): First input image for this step..
  • image2 (image): Second input image for this step..
  • max_allowed_reprojection_error (float_zero_to_one): Advanced parameter overwriting cv.findHomography ransacReprojThreshold parameter. Maximum allowed reprojection error to treat a point pair as an inlier. Increasing value of this parameter for low details photo may yield better results..
  • count_of_best_matches_per_query_descriptor (integer): Advanced parameter overwriting cv.BFMatcher.knnMatch k parameter. Count of best matches found per each query descriptor or less if a query descriptor has less than k possible matches in total..

• output

  • stitched_image (image): Image in workflows.

Example JSON definition of step Stitch Images in version v1

{
    "name": "<your_step_name_here>",
    "type": "roboflow_core/stitch_images@v1",
    "image1": "$inputs.image1",
    "image2": "$inputs.image2",
    "max_allowed_reprojection_error": 3,
    "count_of_best_matches_per_query_descriptor": 2
}