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

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
}