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