Image Convert Grayscale

Class: ConvertGrayscaleBlockV1

Source: inference.core.workflows.core_steps.classical_cv.convert_grayscale.v1.ConvertGrayscaleBlockV1

Block to convert an RGB image to grayscale. The output image will have only one channel.

Type identifier

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

Properties

Name	Type	Description	Refs
name	str	Enter a unique identifier for this step..	❌

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 Image Convert Grayscale in version v1.

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

Input and Output Bindings

The available connections depend on its binding kinds. Check what binding kinds Image Convert Grayscale in version v1 has.

Bindings

• input

  • image (image): The input image for this step..

• output

  • image (image): Image in workflows.

Example JSON definition of step Image Convert Grayscale in version v1

{
    "name": "<your_step_name_here>",
    "type": "roboflow_core/convert_grayscale@v1",
    "image": "$inputs.image"
}