Dominant Color¶
Extract the dominant color from an input image using K-means clustering.
This block identifies the most prevalent color in an image. Processing time is dependant on color complexity and image size. Most images should complete in under half a second.
The output is a list of RGB values representing the dominant color, making it easy to use in further processing or visualization tasks.
Note: The block operates on the assumption that the input image is in RGB format.
Type identifier¶
Use the following identifier in step "type" field: roboflow_core/dominant_color@v1to add the block as
as step in your workflow.
Properties¶
| Name | Type | Description | Refs |
|---|---|---|---|
name |
str |
Enter a unique identifier for this step.. | ❌ |
color_clusters |
int |
Number of dominant colors to identify. Higher values increase precision but may slow processing.. | ✅ |
max_iterations |
int |
Max number of iterations to perform. Higher values increase precision but may slow processing.. | ✅ |
target_size |
int |
Sets target for the smallest dimension of the downsampled image in pixels. Lower values increase speed but may reduce precision.. | ✅ |
The Refs column marks possibility to parametrise the property with dynamic values available
in workflow runtime. See Bindings for more info.
Available Connections¶
Check what blocks you can connect to Dominant Color in version v1.
- inputs:
Reference Path Visualization,Label Visualization,Line Counter,Polygon Zone Visualization,Pixel Color Count,Stability AI Inpainting,Triangle Visualization,Absolute Static Crop,Trace Visualization,Halo Visualization,Ellipse Visualization,SIFT,SIFT Comparison,Pixelate Visualization,Image Blur,Dot Visualization,Model Comparison Visualization,Classification Label Visualization,SIFT Comparison,Dynamic Crop,Image Slicer,Mask Visualization,Perspective Correction,Background Color Visualization,Crop Visualization,Grid Visualization,Relative Static Crop,Line Counter Visualization,Image Convert Grayscale,Image Contours,Stitch Images,Blur Visualization,Image Threshold,Color Visualization,Image Preprocessing,Template Matching,Polygon Visualization,Distance Measurement,Circle Visualization,Camera Focus,Line Counter,Bounding Box Visualization,Corner Visualization,Keypoint Visualization - outputs:
Pixel Color Count,Dynamic Crop
Input and Output Bindings¶
The available connections depend on its binding kinds. Check what binding kinds
Dominant Color in version v1 has.
Bindings
-
input
image(image): The input image for this step..color_clusters(integer): Number of dominant colors to identify. Higher values increase precision but may slow processing..max_iterations(integer): Max number of iterations to perform. Higher values increase precision but may slow processing..target_size(integer): Sets target for the smallest dimension of the downsampled image in pixels. Lower values increase speed but may reduce precision..
-
output
rgb_color(rgb_color): RGB color.
Example JSON definition of step Dominant Color in version v1
{
"name": "<your_step_name_here>",
"type": "roboflow_core/dominant_color@v1",
"image": "$inputs.image",
"color_clusters": 4,
"max_iterations": 100,
"target_size": 100
}