Dominant Color¶
Version v1¶
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 |
The unique name of 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:
Label Visualization,Crop Visualization,Mask Visualization,Blur Visualization,Image Contours,Bounding Box Visualization,Image Convert Grayscale,Camera Focus,Dot Visualization,Color Visualization,Corner Visualization,Circle Visualization,Perspective Correction,Image Slicer,Triangle Visualization,Relative Static Crop,Absolute Static Crop,Halo Visualization,Background Color Visualization,SIFT,Pixelate Visualization,Polygon Visualization,Dynamic Crop,Image Blur,Ellipse Visualization,Image Threshold - outputs:
Pixel Color Count
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
}