🖼️ Execution Node
Execution Nodes represent individual steps in an image processing workflow.
Overview
The ExecutionNode class represents a single step in an image processing workflow. You can think of an Execution Node as containing two main attributes: IMAGE and DATA.
All Execution Nodes have a unique id.
Attributes
The input image at this step of the workflow.
The data resulting from processing the image. This could be text, a Detections object, or a Pydantic object.
The detections from the previous step that led to this node.
Note: This attribute operates behind the scenes to assist with splits and joins.
The unique identifier of the node.
Methods
Returns:
[PIL.Image.Image]: Generates a visual representation of the node. If the data in the node are Detections, it annotates the image with the detections. Otherwise, it displays the data as text on the image.
🖼️ Execution Node
Execution Nodes represent individual steps in an image processing workflow.
Overview
The ExecutionNode class represents a single step in an image processing workflow. You can think of an Execution Node as containing two main attributes: IMAGE and DATA.
All Execution Nodes have a unique id.
Attributes
The input image at this step of the workflow.
The data resulting from processing the image. This could be text, a Detections object, or a Pydantic object.
The detections from the previous step that led to this node.
Note: This attribute operates behind the scenes to assist with splits and joins.
The unique identifier of the node.
Methods
Returns:
[PIL.Image.Image]: Generates a visual representation of the node. If the data in the node are Detections, it annotates the image with the detections. Otherwise, it displays the data as text on the image.