Cluster/core/nodes/__init__.py
2025-07-17 17:04:56 +08:00

58 lines
1.6 KiB
Python

"""
Node definitions for the Cluster4NPU pipeline system.
This package contains all node implementations for the ML pipeline system,
including input sources, preprocessing, model inference, postprocessing,
and output destinations.
Available Nodes:
- InputNode: Data source node (cameras, files, streams)
- PreprocessNode: Data preprocessing and transformation
- ModelNode: AI model inference operations
- PostprocessNode: Output processing and filtering
- OutputNode: Data sink and export operations
Usage:
from cluster4npu_ui.core.nodes import InputNode, ModelNode, OutputNode
# Create a simple pipeline
input_node = InputNode()
model_node = ModelNode()
output_node = OutputNode()
"""
from .base_node import BaseNodeWithProperties, create_node_property_widget
from .input_node import InputNode
from .preprocess_node import PreprocessNode
from .model_node import ModelNode
from .postprocess_node import PostprocessNode
from .output_node import OutputNode
# Available node types for UI registration
NODE_TYPES = {
'Input Node': InputNode,
'Preprocess Node': PreprocessNode,
'Model Node': ModelNode,
'Postprocess Node': PostprocessNode,
'Output Node': OutputNode
}
# Node categories for UI organization
NODE_CATEGORIES = {
'Data Sources': [InputNode],
'Processing': [PreprocessNode, PostprocessNode],
'Inference': [ModelNode],
'Output': [OutputNode]
}
__all__ = [
'BaseNodeWithProperties',
'create_node_property_widget',
'InputNode',
'PreprocessNode',
'ModelNode',
'PostprocessNode',
'OutputNode',
'NODE_TYPES',
'NODE_CATEGORIES'
]