ONNXDetectorProvider

Documentation

• Class name: ONNXDetectorProvider
• Category: ImpactPack
• Output node: False

The ONNXDetectorProvider node is designed to load and provide access to ONNX models for object detection. It serves as a bridge between the ONNX model files and the detection functionality, enabling the use of pre-trained ONNX models for detecting objects within images.

Input types

Required

• model_name
  • Specifies the name of the ONNX model to be loaded. This parameter is crucial for identifying and accessing the correct model file for object detection.
  • Comfy dtype: COMBO[STRING]
  • Python dtype: List[str]

Output types

• bbox_detector
  • Comfy dtype: BBOX_DETECTOR
  • Provides an object detector initialized with the specified ONNX model. This detector is capable of identifying bounding boxes around objects within images.
  • Python dtype: core.ONNXDetector

Usage tips

• Infra type: CPU
• Common nodes: unknown

Source code

class ONNXDetectorProvider:
    @classmethod
    def INPUT_TYPES(s):
        return {"required": {"model_name": (folder_paths.get_filename_list("onnx"), )}}

    RETURN_TYPES = ("BBOX_DETECTOR", )
    FUNCTION = "load_onnx"

    CATEGORY = "ImpactPack"

    def load_onnx(self, model_name):
        model = folder_paths.get_full_path("onnx", model_name)
        return (core.ONNXDetector(model), )