mxpi_classpostprocessor

Function	Inherits the model postprocessing base class, which is used to postprocess the inference output tensor of a classification model.
Constraints	Currently, the upstream of the plugin can only be connected to the mxpi_tensorinfer inference plugin, and only MxpiTensorPackageList can be used as the metadata input. This plugin calls the object detection base class Process API of the mxBase repository to communicate and receive the return value of the ClassInfo data type.
Plugin Base Class (Factory)	mxpi_classpostprocessor
Input/Output	Input: buffer (data type: MxpiBuffer), metadata (data type: MxpiTensorPackageList) Output: buffer (data type: MxpiBuffer), metadata (data type: MxpiClassList)
Port Format (Caps)	Static input: {"metadata/tensor"} Static output: {"metadata/class"}
Property	For details, see Table 1 and Table 2.

Sample pipeline of the Python postprocessing plugin:

"mxpi_classpostprocessor0": {
        "props": {
                "funcLanguage":"python",
                "postProcessConfigPath": "../models/resnet50/resnet50_aipp_tf.cfg",
                "labelPath": "../models/resnet50/resnet50_clsidx_to_labels.names",
                "postProcessLibPath": "../../../python",
                "className":"Resnet50PostProcess",
                "pythonModule":"postprocess.post"
        },
        "factory": "mxpi_classpostprocessor",
        "next": "mxpi_dataserialize0"
},

Sample pipeline of the C++ postprocessing plugin:

"mxpi_classpostprocessor0": {
        "props": {
                "dataSource": "mxpi_tensorinfer0",
                "funcLanguage":"c++",
  "postProcessConfigPath": "../models/resnet50/resnet50_aipp_tf.cfg",
  "labelPath": "../models/resnet50/resnet50_clsidx_to_labels.names",
  "postProcessLibPath": "../../../lib/modelpostprocessors/libresnet50postprocess.so"
        },
        "factory": "mxpi_classpostprocessor", 
        "next": "mxpi_dataserialize0"
},

Parent topic: Model Postprocessing Plugins