Do classification with deep neural networks based on bounding boxes.

The filter accepts the following options:

dnn_backend

Specify which DNN backend to use for model loading and execution. This option accepts only openvino now, tensorflow backends will be added.

model

Set path to model file specifying network architecture and its parameters. Note that different backends use different file formats.

input

Set the input name of the dnn network.

output

Set the output name of the dnn network.

confidence

Set the confidence threshold (default: 0.5).

labels

Set path to label file specifying the mapping between label id and name. Each label name is written in one line, tailing spaces and empty lines are skipped. The first line is the name of label id 0, and the second line is the name of label id 1, etc. The label id is considered as name if the label file is not provided.

backend_configs

Set the configs to be passed into backend

For tensorflow backend, you can set its configs with sess_config options, please use tools/python/tf_sess_config.py to get the configs for your system.