An attribute that recognizes images using the dnn module from OpenCV. Minimum OpenCV version: 3.4.1 (while ROS Melodic comes with 3.2.0, Noetic is recommended) To use networks from other frameworks in this module, you do not need to install them.

Returns areas with objects recognized by CNN and having a probability not lower than Probability.

Not implemented

Not implemented

• Name (string, must be set) attribute unique name
• Type (string, must be "Dnn") attribute type
• Weight (double, default: 1) attribute weight
• Probability (double, default: 0.75) acceptable detection accuracy, used in Detect mode.
• Contour (bool, default: true) Returns the contour of the attribute if true.

• framework (string, must be set) Framework options available: darknet, tensorflow.
• weights (string, must be set) The path to the scale file. See the table below for more information.
• config (string, must be set) The path to the configuration file. See the table below for more information.
• labels (string, default: "") The path to the file with the names of the labels. Optional parameter, needed only if you need to fix the name of the object on the network.
• forceCuda (int, default: 0) For some computers (for example, the Jetson series), you need to set 1 to enable network acceleration using CUDA and cuDNN.
• inputWidth (int, default: 300) The width of the input image to the network. TODO: extract automatically from config
• inputHeight (int, default: 300) The height of the input image to the network. TODO: extract automatically from config
• additional_layers (string, default "") Names of additional layers added to output of the net. Basic only the last layer is proceed. Names must be separated with spaces.
• maskProbability (double, default: 0.75) Separated probability for mask nets.

<?xml version="1.0" ?>

<AttributeLib>

    <Attribute Name="COCO_Dnn" Type="Dnn" framework="tensorflow" weights="ssd_mobilenet_v1_coco_2017_11_17/frozen_inference_graph.pb" config="ssd_mobilenet_v1_coco_2017_11_17/config.pbtxt" labels="ssd_mobilenet_v1_coco_2017_11_17/mscoco_label_map.pbtxt" inputWidth="300" inputHeight="300" Probability="0.75"/>

</AttributeLib>

<SimpleObjectBase>  
    
    <SimpleObject Name="COCO_dnn_object" ID="60">              
        <Attribute Type="Detect">COCO_Dnn</Attribute>                    
    </SimpleObject>
    
</SimpleObjectBase>

How to use net with mask extraction

<Attribute Name="MRCNN" Type="Dnn" framework="tensorflow" weights="mask_rcnn_inception_v2_coco_2018_01_28/frozen_inference_graph.pb" config="mask_rcnn_inception_v2_coco_2018_01_28/mask_rcnn_inception_v2_coco_2018_01_28.pbtxt" labels="mask_rcnn_inception_v2_coco_2018_01_28/mscoco_label_map.pbtxt" inputWidth="300" inputHeight="300" Probability="0.3" forceCuda="1" additional_layers="detection_out_final" maskProbability="0.75"/>