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Running Advance demos

The same Python and C++ demo applications can be used to run multiple inference models and also work with multiple inputs with just simple changes in the config file.

From a repo of input sources, output sources and models one can define advance dataflows which connect them in various configurations. Details on configuration file parameters can be found in pub_edgeai_configuration

Single input multi inference demo

Here is an example of a single-input, multi-inference demo which takes a camera input and run multiple networks on each of them.

debian@beaglebone:/opt/edge_ai_apps/apps_python# ./app_edgeai.py ../configs/single_input_multi_infer.yaml

Sample output for single input, multi inference demo is as shown below,

Fig. 79 Sample output showing single input, mutli-inference output

We can specify the output window location and sizes as shown in the configuration file,

flows:
    flow0:
        input: input0
        models: [model0, model1, model2, model3]
        outputs: [output0, output0, output0, output0]
        mosaic:
            mosaic0:
                width:  800
                height: 450
                pos_x:  160
                pos_y:  90
            mosaic1:
                width:  800
                height: 450
                pos_x:  960
                pos_y:  90
            mosaic2:
                width:  800
                height: 450
                pos_x:  160
                pos_y:  540
            mosaic3:
                width:  800
                height: 450
                pos_x:  960
                pos_y:  540

Multi input multi inference demo

Here is an example of a multi-input, multi-inference demo which takes a camera input and video input and runs multiple networks on each of them.

debian@beaglebone:/opt/edge_ai_apps/apps_python# ./app_edgeai.py ../configs/multi_input_multi_infer.yaml

Sample output for multi input, multi inference demo is as shown below,

Fig. 80 Sample output showing multi-input, mutli-inference output

We can specify the output window location and sizes as shown in the configuration file,

flows:
    flow0:
        input: input0
        models: [model1, model2]
        outputs: [output0, output0]
        mosaic:
            mosaic0:
                width:  800
                height: 450
                pos_x:  160
                pos_y:  90
            mosaic1:
                width:  800
                height: 450
                pos_x:  960
                pos_y:  90
    flow1:
        input: input1
        models: [model0, model3]
        outputs: [output0, output0]
        mosaic:
            mosaic0:
                width:  800
                height: 450
                pos_x:  160
                pos_y:  540
            mosaic1:
                width:  800
                height: 450
                pos_x:  960
                pos_y:  540