segmentation

Segmentation

Overview

Name	Implementation	Platforms	Model	ML engine	Backend	Features
example_segmentation_deeplab_v3_tflite.cpp	C++	i.MX 8M Plus i.MX 93	deeplab_v3_mnv2	TFLite	NPU (defaut) GPU CPU	multifilesrc gst-launch
example_segmentation_deeplab_v3_tflite.sh	Bash	i.MX 8M Plus i.MX 93	deeplab_v3_mnv2	TFLite	NPU (defaut) GPU CPU	multifilesrc gst-launch

NOTES:

• No GPU support on i.MX 93

Execution

Example script can be called from target console with no further restriction. For examples that support multiple backend, default value can be overriden by explicitly defining BACKEND variable, for instance:

Bash

$ BACKEND=CPU ./segmentation/example_segmentation_deeplab_v3_tflite.sh

C++

C++ example script needs to be generated with cross compilation. setup_environment.sh script needs to be executed in nxp-nnstreamer-examples folder to define data paths:

$ . ./tools/setup_environment.sh

It is possible to run the segmentation demo inference on three different hardwares:
Inference on NPU with the following script:

$ ./build/segmentation/example_segmentation_deeplab_v3_tflite -p ${DEEPLABV3_QUANT} -f ${PASCAL_IMAGES}

For i.MX 93 use vela converted model:

$ ./build/segmentation/example_segmentation_deeplab_v3_tflite -p ${DEEPLABV3_QUANT_VELA} -f ${PASCAL_IMAGES}

Inference on CPU with the following script:

$ ./build/segmentation/example_segmentation_deeplab_v3_tflite -p ${DEEPLABV3_QUANT} -f ${PASCAL_IMAGES} -b CPU

Quantized model is used for better inference performances on CPU.
NOTE: inferences on i.MX8MPlus GPU have low performances, but are possible with the following script:

$ ./build/segmentation/example_segmentation_deeplab_v3_tflite -p ${DEEPLABV3} -f ${PASCAL_IMAGES} -b GPU -n centeredReduced

The following execution parameters are available (Run ./example_segmentation_deeplab_v3_tflite -h to see option details):

Option	Description
-b, --backend	Use the selected backend (CPU, GPU, NPU) default: NPU
-n, --normalization	Use the selected normalization (none, centered, reduced, centeredReduced, castInt32, castuInt8) default: none
-p, --model_path	Use the selected model path
-f, --images_file	Use the selected images file
-d, --display_perf	Display performances, can specify time or freq
-t, --text_color	Color of performances displayed, can choose between red, green, blue, and black (white by default)
-g, --graph_path	Path to store the result of the OpenVX graph compilation (only for i.MX8MPlus)

Press Esc or ctrl+C to stop the execution of the pipeline.