README.rst

Instance Segmentation Pipeline

Overview

instance_segmentation.sh demonstrates instance segmentation on one video file source and verifies Hailo’s configuration.

This is done by running a single-stream instance segmentation pipeline on top of GStreamer using the Hailo-8 device.

Options

./instance_segmentation.sh [--input FILL-ME]

• --input is an optional flag, a path to the video displayed (default is detection.mp4).
• --show-fps is an optional flag that enables printing FPS on screen.
• --print-gst-launch is a flag that prints the ready gst-launch command without running it.

Run

cd $TAPPAS_WORKSPACE/apps/h8/gstreamer/general/instance_segmentation
./instance_segmentation.sh

The output should display as:

Model

• yolov5n_seg - https://github.com/hailo-ai/hailo_model_zoo/blob/master/hailo_model_zoo/cfg/networks/yolov5n_seg.yaml

Method of Operation

This app is based on the single network pipeline template

Using Retraining to Replace Models

Note

It is recommended to first read the Retraining TAPPAS Models page.

Retraining Dockers (available on Hailo Model Zoo), can be used to replace the following models with ones that are trained on your own dataset:

• yolov5n_seg
  • No retraining docker is available.
  • Post process CPP file edit update post-processing:
    • Update yolov5seg.cpp with your new parameters, then recompile to create libyolov5seg_post.so