README.rst

Python Classification Pipeline

Classification

The purpose of classification.sh is to demonstrate classification on one video file source with python post-processing by running a single-stream object classification pipeline on top of GStreamer using the Hailo-8 device.

Options

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

• --input is an optional flag, a path to the video displayed (default is classification_movie.mp4).
• --show-fps is a flag that prints the pipeline's fps to the screen.
• --print-gst-launch is a flag that prints the ready gst-launch command without running it.

Supported Networks

• 'resnet_v1_50' - https://github.com/hailo-ai/hailo_model_zoo/blob/master/hailo_model_zoo/cfg/networks/resnet_v1_50.yaml

Run

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

Model

• resnet_v1_50: https://github.com/hailo-ai/hailo_model_zoo/blob/master/hailo_model_zoo/cfg/networks/resnet_v1_50.yaml

Method of Operation

This app is based on single network pipeline template With a slight modification, instead of using hailofilter for post-process, hailopython is used.