century.sh
demonstrates detection on one video file source over multiple Hailo-8 devices, either using the Century platform, or other multi device configurations (i.e., multiple M.2 modules connected directly to the same host). While this application defaults to 4 devices, any number of Hailo-8 devices are supported.This pipeline runs the detection network Yolov5.
In this pipeline the decoding phase is accelerated by VA-API.
./century.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 to the console.--print-gst-launch
is a flag that prints the ready gst-launch command without running it--device-count
is an optional flag that sets the number of devices to use (default 4)
The app post process parameters can be configured by a json file located in $TAPPAS_WORKSPACE/apps/h8/gstreamer/general/century/resources/configs/yolov5.json
- 'yolov5m_wo_spp_60p' - https://github.com/hailo-ai/hailo_model_zoo/blob/master/hailo_model_zoo/cfg/networks/yolov5m_wo_spp_60p.yaml
cd $TAPPAS_WORKSPACE/apps/h8/gstreamer/general/century
./century.sh
The output should look like:
This app is based on our multi device pipeline template.
Note
It is recommended to first read the Retraining TAPPAS Models page.
You can use Retraining Dockers (available on Hailo Model Zoo), to replace the following models with ones that are trained on your own dataset:
yolov5m
- For optimum compatibility and performance with TAPPAS, use for compilation the corresponding YAML file from above.
- TAPPAS changes to replace model:
- Update HEF_PATH on the .sh file
- Update
resources/configs/yolov5.json
with your new post-processing parameters (NMS)