MediaPipe Iris Demo#
This guide shows how to implement MediaPipe graph using OVMS.
Example usage of graph that accepts Mediapipe::ImageFrame as a input:
The demo is based on the Mediapipe Iris demo
Prepare the server deployment#
Clone the repository and enter mediapipe object_detection directory
git clone https://github.com/openvinotoolkit/model_server.git
cd model_server/demos/mediapipe/iris_tracking
./prepare_server.sh
Pull the Latest Model Server Image#
Pull the latest version of OpenVINO™ Model Server from Docker Hub:
docker pull openvino/model_server:latest
Run OpenVINO Model Server#
docker run -d -v $PWD/mediapipe:/mediapipe -v $PWD/ovms:/models -p 9000:9000 openvino/model_server:latest --config_path /models/config_iris.json --port 9000
Run client application for iris tracking#
pip install -r requirements.txt
# download a sample image for analysis
wget https://raw.githubusercontent.com/openvinotoolkit/model_server/releases/2024/4/demos/common/static/images/people/people2.jpeg
echo "people2.jpeg" > input_images.txt
# launch the client
python mediapipe_iris_tracking.py --grpc_port 9000 --images_list input_images.txt
Running demo application.
Start processing:
Graph name: irisTracking
(800, 1200, 3)
Iteration 0; Processing time: 44.73 ms; speed 22.36 fps
Results saved to :image_0.jpg