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

Prerequisites#

Model preparation: Python 3.9 or higher with pip

Model Server deployment: Installed Docker Engine or OVMS binary package according to the baremetal deployment guide

Prepare models#

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

curl https://storage.googleapis.com/mediapipe-assets/face_detection_short_range.tflite -o face_detection_short_range/1/face_detection_short_range.tflite --create-dirs
curl https://storage.googleapis.com/mediapipe-assets/face_landmark.tflite -o face_landmark/1/face_landmark.tflite --create-dirs
curl https://storage.googleapis.com/mediapipe-assets/iris_landmark.tflite -o iris_landmark/1/iris_landmark.tflite --create-dirs

Server Deployment#

Deploying with Docker

Pull the latest version of OpenVINO™ Model Server from Docker Hub:

docker pull openvino/model_server:latest

docker run -d -v $PWD/mediapipe:/mediapipe -v $PWD:/models -p 9000:9000 openvino/model_server:latest --config_path /models/config_iris.json --port 9000
Deploying on Bare Metal

Assuming you have unpacked model server package, make sure to:

  • On Windows: run setupvars script

  • On Linux: set LD_LIBRARY_PATH and PATH environment variables

as mentioned in deployment guide, in every new shell that will start OpenVINO Model Server.

cd demos\mediapipe\iris_tracking
ovms --config_path 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/main/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

Output image#

output