Contents

• Contents
  • Edge Video Analytics Microservice
    • Build the base image
    • Run the base image
    • Run EVAM in OEI mode

Edge Video Analytics Microservice

This repository contains the source code for Edge Video Analytics Microservice (EVAM) used for the Video Analytics Use Case. For information on how to build the use case, refer to the Get Started guide.

Build the base image

Complete the following steps to build the base image:

1. Run the following command:

     `docker-compose -f  docker-compose-build.yml  build`

2. If required, download the pre-built container image for Edge Video Analytics Microservice from Docker Hub.

Run the base image

Complete the following steps to run the base image:

1. Clone this repo.

2. Run the following command to make the following files executable:

    chmod +x tools/model_downloader/model_downloader.sh docker/run.sh

3. Download the required models. From the cloned repo, run the following command:

   ./tools/model_downloader/model_downloader.sh  --model-list <Path to model-list.yml>

4. After downloading the models, you will have the models directory in the base folder. Refer to the following:

    models/
    ├── action_recognition
    ├── audio_detection
    ├── emotion_recognition
    ├── face_detection_retail
    ├── object_classification
    └── object_detection

5. Add the following lines in the docker-compose.yml environment if you are behind a proxy.

    - HTTP_PROXY=<IP>:<Port>/
    - HTTPS_PROXY=<IP>:<Port>/
    - NO_PROXY=localhost,127.0.0.1

6. Run the sudo docker-compose up command.

Note: For more details, refer to Run the Edge Video Analytics Microservice.

Run EVAM in OEI mode

To run EVAM in the OEI mode, refer to the README.