# edge-video-analytics-microservice

**Repository Path**: mirrors_intel/edge-video-analytics-microservice

## Basic Information

- **Project Name**: edge-video-analytics-microservice
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: MIT
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2022-02-18
- **Last Updated**: 2025-11-01

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# Contents

- [Contents](#contents)
  - [Edge Video Analytics Microservice](#edge-video-analytics-microservice)
    - [Build the Base Image](#build-the-base-image)
    - [Run the Base Image](#run-the-base-image)
    - [Run EVAM in Open EII Mode](#run-evam-in-open-eii-mode)

## Edge Video Analytics Microservice

This repository contains the source code for Edge Video Analytics Microservice (EVAM) used for the [Video Analytics Use Case](https://www.intel.com/content/www/us/en/developer/articles/technical/video-analytics-service.html). For information on how to build the use case, refer to the [Get Started](https://www.intel.com/content/www/us/en/developer/articles/technical/video-analytics-service.html#inpage-nav-3) guide.

### Build the Base Image

Complete the following steps to build the base image:

1. Run the following command:
  
   ```sh
     `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](https://hub.docker.com/r/intel/edge_video_analytics_microservice).

### Run the Base Image

Complete the following steps to run the base image:

1. Clone this [repo](https://github.com/intel/edge-video-analytics-microservice).
2. Run the following command to make the following files executable:

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

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

   ```sh
   ./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:

   ```json
    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.

   ```sh
    - 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](https://www.intel.com/content/www/us/en/developer/articles/technical/video-analytics-service.html#inpage-nav-3-1).

### Run EVAM in Open EII Mode

To run EVAM in the Open EII mode, refer to the [README](eii/README.md).