# Getting Started with Intel® SceneScape

-   **Time to Complete:** 30-45 minutes

## Get Started

### Prerequisites

* To run and interact with the demo scenes that the Intel® SceneScape release package provides, one computer is needed. The ./deploy.sh script has been tested to work with Ubuntu* 22.04 Desktop.
* The computer must be at least a 10th Generation Intel® Core™ i5 Processor or Intel® Xeon® Scalable processor, with at least 8+GB of RAM and 64+GB of storage. This configuration is the minimum to run the out of the box demos and more compute resources maybe be required for additional models, cameras, and/or sensors.
* For the initial build of the ./deploy.sh process the computer must have a correctly configured connection to the Internet for acquiring the needed build tools. When using a proxy, the proxy will need to be correctly configured for the console environment, OS package installer, and Docker*. Deployed containers can run without an internet connection.
* When deploying a live scene, a scale floor plan of the scene is needed either in a 3D scene scan in .glb format or in a 2D web image format (JPG, PNG, or GIF) that is about 600 to 1000 pixels wide. Walls and fiducial markers on the floor plan must be at least twice as accurate as the desired tracking accuracy (e.g. accuracy < 1 meter requires a floor plan accurate to < 0.5 meters).
* It is not recommended to initially use a virtual machine. Once Intel® SceneScape is configured for a specific use case and the system resource requirements are understood, then a multicore VM could be configured for deployment and execution. Windows Subsystem for Linux* (WSL) is not supported.

### Step 1: Install OS

Follow this tutorial to download Ubuntu 22.04 and install it on the target computer selecting the minimal installation option and to erase the disk and install Ubuntu: https://ubuntu.com/tutorials/install-ubuntu-desktop
After the install be sure to update the system software before proceeding.
```console
sudo apt update
```

### Step 2: Clone the Intel® SceneScape source code

**Note:** These operations must be executed when logged in as a standard (non-root) user. **Do NOT use root or sudo.**

  ```bash
  git clone https://github.com/open-edge-platform/scenescape/
  cd scenescape
  ```

  Optionally, checkout a specific version, if required, e.g.:

  ```bash
  git checkout v1.3.0
  ```

### Step 3: Build Intel® SceneScape container images

Build container images:

  ```bash
  make
  ```

The build may take around 15 minutes depending on target machine.
This step generates common base docker image and docker images for all microservices.

By default, a parallel build is being run with the number of jobs equal to the number of processors in the system.
Optionally, the number of jobs can be adjusted with `JOBS` environment variable, e.g. to achieve sequential building:

  ```bash
  make JOBS=1
  ```

### Step 4 (Optional): Build dependency list of Intel® SceneScape container images

  ```bash
  make list-dependencies
  ```

This step generates dependency lists. Two separate files are created for system packages and Python packages per each microservice image.

### Step 5: Deploy Intel® SceneScape demo to the target system

Before deploying the demo of Intel® SceneScape for the first time, please set the environment variable SUPASS with the super user password for logging into Intel® SceneScape.
Important: This should be different than the password for your system user.

  ```bash
  export SUPASS=<password>
  ```

  ```bash
  make demo
  ```

### Step 6: Verify a successful deployment

If you are running remotely, connect using ```"https://<ip_address>"``` or ```"https://<hostname>"```, using the correct IP address or hostname of the remote Intel® SceneScape system. If accessing on a local system use ```"https://localhost"```. If you see a certificate warning, click the prompts to continue to the site. For example, in Chrome click "Advanced" and then "Proceed to &lt;ip_address> (unsafe)".

> **Note:** These certificate warnings are expected due to the use of a self-signed certificate for initial deployment purposes. This certificate is generated at deploy time and is unique to the instance.

### Logging In
Enter "admin" for the user name and the value you typed earlier for SUPASS.

### Stopping the System

To stop the containers, use the following command in the project directory:

```console
$ docker compose down --remove-orphans
```
### Starting the System

To start after the first time, use the following command in the project directory:

```console
$ docker compose up -d
```

## Summary

Intel® SceneScape was downloaded, built and deployed onto a fresh Ubuntu 22.04 system. Using the web user interface, Intel® SceneScape provides two scenes by default that can be explored running from stored video data.
![SceneScape WebUI Homepage](images/homepage.png)
* **Note** the “Documentation” menu option, click to view the Intel® SceneScape HTML version of the documentation in the browser.

## Next Steps
- **How to enable reidentification**
  - [How to enable reidentification](How-to-enable-reidentification.md): Step-by-step guide to enable reidentification.

- **How to use sensor types**
  - [How to use Sensor types](How-to-use-sensor-types.md): Step-by-step guide to getting started with sensor types.

- **How to use 3D UI**
  - [How to use 3D UI](How-to-use-3D-UI.md): A guide on how use 3D UI

- **How to create a Geti trained AI models and integrate it with Intel® SceneScape.**
  - [Geti AI model integration](How-to-integrate-geti-trained-model.md): Step-by-step guide for integrating a Geti trained AI model with Intel® SceneScape.

- **How to visualize regions**
  - [How to visualize regions](How-to-visualize-regions.md): Step-by-step guide to getting started with visualizing regions.

- **How to configure a hierarchy of scenes**
  - [How to configure a hierarchy of scenes](How-to-configure-a-hierarchy-of-scenes.md): Step-by-step guide to configuring a hierarchy of scenes.

- **How to manually calibrate cameras**
  - [How to manually calibrate cameras](How-to-manually-calibrate-cameras.md): Step-by-step guide to performing Manual Camera Calibration.

- **How to autocalibrate cameras using visual features**
  - [How to autocalibrate cameras using visual features](How-to-autocalibrate-cameras-using-visual-features.md): Step-by-step guide to performing Auto Camera Calibration using Visual Features.

- **How to autocalibrate cameras using Apriltags**
  - [How to autocalibrate cameras using Apriltags](How-to-autocalibrate-cameras-using-apriltags.md): Step-by-step guide to performing Auto Camera Calibration using Apriltags.

- **How to upgrade Intel® SceneScape**
  - [How to upgrade Intel Scenescape](How-to-upgrade.md): Step-by-step guide for upgrading from an older version of Intel® SceneScape.

- **How to inference using Nvidia GPU with OVMS**
  - [How to inference using Nvidia GPU with OVMS](How-to-inference-using-Nvidia-gpu-with-OVMS.md): Step-by-step guide for enabling inference on Nvidia GPU using OVMS.

## Learn More

-   Understand the components, services, architecture, and data flow, in
    the [Overview](Overview.md).
-   Follow examples to become familiar with the core functionality of Intel® SceneScape, in
    [Tutorial](Tutorial.md).
-   Optimizing security posture for a Intel® SceneScape installation [Hardening Guide for Custom TLS](hardening-guide.md)