Merge pull request #86 from asierarranz/main

Tutorial: First steps with MMJs

docs/tutorial_mmj.md

@@ -0,0 +1,199 @@
+# First steps with Metropolis Microservices for Jetson
+
+
+
+NVIDIA [Metropolis Microservices for Jetson](https://developer.nvidia.com/blog/announcing-metropolis-microservices-on-nvidia-jetson-orin-for-rapid-edge-ai-development/) simplifies the development of vision AI applications, offering a suite of customizable, cloud-native tools. Before diving into this tutorial, ensure you've filled out the Metropolis Microservices for Jetson [Early Access form](https://developer.nvidia.com/metropolis-microservices/jetson-application-form) to gain the necessary access to launch the services. This step is crucial as it enables you to utilize all the features and capabilities discussed in this guide.
+
+Perfect for both newcomers and experts, this tutorial provides straightforward steps to kick-start your edge AI projects. Whether you're a student or an ecosystem partner working on a use case, this guide offers a straightforward start for every skill level.
+
+![android2](./images/mmj_tutorial.gif)
+
+### 0. Install NVIDIA Jetson Services:
+
+Ok, let's start by installing NVIDIA Jetson Services:
+```
+sudo apt install nvidia-jetson-services
+```
+
+Let's add some performance hacks that will be needed to run the demo faster and without streaming artifacts:
+
+```
+sudo nvpmodel -m 0 
+sudo jetson_clocks
+```
+After these two commands, a reboot is needed if your Jetson wasn't already in high-performance mode.
+
+```
+sudo sysctl -w net.core.rmem_default=2129920
+sudo sysctl -w net.core.rmem_max=10000000
+sudo sysctl -w net.core.wmem_max=2000000
+
+```
+
+
+
+
+
+---
+
+### 1. Download NVIDIA CLI for Jetson
+
+Download NGC for ARM64 from: https://ngc.nvidia.com/setup/installers/cli
+```
+unzip ngccli_arm64.zip
+chmod u+x ngc-cli/ngc
+echo "export PATH=\"\$PATH:$(pwd)/ngc-cli\"" >> ~/.bash_profile && source ~/.bash_profile
+ngc config set
+```
+Here it will ask for your API Key, and the organization name, to get those you need to login into NGC and [generate an API key here](https://ngc.nvidia.com/setup/api-key).
+
+You should then paste the **API key** and use the **organization name** you are using. You can also press [Enter] to select the default values for the remaining options. After this, you should get the message:
+
+```
+Successfully saved NGC configuration to /home/jetson/.ngc/config
+```
+
+Then, login with the same API key:
+```
+sudo docker login nvcr.io -u "\$oauthtoken" -p <NGC-API-KEY>
+```
+
+Now launch the Redis and Ingress services, as we need them for this tutorial. 
+
+```
+sudo systemctl start jetson-redis
+sudo systemctl start jetson-ingress
+```
+
+---
+
+### 2. Download and launch NVStreamer
+### 
+
+First, we need to install NVStreamer, an app that streams the videos MMJs will need to run AI on them. Follow this [NVStreamer Link](https://registry.ngc.nvidia.com/orgs/e7ep4mig3lne/teams/release/resources/nvstreamer) (In the top-left, click Download files.zip)
+
+```
+unzip files.zip
+rm files.zip
+tar -xvf nvstreamer.tar.gz
+cd nvstreamer
+```
+Launch it:
+```
+sudo docker compose -f compose_nvstreamer.yaml up -d  --force-recreate
+```
+
+
+
+
+---
+
+### 3. Download AI_NVR and launch:
+### 
+[AI NVR (NGC) Link](https://registry.ngc.nvidia.com/orgs/e7ep4mig3lne/teams/release/resources/ai_nvr) (Top-left -> Download files.zip)
+
+```
+unzip files.zip
+rm files.zip
+tar -xvf ai_nvr.tar.gz
+sudo cp ai_nvr/config/ai-nvr-nginx.conf /opt/nvidia/jetson/services/ingress/config/
+cd ai_nvr
+sudo docker compose -f compose_agx.yaml up -d --force-recreate
+```
+
+
+
+
+
+
+
+### 4. Download some sample videos and upload them to NVStreamer
+
+Download them from [here](https://registry.ngc.nvidia.com/orgs/e7ep4mig3lne/teams/release/resources/sample-videos).
+
+```
+unzip files.zip
+```
+Ok, now, this is important to understand, there are **2 web interfaces**:
+1. The NVStream Streamer Dashboard, running in: http://localhost:31000
+2. The NVStreamer Camera Management Dashboard, running in: http://localhost:30080/vst
+
+So, first we need to upload the file in the Streamer interface, it looks like this:
+
+---
+
+![image1](./images/mmj_streamer.png)
+
+---
+
+
+There, go to **File Upload**, and drag and drop the file in the **upload squared area**.
+
+After uploading it, go to the Dashboad option of the left menu, and copy the **RTSP URL** of the video you just uploaded, you will need it for the Camera Management Dashboard.
+
+
+
+Now jump to the Camera Management Dashboard (http://localhost:30080/vst), it looks like this:
+
+
+
+---
+
+![image2](./images/mmj_vst.png)
+
+---
+
+
+Go to the **Camera Management** option of the menu, then use the **Add device manually** option, and paste the **RTSP URL**, add the name of your video to the **Name** and **Location** text boxes, so it will be displayed on top of the stream.
+
+
+
+Finally, click in the **Live Streams** option of the left menu, and you should be able to watch your video stream.
+
+---
+
+![video1](./images/mmj_livestream.gif)
+
+---
+
+### 5. Watch RTSP AI processed streaming from VLC
+
+Open VLC **from another computer** (localhost doesn't work here), and point to your Jetson Orin's IP address (you should be in the same network, or not having a firewal to access).
+
+The easiest way to get Jetson's ip is launching:
+```
+ifconfig
+```
+And checking the IP of the interface (usually wlan0, inet IP).
+
+Then go to **rtsp://[JETSON_IP]:8555/ds-test** using VLC like this:
+
+---
+
+![video2](./images/mmj_vlc.gif)
+
+
+---
+
+
+### 6. Android app
+
+There is an Android app that allows you to track events and create areas of interest to monitor, you can find it on Google Play as AI NVR.
+
+<img width="400px" src="./images/mmj_android.jpg">
+
+---
+
+
+Here is a quick walkthough where you can see how to:
+
+- Add the IP address of the Jetson
+- Track current events
+- Add new areas of interest
+- Add tripwire to track the flux and direction of events
+
+![android2](./images/mmj_app.gif)
+
+
+---
+

mkdocs.yml

@@ -102,6 +102,8 @@ nav:
     - Audio:
       - AudioCraft: tutorial_audiocraft.md
       - Whisper: tutorial_whisper.md
+    - Metropolis Microservices:
+      - First steps: tutorial_mmj.md
     # - Tools:
     #   - LangChain: tutorial_distillation.md
     - Tips: