Adds documentation from OpenDataCam

Closes #74

docs/00-index.md

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+---
+slug: /
+---
+
+# Introduction
+
+Welcome to the OpenDataCam Documentation.
+Below is a quickstart guide to get you started with OpenDataCam.
+Detailed information on installation options and configuration can be found in the respective subpages.
+
+## Quickstart
+
+The quickest way to get started with OpenDataCam is to use the existing Docker Images.
+
+### Pre-Requesits
+
+- You will need Docker and Docker-Compose installed. 
+- If you want to run OpenDataCam on a NVIDIA GPU you will additonally need
+  - [Nvidia CUDA 11 and cuDNN 8](https://developer.nvidia.com/cuda-downloads)
+  - [Nvidia Container toolkit installed](https://github.com/NVIDIA/nvidia-docker)
+  - You also need to install `nvidia-container-runtime`
+- To run OpenDataCam on a NVIDIA Jetson device you will need [Jetpack 5.x](https://developer.nvidia.com/embedded/jetpack-sdk-512).
+
+### Installation
+
+```bash
+# Download install script
+wget -N https://raw.githubusercontent.com/opendatacam/opendatacam/v3.0.2/docker/install-opendatacam.sh
+
+# Give exec permission
+chmod 777 install-opendatacam.sh
+
+# Note: You will be asked for sudo password when installing OpenDataCam
+
+# Install command for Jetson Nano
+./install-opendatacam.sh --platform nano
+
+# Install command for Jetson Xavier / Xavier NX
+./install-opendatacam.sh --platform xavier
+
+# Install command for a Laptop, Desktop or Server with NVIDIA GPU
+./install-opendatacam.sh --platform desktop
+```
+
+This command will download and start a docker container on the machine.
+After it finishes the docker container starts a webserver on port 8080 and run a demo video.
+
+:::note
+
+The docker container is started in auto-restart mode, so if you reboot your machine it will automaticaly start opendatacam on startup.
+To stop it run `docker-compose down` in the same folder as the install script.
+
+:::
+
+### Next Steps
+
+Now you can…
+
+- Drag'n'Drop a video file into the browser window to have OpenDataCam analzye this file
+- Change the [video input](/docs/configuration/#video-input) to run from a USB-Cam or other cameras
+- Use custom [neural network weigts](/docs/configuration/#use-custom-neural-network-weights)
+
+and much more. See [Configuration](/docs/configuration) for a full list of configuration options.
+
+## How accurate is OpenDataCam?
+
+Accuracy depends on which YOLO weights your hardware is capable of running.
+
+We are working on [adding a benchmark](https://github.com/opendatacam/opendatacam/issues/87) to rank OpenDataCam on the [MOT Challenge (Multiple Object Tracking Benchmark)](https://motchallenge.net/)
+
+## How fast is OpenDataCam?
+
+FPS depends on:
+
+- which hardware your are running OpenDataCam on
+- which YOLO weights you are using
+
+We made the default settings to run at least at 10 FPS on any Jetson.
+
+Learn more in the [Customize OpenDataCam documentation](documentation/CONFIG.md#Change-neural-network-weights)

docs/02-installation.md

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+# Installation
+
+- You will need Docker and Docker-Compose installed.
+- If you want to run OpenDataCam on a NVIDIA GPU you will additonally need
+  - [Nvidia CUDA 11 and cuDNN 8](https://developer.nvidia.com/cuda-downloads)
+  - [Nvidia Container toolkit installed](https://github.com/NVIDIA/nvidia-docker)
+  - You also need to install `nvidia-container-runtime`
+- To run OpenDataCam on a NVIDIA Jetson device you will need [Jetpack 5.x](https://developer.nvidia.com/embedded/jetpack-sdk-512).
+
+## As Docker Container (Recommended)
+
+This is the recommended way to install OpenDataCam.
+Follow the [Quickstart Guide](/docs/#quickstart)
+
+## Kubernetes
+
+If you prefer to deploy OpenDataCam on Kubernetes rather than with Docker Compose, use the `--orchestrator` flag for changing the engine.
+
+Apart from that, a Kubernetes distribution custom made for the embedded world would be [K3s](https://k3s.io/), which can be installed in 30 seconds by running:
+
+```bash
+curl -sfL https://get.k3s.io | sh -
+```
+
+Then, to automatically download and deploy the services:
+
+```bash
+# Download install script
+wget -N https://raw.githubusercontent.com/opendatacam/opendatacam/master/docker/install-opendatacam.sh
+
+# Give exec permission
+chmod 777 install-opendatacam.sh
+
+# Install command for Jetson Nano
+./install-opendatacam.sh --platform nano --orchestrator k8s
+
+# Install command for Jetson Xavier / Xavier NX
+./install-opendatacam.sh --platform xavier --orchestrator k8s
+
+# Install command for a Desktop machine
+./install-opendatacam.sh --platform desktop --orchestrator k8s
+```
+
+:::note
+NVIDIA offers a [Kubernetes device plugin](https://github.com/NVIDIA/k8s-device-plugin) for detecting GPUs on nodes in case you are managing a heterogeneous cluster.
+Support for Jetson boards is being worked [here](https://gitlab.com/nvidia/kubernetes/device-plugin/-/merge_requests/20)
+:::
+
+## Balena
+
+[![](https://www.balena.io/deploy.png)](https://dashboard.balena-cloud.com/deploy?repoUrl=https://github.com/balenalabs-incubator/opendatacam)
+
+If you have a fleet of one or more devices, you can use [balena](https://www.balena.io/) to streamline deployment and management of OpenDataCam.
+You can sign up for a free account [here](https://dashboard.balena-cloud.com/signup) and add up to ten devices at no charge.
+Use the button below to build OpenDataCam for a Jetson Nano, TX2, or Xavier.
+You can then download an image containing the OS, burn it to an SD card, and use balenaCloud to push OpenDataCam to your devices.
+
+You can learn more about this deployment option along with a step-by-step guide in this [recent blog post](https://www.balena.io/blog/using-opendatacam-and-balena-to-quantify-the-world-with-ai/), or [view a screencast](https://www.youtube.com/watch?v=YfRvUeSLi0M&t=44m45s) of the deployment in action.
+
+## Without Docker
+
+See [How to install OpenDataCam without docker](/docs/development/install-without-docker/)