Echo your face detection with the SFU ExWebRTC and “mediaPipe”
Mix.install([
{:kino, "~> 0.13.1"},
{:ex_webrtc, "~> 0.3.0"},
{:req, "~> 0.5.2"}
])What are we doing?
We illustrate the SFU server ExWebRTC by broadcasting our webcam via WebRTC.
ExWebRTC is an Elixir port of the WebRTC API.
This is a low latency protocole running on UDP.
By SFU, we mean that we forward the WebRTC signals via a server running Elixir code. We are not using the “standard” peer-to-peer WebRTC connection.
In this demo, we transform the feed directly in the browser. Since it is mandatory to start with the “hello world” of computer vision - face detection - , we use the library
mediaPipe
.
You will notice that the results are pretty good!
The transformed stream will be sent to the SFU server. We broadcast it back in another element. ## The WebRTC flow without the face detection addition The webcam is captured and displayed in a first `` element. The browser and the Elixir SFU will establish a WebRTC PeerConnection via a signaling channel: the Livebook WebSocket. They will exchange SDP and ICE candidates. Once connected, the Elixir SFU will receive the streams from the `` via a UDP connection. In this Echo configuration, it will send back the streams to the connected peer via UDP and display them in the other `` element. ### Information flow - The signaling process (instantiate the PeerConnection): ```mermaid graph LR; B1[Browser ExWebRTC.PeerConnection
PeerConnection]-- ws-->L[Livebook]; L-- ws -->Ex[Elixir SFU
PeerConnection]; Ex -- ws --> L L -- ws --> B1 ``` - The active connection: ```mermaid graph LR; B3[video 1]--stream
UDP -->ExSFU[Elixir SFU] ExSFU --stream
UPD-->B4[video 2]; ``` ### Server-side WebRTC module ```elixir defmodule RtcServer do use GenServer alias ExWebRTC.{ICECandidate, PeerConnection, SessionDescription, MediaStreamTrack, RTPCodecParameters} alias ExWebRTC.RTP.VP8.Depayloader require Logger defp ice_servers(), do: [%{urls: "stun:stun.l.google.com:19302"}] defp video_codecs, do: [ %RTPCodecParameters{ payload_type: 96, mime_type: "video/VP8", clock_rate: 90_000 } ] defp setup_transceivers(pc) do media_stream_id = MediaStreamTrack.generate_stream_id() video_track = MediaStreamTrack.new(:video, [media_stream_id]) {:ok, _sender} = PeerConnection.add_track(pc, video_track) %{serv_video_track: video_track} end # public ---------------- def start_link(args), do: GenServer.start_link(__MODULE__, args, name: __MODULE__) def connect, do: GenServer.call(__MODULE__, :connect) def receive_signaling_msg({msg, sender}) do GenServer.cast(__MODULE__, {:receive_signaling_msg, msg, sender}) end def peek_state, do: GenServer.call(__MODULE__, :peek_state) # callbacks------------------------- @impl true def init(_args) do Logger.info("ExRtc PeerConnection started") {:ok, %{ sender: nil, pc: nil, client_video_track: nil, video_depayloader: Depayloader.new(), i: 1, t: System.monotonic_time(:microsecond) }} end # Livebook calls @impl true def handle_call(:peek_state, _, state) do {:reply, state, state} end def handle_call(:connect, _, state) do {:ok, pc_pid} = PeerConnection.start_link(ice_servers: ice_servers(), video_codecs: video_codecs()) state = %{state | pc: pc_pid} |> Map.merge(setup_transceivers(pc_pid)) {:reply, :connected, state} end # messages received from the client @impl true def handle_cast({:receive_signaling_msg, %{"type"=> "offer"} = msg, sender},state) do with desc <- SessionDescription.from_json(msg), :ok <- PeerConnection.set_remote_description(state.pc, desc), {:ok, answer} <- PeerConnection.create_answer(state.pc), :ok <- PeerConnection.set_local_description(state.pc, answer), :ok <- gather_candidates(state.pc) do # the 'answer' is formatted into a struct, which can't be read by the JS client answer = %{"type" => "answer", "sdp" => answer.sdp} send(sender, {:signaling, answer}) Logger.warning("--> Server sends Answer to remote") {:noreply, %{state | sender: sender}} else error -> Logger.error("Server: Error creating answer: #{inspect(error)}") {:stop, :shutdown, state} end end def handle_cast({:receive_signaling_msg, %{"type"=> "ice"} = msg, _sender}, state) do candidate = ICECandidate.from_json(msg["candidate"]) :ok = PeerConnection.add_ice_candidate(state.pc, candidate) Logger.debug("--> Server processes remote ICE") {:noreply, state} end def handle_cast({:receive_signaling_msg, {msg, _}}, state) do Logger.warning("Server: unexpected msg: #{inspect(msg)}") {:stop, :shutdown, state} end @impl true def handle_info({:ex_webrtc, _pc, {:track, %{kind: :video} = client_video_track}}, state) do {:noreply, %{state | client_video_track: client_video_track}} end # internal messages -------- def handle_info({:ex_webrtc, _pc, {:ice_candidate, candidate}}, state) do candidate = ICECandidate.to_json(candidate) send(state.sender, {:signaling, %{"type"=> "ice", "candidate" => candidate}}) Logger.debug("--> Server sends ICE to remote") {:noreply, state} end def handle_info( {:ex_webrtc, pc, {:rtp, client_track_id, _rid, packet}}, %{client_video_track: %{id: client_track_id, kind: :video}} = state ) do PeerConnection.send_rtp(pc, state.serv_video_track.id, packet) {:noreply, state} end def handle_info({:ex_webrtc, pc, {:connection_state_change, :connected}}, state) do PeerConnection.get_transceivers(pc) |> Enum.find(&(&1.kind == :video)) |> then(fn %{receiver: receiver} -> Logger.warning("PeerConnection successfully connected, using #{inspect(receiver.codec.mime_type)}") end) {:noreply, state} end def handle_info({:ex_webrtc, _pc, _msg}, state) do {:noreply, state} end defp gather_candidates(pc) do receive do {:ex_webrtc, ^pc, {:ice_gathering_state_change, :complete}} -> :ok after 1000 -> {:error, :timeout} end end end ``` We will start the RTC GenServer. ```elixir Supervisor.start_link([RtcServer], strategy: :one_for_one) ``` We instantiate a new PeerConnection: ```elixir :connected = RtcServer.connect() ``` This will instantiate aserver-side. It is waiting for a peer to connect and receive its offer. It will respond with an "answer", digest the peer's Ice candidates, and send to the peer its own ICE candidates. ```elixir RtcServer.peek_state() ``` ### Client-side WebRTC module On connection, a newPeerConnectionis created. Since the server is already connected, the client will send an "offer" via the signaling channel. The client expects an "answer" back. It will also send "Ice" candidates via the signaling channel, and expects to receive Ice candidates from the server. Once the connection is set, the client will receive RTP packets and digest them into a `` element. We use aKino.JS.Liveto handle the signaling channel (the Live WebSocket). The face-detection will run in the browser and sent via WebRTC. Some notes on Kino.JS. > Kino expects us to code a "main.js" module that exports aninitfunction. In this module, we firstly import themediPipelibrary. > To have a cleaer code, we separated the Javascript code and inject it from an URL. A helper module to pull in the Javacsript code used in the "main.js" module from the Gihub repo. ```elixir defmodule Assets do def fetch_js do github_js_url = "https://raw.githubusercontent.com/dwyl/WebRTC-SFU-demo/main/lib/assets/main_mediapipe.js" Req.get!(github_js_url).body end def fetch_html do github_html_url = "https://raw.githubusercontent.com/dwyl/WebRTC-SFU-demo/main/lib/assets/index.html" Req.get!(github_html_url).body end end ``` TheKino.JS.livemodule: ```elixir defmodule VideoLive do # GenServer to communicate between browser and Livebook server use Kino.JS use Kino.JS.Live require Logger @html Assets.fetch_html() asset "main.css" do """ #elt { display: flex; flex-direction: column; align-items: center; } button { margin-top: 1em; margin-bottom: 1em; padding: 1em; background-color: bisque; } """ end asset "main.js" do Assets.fetch_js() end def new() do Kino.JS.Live.new(__MODULE__, @html) end @impl true def init(html, ctx) do {:ok, assign(ctx, html: html)} end @impl true def handle_connect(ctx) do {:ok, ctx.assigns.html, ctx} end # received from the browser via the signaling WebSocket, call server @impl true def handle_event("offer",%{"sdp" => sdp}, ctx) do RtcServer.receive_signaling_msg({sdp, self()}) {:noreply, ctx} end def handle_event("ice",%{"candidate" => candidate}, ctx) do RtcServer.receive_signaling_msg({%{"type" => "ice", "candidate" => candidate}, self()}) {:noreply, ctx} end # received from the server, send to the browser via signaling WebSocket @impl true def handle_info({:signaling, %{"type" => "answer"} = msg}, ctx) do broadcast_event(ctx, "answer", msg) {:noreply, ctx} end def handle_info({:signaling, %{"type" => "ice"} = msg}, ctx) do if msg["candidate"], do: broadcast_event(ctx, "ice",msg) {:noreply, ctx} end end ``` ## Run it! ```elixir VideoLive.new() ``` ## Note on the Javascript face detection drawing It relies on the methods [requestVideoFrameCallback](https://developer.mozilla.org/en-US/docs/Web/API/HTMLVideoElement/requestVideoFrameCallback) andcanvas.captureStreamand on themediaPipelibrary that accepts a video stream. The code is borrowed from Google's [MediaPipe](https://ai.google.dev/edge/mediapipe/solutions/vision/face_detector/web_js) documentation. **TLTR;** We draw every frame on acanvas, run the face detection, and redraw the detected faces on the canvas. WithrequestVideoFrameCallback, you can transform each frame of a video stream, _at the rate of the video_, namely 30fps. We use this transformed stream and add it to the PeerConnection track. ```js const pc = new RTCPeerConnection(iceConf); transformedStream .getTracks() .forEach((track) => pc.addTrack(track, transformedStream)); ``` Et voilà. ```js import { FaceDetector, FilesetResolver, } from "https://cdn.jsdelivr.net/npm/@mediapipe/tasks-vision@0.10.0"; export async function init(ctx, html) { ctx.importCSS("main.css"); ctx.root.innerHTML = html; async function run() { console.log("Starting....."); const videoIn = document.getElementById("source"), display = { width: videoIn.width, height: videoIn.height }, canvas = document.createElement("canvas"), context = canvas.getContext("2d"), stream = await window.navigator.mediaDevices.getUserMedia({ video: display, audio: false, }); videoIn.srcObject = stream; await videoIn.play(); // -------------------mediaPipe-api ------------------ canvas.height = display.height; canvas.width = display.width; let faceDetector; // Loads the MediaPipe Face Detector model and begins detecting faces in the input video. const initializeFaceDetector = async () => { const vision = await FilesetResolver.forVisionTasks( "https://cdn.jsdelivr.net/npm/@mediapipe/tasks-vision@0.10.0/wasm" ); faceDetector = await FaceDetector.createFromOptions(vision, { baseOptions: { modelAssetPath:https://storage.googleapis.com/mediapipe-models/face_detector/blaze_face_short_range/float16/1/blaze_face_short_range.tflite`,
delegate: “GPU”,
},
runningMode: “VIDEO”,
});
await predictWebcam();
};
async function predictWebcam() {
const detections = await faceDetector.detectForVideo(
videoIn,
performance.now()
);
displayVideoDetections(detections.detections);
window.requestAnimationFrame(predictWebcam);
}
function displayVideoDetections(detections) {
context.clearRect(0, 0, display.width, display.height);
context.drawImage(videoIn, 0, 0, display.width, display.height);
detections.forEach((detection) => {
const bbox = detection.boundingBox;
context.beginPath();
context.rect(bbox.originX, bbox.originY, bbox.width, bbox.height);
context.lineWidth = 2;
context.strokeStyle = “blue”;
context.stroke();
detection.keypoints.forEach((keypoint) => {
context.beginPath();
context.arc(keypoint.x, keypoint.y, 3, 0, 2 Math.PI);
context.fillStyle = “red”;
context.fill();
});
/
const p = document.createElement(“p”);
p.innerText = Confidence: ${( detection.categories[0].score * 100 ).toFixed(2)}%;
p.style.position = “absolute”;
p.style.left = ${bbox.originX}px;
p.style.top = ${bbox.originY - 20}px;
p.style.backgroundColor = “rgba(255, 255, 255, 0.7)”;
p.style.padding = “2px”;
p.style.borderRadius = “3px”;
document.body.appendChild(p);
setTimeout(() => {
document.body.removeChild(p);
}, 1000);
*/
});
}
await initializeFaceDetector();
const transformedStream = canvas.captureStream(30);
//———————– WEBRTC—————————–
const iceConf = { iceServers: [{ urls: “stun:stun.l.google.com:19302” }] };
const pc = new RTCPeerConnection(iceConf);
// capture local MediaStream (from the webcam)
const tracks = transformedStream.getTracks();
tracks.forEach((track) => pc.addTrack(track, transformedStream));
// send offer to any peer connected on the signaling channel
pc.onicecandidate = ({ candidate }) => {
if (candidate === null) {
return;
}
ctx.pushEvent(“ice”, { candidate: candidate.toJSON(), type: “ice” });
};
// send offer to any peer connected on the signaling channel
pc.onnegotiationneeded = async () => {
const offer = await pc.createOffer();
await pc.setLocalDescription(offer);
console.log(“–> Offer created and sent”);
ctx.pushEvent(“offer”, { sdp: offer });
};
// received from the remote peer (Elixir SFU server here) via UDP
pc.ontrack = ({ streams }) => {
console.log(“–> Received remote track”);
const echo = document.querySelector(“#echo”);
echo.srcObject = streams[0];
};
// received from the remote peer via signaling channel (Elixir server)
ctx.handleEvent(“ice”, async ({ candidate }) => {
await pc.addIceCandidate(candidate);
});
ctx.handleEvent(“answer”, async (msg) => {
console.log(“–> handled Answer”);
await pc.setRemoteDescription(msg);
});
// internal WebRTC listener, for information or other action…
pc.onconnectionstatechange = () => {
console.log(“~~> Connection state: “, pc.connectionState);
};
}
run();
}
html
Local webcam
Echo webcam
```