Untitled notebook

Mix.install([
  {:evision, "~> 0.2.5"},
  {:ex_cmd, "~> 0.12.0"},
  {:kino, "~> 0.13.1"},
])

Section

Constants

defmodule Constants do
  def ffmpeg_path do
    "/opt/homebrew/Cellar/ffmpeg/7.0-with-options_1/bin/ffmpeg"
  end

  def haar do
    haar_path = 
      Path.join(
        :code.priv_dir(:evision),
        "share/opencv4/haarcascades/haarcascade_frontalface_default.xml"
      )
          
    Evision.CascadeClassifier.cascadeClassifier(haar_path)
  end
end

A folder to collect the temp files we will produce

File.mkdir("pics")

A module to render a `` and 3 actions buttons: “to file” to save every frame into a file, “to buffer” to work directly with the buffer sent as binary via websocket, and “stop” to cleanup. elixir defmodule VideoLive do use Kino.JS use Kino.JS.Live @html """ Local webcam
Send chunks Stop """ 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 """ export function init(ctx, html) { console.log("init") ctx.importCSS("main.css"); ctx.root.innerHTML = html; function run() { let video1 = document.getElementById("source"), video2 = document.getElementById("output"), start = document.getElementById("send-chunk"), stop = document.getElementById("stop"); navigator.mediaDevices.getUserMedia({video: true}) .then((stream)=> { video1.srcObject = stream let mediaRecorder = new MediaRecorder(stream); mediaRecorder.ondataavailable = async ({data}) => { if (data.size > 0) { console.log(data.size) const buffer = await data.arrayBuffer() ctx.pushEvent("chunk", [{}, buffer]); } } start.onclick = () => { mediaRecorder.start(1000); } stop.onclick = () => { mediaRecorder.stop(); ctx.pushEvent("stop", {}); } }) } run() } """ end def new() do Kino.JS.Live.new(__MODULE__, @html) end @impl true def init(html, ctx) do ffmpeg_path = Constants.ffmpeg_path() model = Constants.haar() # runs FFmpeg as a keep alive process: the file names are set by FFmpeg {:ok, pid} = # ~w(#{ffmpeg_path} -i pipe:0 -r 15 -video_size 640x480 pics/test_%004d.jpg) ~w(#{ffmpeg_path} ffmpeg -i pipe:0 -r 30 -s 640x480 -vf format=yuv420p -y in/test_%04d.jpg) |> ExCmd.Process.start_link() {:ok, assign(ctx, html: html, proc_file: pid, model: model)} end @impl true def handle_connect(ctx) do {:ok, ctx.assigns.html, ctx} end # received from the browser @impl true def handle_event("stop", _, ctx) do IO.puts "STOPPED" ExCmd.Process.close_stdin(ctx.assigns.proc_file) ExCmd.Process.await_exit(ctx.assigns.proc_file) {:noreply, ctx} end def handle_event("chunk", {:binary, _, data}, ctx) do :ok = ExCmd.Process.write(ctx.assigns.proc_file, data) send(self(), :continue) {:noreply, ctx} end @impl true def handle_info(:continue, ctx) do #img_path = Path.join("./pics/", File.ls!("./pics")|> List.last()) #File.read!(img_path) #|> Processor.contour() #broadcast_event(ctx, "new", {:binary, [%{}, ]}) IO.puts("Total files: #{File.ls!("pics") |> length()}") {:noreply, ctx} end end elixir defmodule Processor do def haar() do haar_path = Path.join( :code.priv_dir(:evision), "share/opencv4/haarcascades/haarcascade_frontalface_default.xml" ) Evision.CascadeClassifier.cascadeClassifier(haar_path) end def contour(path) do img = Evision.imread(path) grey_data = Evision.cvtColor(img, Evision.ImreadModes.cv_IMREAD_GRAYSCALE()) faces = Evision.CascadeClassifier.detectMultiScale(Constants.haar(), grey_data) new_img = Enum.reduce(faces, img, fn {x, y, w, h}, mat -> Evision.rectangle(mat, {x, y}, {x + w, y + h}, {0, 0, 255}, thickness: 2) end) Evision.imwrite("pics/out-#{Path.basename(path)}", new_img) end end elixir VideoLive.new() ### Face contouring on a single image Testing on a single image extracted from the previous run, you can check: elixir Path.join("./pics/", File.ls!("./pics")|> List.last()) |> Processor.contour()