// To display predictions, this app has:
// 1. A video that shows a feed from the user's webcam
// 2. A canvas that appears over the video and shows predictions
// When the page loads, a user is asked to give webcam permission.
// After this happens, the model initializes and starts to make predictions
// On the first prediction, an initialiation step happens in detectFrame()
// to prepare the canvas on which predictions are displayed.

var bounding_box_colors = {};

var user_confidence = 0.6;

// Update the colors in this list to set the bounding box colors
var color_choices = [
  "#C7FC00",
  "#FF00FF",
  "#8622FF",
  "#FE0056",
  "#00FFCE",
  "#FF8000",
  "#00B7EB",
  "#FFFF00",
  "#0E7AFE",
  "#FFABAB",
  "#0000FF",
  "#CCCCCC",
];

var canvas_painted = false;
var canvas = document.getElementById("video_canvas");
var ctx = canvas.getContext("2d");

var model = null;


function detectFrame() {
  // On first run, initialize a canvas
  // On all runs, run inference using a video frame
  // For each video frame, draw bounding boxes on the canvas
  if (!model) return requestAnimationFrame(detectFrame);

  model.detect(video).then(function(predictions) {

    if (!canvas_painted) {
      var video_start = document.getElementById("video1");
      canvas.style.width = video_start.width + "px";
      canvas.style.height = video_start.height + "px";
      canvas.width = video_start.width;
      canvas.height = video_start.height;
      // adjust top to margin position of video

      canvas.top = video_start.top;
      canvas.left = video_start.left;
      canvas.style.top = video_start.top + "px";
      canvas.style.left = video_start.left + "px";
      canvas.style.position = "absolute";
      video_start.style.display = "block";
      canvas.style.display = "absolute";
      canvas_painted = true;

      var loading = document.getElementById("loading");
      loading.style.display = "none";
    }
    requestAnimationFrame(detectFrame);
    ctx.clearRect(0, 0, canvas.width, canvas.height);
    if (video) {
      drawBoundingBoxes(predictions, ctx)
    }
  });
}

function drawBoundingBoxes(predictions, ctx) {
  // For each prediction, choose or assign a bounding box color choice,
  // then apply the requisite scaling so bounding boxes appear exactly
  // around a prediction.

  // If you want to do anything with predictions, start from this function.
  // For example, you could display them on the web page, check off items on a list,
  // or store predictions somewhere.

  for (var i = 0; i < predictions.length; i++) {
    var confidence = predictions[i].confidence;

    console.log(user_confidence)

    if (confidence < user_confidence) {
      continue
    }

    if (predictions[i].class in bounding_box_colors) {
      ctx.strokeStyle = bounding_box_colors[predictions[i].class];
    } else {
      var color =
        color_choices[Math.floor(Math.random() * color_choices.length)];
      ctx.strokeStyle = color;
      // remove color from choices
      color_choices.splice(color_choices.indexOf(color), 1);

      bounding_box_colors[predictions[i].class] = color;
    }

    var prediction = predictions[i];
    var x = prediction.bbox.x - prediction.bbox.width / 2;
    var y = prediction.bbox.y - prediction.bbox.height / 2;
    var width = prediction.bbox.width;
    var height = prediction.bbox.height;

    ctx.rect(x, y, width, height);

    ctx.fillStyle = "rgba(0, 0, 0, 0)";
    ctx.fill();

    ctx.fillStyle = ctx.strokeStyle;
    ctx.lineWidth = "4";
    ctx.strokeRect(x, y, width, height);
    ctx.font = "25px Arial";
    ctx.fillText(prediction.class + " " + Math.round(confidence * 100) + "%", x, y - 10);
  }
}

function webcamInference() {
  // Ask for webcam permissions, then run main application.
  var loading = document.getElementById("loading");
  loading.style.display = "block";

  navigator.mediaDevices
    .getUserMedia({ video: { facingMode: "environment" } })
    .then(function(stream) {
      video = document.createElement("video");
      video.srcObject = stream;
      video.id = "video1";

      // hide video until the web stream is ready
      video.style.display = "none";
      video.setAttribute("playsinline", "");

      document.getElementById("video_canvas").after(video);

      video.onloadedmetadata = function() {
        video.play();
      }

      // on full load, set the video height and width
      video.onplay = function() {
        height = video.videoHeight;
        width = video.videoWidth;

        // scale down video by 0.75

        height = height * 0.75;
        width = width * 0.75;

        width = Math.round(width);
        height = Math.round(height);

        video.setAttribute("width", width);
        video.setAttribute("height", height);
        video.style.width = width + "px";
        video.style.height = height + "px";

        canvas.style.width = width + "px";
        canvas.style.height = height + "px";
        canvas.width = width;
        canvas.height = height;

        document.getElementById("video_canvas").style.display = "block";
      };

      ctx.scale(1, 1);

      // Load the Roboflow model using the publishable_key set in index.html
      // and the model name and version set at the top of this file
      roboflow
        .auth({
          publishable_key: publishable_key,
        })
        .load({
          model: MODEL_NAME,
          version: MODEL_VERSION,
        })
        .then(function(m) {
          model = m;
          // Images must have confidence > CONFIDENCE_THRESHOLD to be returned by the model
          m.configure({ threshold: CONFIDENCE_THRESHOLD });
          // Start inference
          detectFrame();
        });
    })
    .catch(function(err) {
      console.log(err);
    });
}

function changeConfidence () {
  user_confidence = document.getElementById("confidence").value / 100;
}

document.getElementById("confidence").addEventListener("input", changeConfidence);

webcamInference();