{
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    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "%matplotlib inline"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "# Face Detection\n\nThis demo shows how a simple image processing example can be demonstrated.\nThe ``itom`` grabber ``OpenCVGrabber`` captures your webcam.\nThen live your face and eyes are detected and marked in the live plot.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "from itom import dataObject\nfrom itom import dataIO\nfrom itom import ui\nimport cv2\nimport numpy as np\nimport gc"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Face detection method.\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "def detectFace(img, cascade):\n    rects = cascade.detectMultiScale(img, scaleFactor=1.3, minNeighbors=4)\n    if len(rects) == 0:\n        return []\n    rects[:, 2:] += rects[:, :2]\n    return rects"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Eye detection method.\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "def detectEyes(img, cascade):\n    eyes = cascade.detectMultiScale(img)\n    if len(eyes) == 0:\n        return []\n\n    if eyes.shape[0] > 2:\n        eyes = eyes[0:1, :]\n\n    return eyes"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Draw detected rectangle method. \n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "def drawRects(img, faces, color):\n    for x1, y1, x2, y2 in faces:\n        rect = shape.createRectangle((x1, y1), (x2, y2), index=11)\n        rect.color = color\n        win.plot.call(\"updateGeometricShape\", rect)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Draw detected eyes method.\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "def drawEyes(img, eyes, color):\n    cnt = 21\n    for x, y, w, h in eyes:\n        eye = shape.createEllipse((x, y + h), (x + w, y), index=cnt)\n        eye.color = color\n        try:\n            win.plot.call(\"updateGeometricShape\", eye)\n        except AttributeError:\n            break\n        cnt = cnt + 1"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Acquire an image from the webcam.\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "def snap():\n    # image acquisition\n    if \"cam\" in globals():\n        d = dataObject()\n        cam.disableAutoGrabbing()\n        cam.acquire()\n        cam.getVal(d)\n    else:\n        return\n\n    img = np.array(d)\n\n    win.plot[\"source\"] = img\n\n    # detect face and eyes\n    faces = detectFace(img, faceCascade)\n    eyes = detectEyes(img, eyeCascade)\n\n    # overlay rect and eyes\n    drawRects(img, faces, rgba(255, 0, 0, 255))  # in color red\n    drawEyes(img, eyes, rgba(0, 255, 0, 255))  # in color green"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Close GUI and stop webcam. \n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "def guiClosed():\n    tDetect.stop()\n    global cam, win\n    del win\n    del cam\n    gc.collect()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Open a simple ``GUI``, connect the webcam and starte the live face detection. \n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "win = ui(\n    \"FaceDetect.ui\",\n    ui.TYPEWINDOW,\n    childOfMainWindow=True,\n    deleteOnClose=True,\n)\n\nfaceCascade = cv2.CascadeClassifier()\neyeCascade = cv2.CascadeClassifier()\n\nfaceCascade.load(\"haarcascades/haarcascade_frontalface_alt.xml\")\neyeCascade.load(\"haarcascades/haarcascade_eye_tree_eyeglasses.xml\")\n\ncam = dataIO(\"OpenCVGrabber\", 0, \"gray\")\ncam.startDevice()\ncam.disableAutoGrabbing()\n\ntDetect = timer(100, snap)\n\nwin.connect(\"destroyed()\", guiClosed)\n\n# start GUI\nwin.show(0)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "<img src=\"file://../../_static/demoFaceDetection_1.png\" width=\"100%\">\n"
      ]
    }
  ],
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