PyImageConf-Overview.ipynb

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   "source": [
    "# Computer Vision for Faces\n",
    "\n",
    "By **Satya Mallick**"
   ]
  },
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   "source": [
    "# Overview\n"
   ]
  },
  {
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   "metadata": {
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    }
   },
   "source": [
    "# Red Eye Removal ( Test Installation )\n",
    "\n",
    "\n",
    "![](data/images/automatic-red-eye-removal.jpg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
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   },
   "source": [
    "# Red Eye Removal \n",
    "\n",
    "1. Read Image\n",
    "2. How to use an eye detector\n",
    "3. Simple color based segmentation\n",
    "4. Color channel manipulation & masking"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
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   },
   "source": [
    "# Face Morphing\n",
    "![](data/images/morph.gif)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
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   "source": [
    "# Face Morphing\n",
    "\n",
    "1. Facial Landmark Detection\n",
    "2. Simple image warping\n",
    "3. Piecewise linear warp\n",
    "4. Delaunay triangulation\n",
    "5. Alpha blending images"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
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   },
   "source": [
    "# Face Swap\n",
    "\n",
    "![](data/images/trump-putin.jpg)\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
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   "source": [
    "# Face Swap\n",
    "\n",
    "1. Convex Hull\n",
    "2. Seamless Cloning"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
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     "slide_type": "slide"
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   },
   "source": [
    "# Face Recognition Web App\n",
    "\n"
   ]
  },
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    "%%HTML\n",
    "<video width=\"640\" height=\"480\" controls>\n",
    "  <source src=\"data/videos/facerec.mp4\" type=\"video/mp4\">\n",
    "</video>"
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   "metadata": {
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   },
   "source": [
    "# Face Recognition Web App\n",
    "\n",
    "1. Basics of Face Recogntion\n",
    "2. Using Face Recognition in an offline application\n",
    "3. Javascript based face detector\n",
    "4. How to build a Face Recognition Web Application"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
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    }
   },
   "source": [
    "# Thank You!"
   ]
  }
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