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   "source": [
    "# Tutorial 2: Simple Customisation\n",
    "In this notebook we will get to grips with how to peice together a simple IQM-Vis UI. We will go through the 3 basic aspects of customisation:\n",
    " - Images\n",
    " - Metrics\n",
    " - Transformations\n",
    "\n",
    "Let's start by importing the package."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "215fd983",
   "metadata": {},
   "outputs": [],
   "source": [
    "import IQM_Vis"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "59b6af9e",
   "metadata": {},
   "source": [
    "### Images\n",
    "To include custom images we define their filepaths. For now we will use the example images provided with IQM-Vis, but feel free to change the file paths with your own local image files."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "04dc4a41",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Images files: ['/home/matt/projects/IQM-VIS/IQM_Vis/examples/images/waves1.jpeg', '/home/matt/projects/IQM-VIS/IQM_Vis/examples/images/waves2.jpeg']\n"
     ]
    }
   ],
   "source": [
    "image1 = IQM_Vis.examples.images.IMAGE1\n",
    "image2 = IQM_Vis.examples.images.IMAGE2\n",
    "\n",
    "images = [image1, image2]\n",
    "print(f'Images files: {images}')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e6984719",
   "metadata": {},
   "source": [
    "### Metrics\n",
    "To include some custom image quality metrics we store them in a dictionary. These return a scalar value when comparing two images. For now we will use some metrics provided by IQM-Vis. For a list of all metrics provided by IQM-Vis see the documentation (https://mattclifford1.github.io/IQM-Vis/IQM_Vis.metrics.html). See later tutorials for how to define your own custom metrics."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "19eab748",
   "metadata": {},
   "outputs": [],
   "source": [
    "MAE = IQM_Vis.IQMs.MAE()\n",
    "MSE = IQM_Vis.IQMs.MSE()\n",
    "SSIM = IQM_Vis.IQMs.SSIM()\n",
    "\n",
    "metrics = {'MAE': MAE,\n",
    "           'MSE': MSE,\n",
    "           '1-SSIM': SSIM}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a509fc73",
   "metadata": {},
   "source": [
    "### Metric Images\n",
    "Adding image quality metrics that return an image instead of a scalar value is a similar process to the metrics before. Defining these is optional but can be useful for qualitive spacial analysis."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "9038617d",
   "metadata": {},
   "outputs": [],
   "source": [
    "MSE_image = IQM_Vis.IQMs.MSE(return_image=True)\n",
    "SSIM_image = IQM_Vis.IQMs.SSIM(return_image=True)\n",
    "\n",
    "metric_images = {'MSE': MSE_image,\n",
    "                 '1-SSIM': SSIM_image}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8fe1426e",
   "metadata": {},
   "source": [
    "### Transformations\n",
    "Defining image transformation/distortions requires a little more information as we also need to provide the range of values that we want the transformations to operate over."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "0d35590d",
   "metadata": {},
   "outputs": [],
   "source": [
    "rotation = IQM_Vis.transforms.rotation\n",
    "blur = IQM_Vis.transforms.blur\n",
    "brightness = IQM_Vis.transforms.brightness\n",
    "jpeg_compression = IQM_Vis.transforms.jpeg_compression\n",
    "\n",
    "transformations = {\n",
    "    'rotation':  {'min':-180, 'max':180, 'function':rotation},                # normal input\n",
    "    'blur':      {'min':1,    'max':41,  'function':blur, 'normalise':'odd'}, # only odd ints since it's a kernel\n",
    "    'brightness':{'min':-1.0, 'max':1.0, 'function':brightness},              # float values\n",
    "    'jpg comp.': {'min':1,    'max':100, 'function':jpeg_compression, 'init_value':100}, # non zero inital value\n",
    "               }"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "393e6549",
   "metadata": {},
   "source": [
    "## Putting it all together\n",
    "We need to pass everything to the UI maker"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "45efb3d3",
   "metadata": {},
   "outputs": [],
   "source": [
    "IQM_Vis.make_UI(transformations=transformations,\n",
    "                image_list=images,\n",
    "                metrics=metrics,\n",
    "                metric_images=metric_images)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "606115ff",
   "metadata": {},
   "source": [
    "You will now get the desired UI with the specified transformations, metrics and images\n",
    "\n",
    "![](./resources/custom_UI.png)"
   ]
  }
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