{
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    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
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      "source": [
        "%matplotlib inline"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "# OpenCV filter\n\nThis demo shows how OpenCV filters are applied to the ``dataObject``.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "from itom import dataObject\nfrom itom import algorithms\nfrom itom import plot\nfrom itom import filterHelp\n\n# create a randomly filled  150x150px dataObject\ndObj = dataObject.rand([150, 150], \"float32\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Get information about the filter and its parameters.\nFirst, no idea about the filters name, therefore get all names containing the keyword ``cv``:\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "filterInfoDict = filterHelp(\"cv\", dictionary=1)\n\nfor key, value in filterInfoDict.items():\n    print(\"{}: {}\".format(value[\"name\"], value[\"description\"]))\n\n# the desired filter is called \"cvMedianBlur\", now obtain detailed information\nmedianBlurDict = filterHelp(\"cvMedianBlur\", dictionary=1)\n\nprint(\"{}: {}\".format(medianBlurDict[\"cvMedianBlur\"][\"name\"], medianBlurDict[\"cvMedianBlur\"][\"description\"]))\n\n# create an empty output image (its content will be filled within the filter-call)\noutputImage = dataObject()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Call the filter. The parameters after the filter name are the\n``mandatory`` parameters followed by the ``optional`` ones (if desired):\n\n1. parameter (mand): input image\n\n2. parameter (mand): output image\n\n3. kernellength (opt): size of squared filter kernel (default: 3)\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "algorithms.cvMedianBlur(dObj, outputImage, 5)\n\nplot(dObj)  # plot original image\nplot(outputImage)  # plot filtered image"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "<img src=\"file://../../_static/demoOpenCVFilter_1.png\" width=\"100%\">\n"
      ]
    }
  ],
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