{
 "cells": [
  {
   "cell_type": "markdown",
   "source": [
    "Crop centered window to given size"
   ],
   "metadata": {}
  },
  {
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": "150×410 MosaicViews.MosaicView{RGB{FixedPointNumbers.N0f8}, 4, Base.ReshapedArray{RGB{FixedPointNumbers.N0f8}, 4, PaddedViews.PaddedView{RGB{FixedPointNumbers.N0f8}, 3, Tuple{Base.OneTo{Int64}, Base.OneTo{Int64}, Base.OneTo{Int64}}, StackViews.StackView{RGB{FixedPointNumbers.N0f8}, 3, 3, Tuple{OffsetArrays.OffsetMatrix{RGB{FixedPointNumbers.N0f8}, PaddedViews.PaddedView{RGB{FixedPointNumbers.N0f8}, 2, Tuple{UnitRange{Int64}, UnitRange{Int64}}, Matrix{RGB{FixedPointNumbers.N0f8}}}}, OffsetArrays.OffsetMatrix{RGB{FixedPointNumbers.N0f8}, PaddedViews.PaddedView{RGB{FixedPointNumbers.N0f8}, 2, Tuple{UnitRange{Int64}, UnitRange{Int64}}, Matrix{RGB{FixedPointNumbers.N0f8}}}}}}}, Tuple{Base.MultiplicativeInverses.SignedMultiplicativeInverse{Int64}, Base.MultiplicativeInverses.SignedMultiplicativeInverse{Int64}}}}:\n RGB{N0f8}(1.0,1.0,1.0)  RGB{N0f8}(1.0,1.0,1.0)  …  RGB{N0f8}(0.0,0.0,0.0)\n RGB{N0f8}(1.0,1.0,1.0)  RGB{N0f8}(1.0,1.0,1.0)     RGB{N0f8}(0.0,0.0,0.0)\n RGB{N0f8}(1.0,1.0,1.0)  RGB{N0f8}(1.0,1.0,1.0)     RGB{N0f8}(0.0,0.0,0.0)\n RGB{N0f8}(1.0,1.0,1.0)  RGB{N0f8}(1.0,1.0,1.0)     RGB{N0f8}(0.0,0.0,0.0)\n RGB{N0f8}(1.0,1.0,1.0)  RGB{N0f8}(1.0,1.0,1.0)     RGB{N0f8}(0.0,0.0,0.0)\n RGB{N0f8}(1.0,1.0,1.0)  RGB{N0f8}(1.0,1.0,1.0)  …  RGB{N0f8}(0.0,0.0,0.0)\n RGB{N0f8}(1.0,1.0,1.0)  RGB{N0f8}(1.0,1.0,1.0)     RGB{N0f8}(0.0,0.0,0.0)\n RGB{N0f8}(1.0,1.0,1.0)  RGB{N0f8}(1.0,1.0,1.0)     RGB{N0f8}(0.0,0.0,0.0)\n RGB{N0f8}(1.0,1.0,1.0)  RGB{N0f8}(1.0,1.0,1.0)     RGB{N0f8}(0.0,0.0,0.0)\n RGB{N0f8}(1.0,1.0,1.0)  RGB{N0f8}(1.0,1.0,1.0)     RGB{N0f8}(0.0,0.0,0.0)\n ⋮                                               ⋱  \n RGB{N0f8}(1.0,1.0,1.0)  RGB{N0f8}(1.0,1.0,1.0)     RGB{N0f8}(0.0,0.0,0.0)\n RGB{N0f8}(1.0,1.0,1.0)  RGB{N0f8}(1.0,1.0,1.0)     RGB{N0f8}(0.0,0.0,0.0)\n RGB{N0f8}(1.0,1.0,1.0)  RGB{N0f8}(1.0,1.0,1.0)     RGB{N0f8}(0.0,0.0,0.0)\n RGB{N0f8}(1.0,1.0,1.0)  RGB{N0f8}(1.0,1.0,1.0)     RGB{N0f8}(0.0,0.0,0.0)\n RGB{N0f8}(1.0,1.0,1.0)  RGB{N0f8}(1.0,1.0,1.0)  …  RGB{N0f8}(0.0,0.0,0.0)\n RGB{N0f8}(1.0,1.0,1.0)  RGB{N0f8}(1.0,1.0,1.0)     RGB{N0f8}(0.0,0.0,0.0)\n RGB{N0f8}(1.0,1.0,1.0)  RGB{N0f8}(1.0,1.0,1.0)     RGB{N0f8}(0.0,0.0,0.0)\n RGB{N0f8}(1.0,1.0,1.0)  RGB{N0f8}(1.0,1.0,1.0)     RGB{N0f8}(0.0,0.0,0.0)\n RGB{N0f8}(1.0,1.0,1.0)  RGB{N0f8}(1.0,1.0,1.0)     RGB{N0f8}(0.0,0.0,0.0)",
      "image/png": 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"
     },
     "metadata": {},
     "execution_count": 1
    }
   ],
   "cell_type": "code",
   "source": [
    "using Augmentor\n",
    "using ImageShow, ImageCore\n",
    "\n",
    "img_in = testpattern(RGB, ratio=0.5)\n",
    "img_out = augment(img_in, CropSize(70, 70)) # crop out a square window\n",
    "\n",
    "mosaicview(img_in, img_out; nrow=1, npad=10)"
   ],
   "metadata": {},
   "execution_count": 1
  },
  {
   "cell_type": "markdown",
   "source": [
    "`RCropSize` is a random version that randomly choose a crop center -- not necessarily the center\n",
    "of the input image."
   ],
   "metadata": {}
  },
  {
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": "70×70 Array{RGB{N0f8},2} with eltype RGB{FixedPointNumbers.N0f8}:\n RGB{N0f8}(1.0,1.0,1.0)  RGB{N0f8}(1.0,1.0,1.0)  …  RGB{N0f8}(1.0,1.0,1.0)\n RGB{N0f8}(1.0,1.0,1.0)  RGB{N0f8}(1.0,1.0,1.0)     RGB{N0f8}(1.0,1.0,1.0)\n RGB{N0f8}(1.0,1.0,1.0)  RGB{N0f8}(1.0,1.0,1.0)     RGB{N0f8}(1.0,1.0,1.0)\n RGB{N0f8}(1.0,1.0,1.0)  RGB{N0f8}(1.0,1.0,1.0)     RGB{N0f8}(1.0,1.0,1.0)\n RGB{N0f8}(1.0,1.0,1.0)  RGB{N0f8}(1.0,1.0,1.0)     RGB{N0f8}(1.0,1.0,1.0)\n RGB{N0f8}(1.0,1.0,1.0)  RGB{N0f8}(1.0,1.0,1.0)  …  RGB{N0f8}(1.0,1.0,1.0)\n RGB{N0f8}(1.0,1.0,1.0)  RGB{N0f8}(1.0,1.0,1.0)     RGB{N0f8}(1.0,1.0,1.0)\n RGB{N0f8}(1.0,1.0,1.0)  RGB{N0f8}(1.0,1.0,1.0)     RGB{N0f8}(1.0,1.0,1.0)\n RGB{N0f8}(1.0,1.0,1.0)  RGB{N0f8}(1.0,1.0,1.0)     RGB{N0f8}(1.0,1.0,1.0)\n RGB{N0f8}(1.0,1.0,1.0)  RGB{N0f8}(1.0,1.0,1.0)     RGB{N0f8}(1.0,1.0,1.0)\n ⋮                                               ⋱  \n RGB{N0f8}(1.0,1.0,1.0)  RGB{N0f8}(1.0,1.0,1.0)     RGB{N0f8}(1.0,1.0,1.0)\n RGB{N0f8}(1.0,1.0,1.0)  RGB{N0f8}(1.0,1.0,1.0)     RGB{N0f8}(1.0,1.0,1.0)\n RGB{N0f8}(1.0,1.0,1.0)  RGB{N0f8}(1.0,1.0,1.0)     RGB{N0f8}(1.0,1.0,1.0)\n RGB{N0f8}(1.0,1.0,1.0)  RGB{N0f8}(1.0,1.0,1.0)     RGB{N0f8}(1.0,1.0,1.0)\n RGB{N0f8}(1.0,1.0,1.0)  RGB{N0f8}(1.0,1.0,1.0)  …  RGB{N0f8}(1.0,1.0,1.0)\n RGB{N0f8}(1.0,1.0,1.0)  RGB{N0f8}(1.0,1.0,1.0)     RGB{N0f8}(1.0,1.0,1.0)\n RGB{N0f8}(1.0,1.0,1.0)  RGB{N0f8}(1.0,1.0,1.0)     RGB{N0f8}(1.0,1.0,1.0)\n RGB{N0f8}(1.0,1.0,1.0)  RGB{N0f8}(1.0,1.0,1.0)     RGB{N0f8}(1.0,1.0,1.0)\n RGB{N0f8}(1.0,1.0,1.0)  RGB{N0f8}(1.0,1.0,1.0)     RGB{N0f8}(1.0,1.0,1.0)",
      "image/png": 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"
     },
     "metadata": {},
     "execution_count": 2
    }
   ],
   "cell_type": "code",
   "source": [
    "augment(img_in, CropSize(70, 70))"
   ],
   "metadata": {},
   "execution_count": 2
  },
  {
   "cell_type": "markdown",
   "source": [
    "![](cropsize.gif)"
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "## Reference"
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "---\n",
    "\n",
    "*This notebook was generated using [Literate.jl](https://github.com/fredrikekre/Literate.jl).*"
   ],
   "metadata": {}
  }
 ],
 "nbformat_minor": 3,
 "metadata": {
  "language_info": {
   "file_extension": ".jl",
   "mimetype": "application/julia",
   "name": "julia",
   "version": "1.7.3"
  },
  "kernelspec": {
   "name": "julia-1.7",
   "display_name": "Julia 1.7.3",
   "language": "julia"
  }
 },
 "nbformat": 4
}