2-Image_read_and_save.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 1-Resim Okuma / Kaydetme"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## [Matplotlib](https://matplotlib.org/users/image_tutorial.html) ile Resim Dosyasını Okuma "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-22T09:25:14.855050Z",
     "start_time": "2019-08-22T09:25:14.068570Z"
    }
   },
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.image as mpimg\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-22T09:25:14.868279Z",
     "start_time": "2019-08-22T09:25:14.857150Z"
    }
   },
   "outputs": [],
   "source": [
    "img = mpimg.imread('images/parrot.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-22T09:25:15.136711Z",
     "start_time": "2019-08-22T09:25:14.869850Z"
    }
   },
   "outputs": [],
   "source": [
    "plt.imshow(img)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## [Pillow](https://pillow.readthedocs.io/en/3.1.x/index.html) ile Resim Dosyasını Okuma "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-22T09:25:15.144017Z",
     "start_time": "2019-08-22T09:25:15.138829Z"
    }
   },
   "outputs": [],
   "source": [
    "from PIL import Image\n",
    "from matplotlib.pyplot import imshow\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Grayscale"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-22T09:25:15.794076Z",
     "start_time": "2019-08-22T09:25:15.782165Z"
    }
   },
   "outputs": [],
   "source": [
    "img_gray = Image.open(\"images/lena_gray.gif\")\n",
    "print(img_gray.width, img_gray.height, img_gray.mode, img_gray.format, type(img_gray))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-22T09:25:16.220346Z",
     "start_time": "2019-08-22T09:25:16.015813Z"
    }
   },
   "outputs": [],
   "source": [
    "imshow(img_gray)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-22T09:25:16.408485Z",
     "start_time": "2019-08-22T09:25:16.395030Z"
    }
   },
   "outputs": [],
   "source": [
    "pixels = list(img_gray.getdata())\n",
    "len(pixels)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Color"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-22T09:25:17.164406Z",
     "start_time": "2019-08-22T09:25:17.158206Z"
    }
   },
   "outputs": [],
   "source": [
    "img_lena = Image.open(\"images/lena.jpg\").convert('RGB')\n",
    "print(img_lena.width, img_lena.height, img_lena.mode, img_lena.format, type(img_lena))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-22T09:25:17.815534Z",
     "start_time": "2019-08-22T09:25:17.616595Z"
    }
   },
   "outputs": [],
   "source": [
    "imshow(img_lena)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-22T09:25:18.287628Z",
     "start_time": "2019-08-22T09:25:18.284802Z"
    }
   },
   "outputs": [],
   "source": [
    "width, height = img_lena.size\n",
    "print(width, height)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Renkli görüntünün 3 kanal için pixel değerlerini okuma**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-22T09:25:22.995670Z",
     "start_time": "2019-08-22T09:25:19.519736Z"
    }
   },
   "outputs": [],
   "source": [
    "w,h = img_lena.size\n",
    "for i in range(w):\n",
    "    for j in range(h):\n",
    "        r,g,b = img_lena.getpixel((i,j))\n",
    "        print(\"({0},{1}) : r:{2},g:{3},b:{4}\".format(i,j, r,g,b))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Resim oluşturma ve Resmin negatifini alma"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-22T09:25:23.010486Z",
     "start_time": "2019-08-22T09:25:22.999265Z"
    }
   },
   "outputs": [],
   "source": [
    "img_new = np.zeros([220,220,3],dtype=np.uint8)\n",
    "img_new.fill(0)\n",
    "img_new"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-22T09:25:23.264825Z",
     "start_time": "2019-08-22T09:25:23.012943Z"
    }
   },
   "outputs": [],
   "source": [
    "imshow(img_new)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-22T09:25:23.275612Z",
     "start_time": "2019-08-22T09:25:23.270691Z"
    }
   },
   "outputs": [],
   "source": [
    "img_new.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Pixel değerlerini değiştirme**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-22T09:25:24.421108Z",
     "start_time": "2019-08-22T09:25:24.085220Z"
    }
   },
   "outputs": [],
   "source": [
    "import ipywidgets as widgets\n",
    "from ipywidgets import interact, interact_manual\n",
    "\n",
    "@interact\n",
    "def change_color_img(column='colors', r=(0,255), g=(0,255), b=(0,255)):\n",
    "    w = img_new.shape[0]\n",
    "    h = img_new.shape[1]\n",
    "    c = img_new.shape[2]\n",
    "    for i in range(w):\n",
    "        for j in range(h):\n",
    "            img_new[i][j][0] = r\n",
    "            img_new[i][j][1] = g\n",
    "            img_new[i][j][2] = b\n",
    "        \n",
    "    imshow(img_new)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Resmin Negatifini Alma"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-22T09:25:33.175864Z",
     "start_time": "2019-08-22T09:25:32.893787Z"
    }
   },
   "outputs": [],
   "source": [
    "img = Image.open('images/lena.jpg')\n",
    "img_array = np.array(img)\n",
    "\n",
    "imshow(img_array)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-22T09:25:33.879535Z",
     "start_time": "2019-08-22T09:25:33.179116Z"
    }
   },
   "outputs": [],
   "source": [
    "img_negative = np.zeros([220,220,3],dtype=np.uint8)\n",
    "\n",
    "for i in range(img_array.shape[0]):\n",
    "    for j in range(img_array.shape[1]):\n",
    "        r,g,b = img_array[i][j]\n",
    "        \n",
    "        img_negative[i][j][0] = 255-r\n",
    "        img_negative[i][j][1] = 255-g\n",
    "        img_negative[i][j][2] = 255-b\n",
    "\n",
    "imshow(img_negative)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Resim Kaydetme"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2019-08-22T09:25:33.910994Z",
     "start_time": "2019-08-22T09:25:33.882280Z"
    }
   },
   "outputs": [],
   "source": [
    "img_lena_negative = Image.fromarray(img_negative)\n",
    "img_lena_negative.save('images/lena_negative.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Daha fazla interaktif örnek için: http://setosa.io/ev/image-kernels/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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