02 - Image_Preparation.ipynb

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    "# Image preparation\n",
    "\n",
    "The original image size is 55x90 pixels with a color depth of 3 (RGB).\n",
    "The below code can be used to transform the images in an input directory (Input_dir) to the right size (20x32 pixels) into an output directory (Output_dir). Inside the directory the pictures are stored in subdirectories according their labeling (0 ... 9 + NaN).\n",
    "Any other image converter can be used as well.\n",
    "\n",
    "### Prerequisite\n",
    "Installed OpenCV libary within python (opencv)"
   ]
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    "import glob\n",
    "import os\n",
    "from PIL import Image \n",
    "\n",
    "Input_dir = 'ziffer_sortiert_raw'\n",
    "Output_dir= 'ziffer_sortiert_resize'\n",
    "\n",
    "target_size_x = 20\n",
    "target_size_y = 32\n",
    "\n"
   ]
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     "text": [
      "1573 files have been deleted.\n"
     ]
    }
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   "source": [
    "files = glob.glob(Output_dir + '/*.jpg')\n",
    "i = 0\n",
    "for f in files:\n",
    "    os.remove(f)\n",
    "    i=i+1\n",
    "print(str(i) + \" files have been deleted.\")"
   ]
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     "text": [
      "250 ...\n",
      "500 ...\n",
      "750 ...\n",
      "1000 ...\n",
      "1250 ...\n",
      "1300\n"
     ]
    }
   ],
   "source": [
    "files = glob.glob(Input_dir + '/*.jpg')\n",
    "files = files + glob.glob(Input_dir + '/*.png')\n",
    "files = files + glob.glob(Input_dir + '/*.bmp')\n",
    "count = 0\n",
    "for aktfile in files:\n",
    "    count = count + 1\n",
    "    if not count % 250:\n",
    "        print(str(count) + \" ...\")\n",
    "    test_image = Image.open(aktfile)\n",
    "    test_image = test_image.convert('RGB')\n",
    "    test_image = test_image.resize((target_size_x, target_size_y), Image.NEAREST)\n",
    "    base=os.path.basename(aktfile)\n",
    "    base = os.path.splitext(base)[0] + \".jpg\"\n",
    "    save_name = Output_dir + '/' + base\n",
    "#    print(\"in: \" + aktfile + \"  -  out: \" + save_name)\n",
    "    test_image.save(save_name, \"JPEG\", quality=100)\n",
    "print(count)"
   ]
  },
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   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
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