{
 "<h1>Carvana Dataset for the <a href=\"index.html\">U-Net</a> <a href=\"experiment.html\">experiment</a></h1>\n<p>You can find the download instructions <a href=\"https://www.kaggle.com/competitions/carvana-image-masking-challenge/data\">on Kaggle</a>.</p>\n<p>Save the training images inside <span translate=no>_^_0_^_</span> folder and the masks in <span translate=no>_^_1_^_</span> folder.</p>\n": "<h1><a href=\"index.html\"><a href=\"experiment.html\">U-Net\u5b9f\u9a13\u7528\u306e\u30ab\u30eb\u30d0\u30ca\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8</a></a></h1>\n<p>\u30c0\u30a6\u30f3\u30ed\u30fc\u30c9\u624b\u9806\u306f <a href=\"https://www.kaggle.com/competitions/carvana-image-masking-challenge/data\">Kaggle \u3067\u78ba\u8a8d\u3067\u304d\u307e\u3059</a>\u3002</p>\n<p><span translate=no>_^_0_^_</span>\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u753b\u50cf\u3092\u30d5\u30a9\u30eb\u30c0\u30fc\u5185\u306b\u4fdd\u5b58\u3057\u3001<span translate=no>_^_1_^_</span>\u30de\u30b9\u30af\u3092\u30d5\u30a9\u30eb\u30c0\u30fc\u306b\u4fdd\u5b58\u3057\u307e\u3059\u3002</p>\n",
 "<h2>Carvana Dataset</h2>\n": "<h2>\u30ab\u30fc\u30d0\u30ca\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8</h2>\n",
 "<h4>Get an image and its mask.</h4>\n<ul><li><span translate=no>_^_0_^_</span>  is index of the image</li></ul>\n": "<h4>\u753b\u50cf\u3068\u305d\u306e\u30de\u30b9\u30af\u3092\u5165\u624b\u3057\u3066\u304f\u3060\u3055\u3044\u3002</h4>\n<ul><li><span translate=no>_^_0_^_</span>\u306f\u753b\u50cf\u306e\u30a4\u30f3\u30c7\u30c3\u30af\u30b9\u3067\u3059</li></ul>\n",
 "<h4>Size of the dataset</h4>\n": "<h4>\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306e\u30b5\u30a4\u30ba</h4>\n",
 "<p>Get a dictionary of images by id </p>\n": "<p>ID \u3067\u753b\u50cf\u306e\u8f9e\u66f8\u3092\u53d6\u5f97</p>\n",
 "<p>Get a dictionary of masks by id </p>\n": "<p>ID \u3067\u30de\u30b9\u30af\u306e\u8f9e\u66f8\u3092\u53d6\u5f97</p>\n",
 "<p>Get image id </p>\n": "<p>\u753b\u50cf ID \u3092\u53d6\u5f97</p>\n",
 "<p>Image ids list </p>\n": "<p>\u753b\u50cfID\u30ea\u30b9\u30c8</p>\n",
 "<p>Load image </p>\n": "<p>\u753b\u50cf\u3092\u8aad\u307f\u8fbc\u3080</p>\n",
 "<p>Load mask </p>\n": "<p>\u30ed\u30fc\u30c9\u30de\u30b9\u30af</p>\n",
 "<p>Return the image and the mask </p>\n": "<p>\u753b\u50cf\u3068\u30de\u30b9\u30af\u3092\u8fd4\u3059</p>\n",
 "<p>Testing code </p>\n": "<p>\u30c6\u30b9\u30c8\u30b3\u30fc\u30c9</p>\n",
 "<p>The mask values were not <span translate=no>_^_0_^_</span>, so we scale it appropriately. </p>\n": "<p>\u30de\u30b9\u30af\u5024\u306f\u306a\u304b\u3063\u305f\u306e\u3067<span translate=no>_^_0_^_</span>\u3001\u9069\u5207\u306b\u30b9\u30b1\u30fc\u30ea\u30f3\u30b0\u3057\u307e\u3057\u305f\u3002</p>\n",
 "<p>Transform image and convert it to a PyTorch tensor </p>\n": "<p>\u753b\u50cf\u3092\u5909\u63db\u3057\u3066 PyTorch \u30c6\u30f3\u30bd\u30eb\u306b\u5909\u63db\u3059\u308b</p>\n",
 "<p>Transform mask and convert it to a PyTorch tensor </p>\n": "<p>\u30de\u30b9\u30af\u3092\u5909\u63db\u3057\u3066 PyTorch \u30c6\u30f3\u30bd\u30eb\u306b\u5909\u63db\u3059\u308b</p>\n",
 "<p>Transformations </p>\n": "<p>\u30c8\u30e9\u30f3\u30b9\u30d5\u30a9\u30fc\u30e1\u30fc\u30b7\u30e7\u30f3</p>\n",
 "<ul><li><span translate=no>_^_0_^_</span>  is the path to the images </li>\n<li><span translate=no>_^_1_^_</span>  is the path to the masks</li></ul>\n": "<ul><li><span translate=no>_^_0_^_</span>\u753b\u50cf\u3078\u306e\u30d1\u30b9\u3067\u3059</li>\n<li><span translate=no>_^_1_^_</span>\u30de\u30b9\u30af\u3078\u306e\u9053\u3067\u3059</li></ul>\n",
 "Carvana dataset for the U-Net experiment": "U-Net\u5b9f\u9a13\u7528\u306eCarvana\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8",
 "Carvana dataset for the U-Net experiment.": "U-Net\u5b9f\u9a13\u7528\u306eCarvana\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3002"
}