{
  "id": 62330,
  "title": "Encoded Pixels in .csv file?",
  "url": "/competitions/airbus-ship-detection/discussion/62330",
  "author_name": "",
  "post_date": "2018-07-31T10:41:59.311831Z",
  "votes": 2,
  "comment_count": 5,
  "views": 0,
  "content": "<p>Can you define what Encoded Pixels in the training set are? what do they represent?  </p>",
  "messages": [
    {
      "id": "364341",
      "postDate": "07/31/2018 10:41:59",
      "content": "<p>Can you define what Encoded Pixels in the training set are? what do they represent?  </p>",
      "rawMarkdown": "Can you define what Encoded Pixels in the training set are? what do they represent?",
      "votes": null
    },
    {
      "id": "364630",
      "postDate": "07/31/2018 22:46:17",
      "content": "<p>According to Data Description page: \"The train_ship_segmentations.csv file provides the ground truth (in run-length encoding format) for the training images.\"\nYou can learn about run-length-encoding in general from wikipedia: <a href=\"https://en.wikipedia.org/wiki/Run-length_encoding\">https://en.wikipedia.org/wiki/Run-length_encoding</a>\nThere are some examples on how to read and write run-length-encoding in the kernels of this competition: <a href=\"https://www.kaggle.com/c/airbus-ship-detection/kernels\">https://www.kaggle.com/c/airbus-ship-detection/kernels</a></p>",
      "rawMarkdown": "According to Data Description page: \"The train_ship_segmentations.csv file provides the ground truth (in run-length encoding format) for the training images.\"\nYou can learn about run-length-encoding in general from wikipedia: https://en.wikipedia.org/wiki/Run-length_encoding\nThere are some examples on how to read and write run-length-encoding in the kernels of this competition: https://www.kaggle.com/c/airbus-ship-detection/kernels",
      "votes": null
    },
    {
      "id": "364716",
      "postDate": "08/01/2018 05:22:30",
      "content": "<p>So all the images are zig-zag encoded? or run through x and then y-axis? or 4*4 grid encoded?</p>",
      "rawMarkdown": "So all the images are zig-zag encoded? or run through x and then y-axis? or 4*4 grid encoded?",
      "votes": null
    },
    {
      "id": "383707",
      "postDate": "09/09/2018 12:14:08",
      "content": "<p>Thanks :)</p>",
      "rawMarkdown": "Thanks :)",
      "votes": null
    },
    {
      "id": "386414",
      "postDate": "09/12/2018 20:07:19",
      "content": "<p>Hi Asvini R, </p>\n\n<p>I wrote a kernel explaining the field <code>EncodedPixels</code> in detail: <a href=\"https://www.kaggle.com/julian3833/2-understanding-and-plotting-rle-bounding-boxes\">2 - Understanding and plotting rle bounding boxes</a>. If it's still not clear for you, you can try checking it out.</p>\n\n<p>Hope it helps!</p>",
      "rawMarkdown": "Hi Asvini R, \n\nI wrote a kernel explaining the field `EncodedPixels` in detail: [2 - Understanding and plotting rle bounding boxes](https://www.kaggle.com/julian3833/2-understanding-and-plotting-rle-bounding-boxes). If it's still not clear for you, you can try checking it out.\n\nHope it helps!",
      "votes": null
    },
    {
      "id": "590716",
      "postDate": "08/02/2019 13:53:22",
      "content": "<p>Thanks a ton!</p>",
      "rawMarkdown": "Thanks a ton!",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 364630,
      "author_name": "waskita",
      "author_url": "",
      "post_date": "07/31/2018 22:46:17",
      "content": "<p>According to Data Description page: \"The train_ship_segmentations.csv file provides the ground truth (in run-length encoding format) for the training images.\"\nYou can learn about run-length-encoding in general from wikipedia: <a href=\"https://en.wikipedia.org/wiki/Run-length_encoding\">https://en.wikipedia.org/wiki/Run-length_encoding</a>\nThere are some examples on how to read and write run-length-encoding in the kernels of this competition: <a href=\"https://www.kaggle.com/c/airbus-ship-detection/kernels\">https://www.kaggle.com/c/airbus-ship-detection/kernels</a></p>",
      "votes": null,
      "replies": [
        {
          "id": 383707,
          "author_name": "sehgaldivij",
          "author_url": "",
          "post_date": "09/09/2018 12:14:08",
          "content": "<p>Thanks :)</p>",
          "votes": null,
          "replies": []
        }
      ]
    },
    {
      "id": 364716,
      "author_name": "asvinir3",
      "author_url": "",
      "post_date": "08/01/2018 05:22:30",
      "content": "<p>So all the images are zig-zag encoded? or run through x and then y-axis? or 4*4 grid encoded?</p>",
      "votes": null,
      "replies": []
    },
    {
      "id": 386414,
      "author_name": "julian3833",
      "author_url": "",
      "post_date": "09/12/2018 20:07:19",
      "content": "<p>Hi Asvini R, </p>\n\n<p>I wrote a kernel explaining the field <code>EncodedPixels</code> in detail: <a href=\"https://www.kaggle.com/julian3833/2-understanding-and-plotting-rle-bounding-boxes\">2 - Understanding and plotting rle bounding boxes</a>. If it's still not clear for you, you can try checking it out.</p>\n\n<p>Hope it helps!</p>",
      "votes": null,
      "replies": [
        {
          "id": 590716,
          "author_name": "tejasjojo",
          "author_url": "",
          "post_date": "08/02/2019 13:53:22",
          "content": "<p>Thanks a ton!</p>",
          "votes": null,
          "replies": []
        }
      ]
    }
  ],
  "raw_markdown_by_id": {
    "364341": "Can you define what Encoded Pixels in the training set are? what do they represent?",
    "364630": "According to Data Description page: \"The train_ship_segmentations.csv file provides the ground truth (in run-length encoding format) for the training images.\"\nYou can learn about run-length-encoding in general from wikipedia: https://en.wikipedia.org/wiki/Run-length_encoding\nThere are some examples on how to read and write run-length-encoding in the kernels of this competition: https://www.kaggle.com/c/airbus-ship-detection/kernels",
    "364716": "So all the images are zig-zag encoded? or run through x and then y-axis? or 4*4 grid encoded?",
    "383707": "Thanks :)",
    "386414": "Hi Asvini R, \n\nI wrote a kernel explaining the field `EncodedPixels` in detail: [2 - Understanding and plotting rle bounding boxes](https://www.kaggle.com/julian3833/2-understanding-and-plotting-rle-bounding-boxes). If it's still not clear for you, you can try checking it out.\n\nHope it helps!",
    "590716": "Thanks a ton!"
  },
  "source": "meta"
}