{
  "id": 214819,
  "title": "something maybe useful",
  "url": "/competitions/cassava-leaf-disease-classification/discussion/214819",
  "author_name": "DarknessZX",
  "post_date": "2021-01-27T18:03:26.499000",
  "votes": 11,
  "comment_count": 7,
  "views": 0,
  "content": "<p>1.Noise label<br>\n <a href=\"https://github.com/haochenglouis/cores\" target=\"_blank\">https://github.com/haochenglouis/cores</a></p>\n<p>2.label balance<br>\n<a href=\"https://github.com/blackfeather-wang/ISDA-for-Deep-Networks/blob/master/Image%20classification%20on%20CIFAR/ISDA.py\" target=\"_blank\">https://github.com/blackfeather-wang/ISDA-for-Deep-Networks/blob/master/Image%20classification%20on%20CIFAR/ISDA.py</a></p>\n<p><a href=\"https://github.com/unique-chan/Complement-Cross-Entropy\" target=\"_blank\">https://github.com/unique-chan/Complement-Cross-Entropy</a></p>\n<p>3.2019+2020dataset<br>\n<a href=\"https://www.kaggle.com/tahsin/cassava-leaf-disease-merged\" target=\"_blank\">https://www.kaggle.com/tahsin/cassava-leaf-disease-merged</a></p>",
  "messages": [
    {
      "id": 1173187,
      "postDate": "2021-01-27T18:03:26.500Z",
      "content": "<p>1.Noise label<br>\n <a href=\"https://github.com/haochenglouis/cores\" target=\"_blank\">https://github.com/haochenglouis/cores</a></p>\n<p>2.label balance<br>\n<a href=\"https://github.com/blackfeather-wang/ISDA-for-Deep-Networks/blob/master/Image%20classification%20on%20CIFAR/ISDA.py\" target=\"_blank\">https://github.com/blackfeather-wang/ISDA-for-Deep-Networks/blob/master/Image%20classification%20on%20CIFAR/ISDA.py</a></p>\n<p><a href=\"https://github.com/unique-chan/Complement-Cross-Entropy\" target=\"_blank\">https://github.com/unique-chan/Complement-Cross-Entropy</a></p>\n<p>3.2019+2020dataset<br>\n<a href=\"https://www.kaggle.com/tahsin/cassava-leaf-disease-merged\" target=\"_blank\">https://www.kaggle.com/tahsin/cassava-leaf-disease-merged</a></p>",
      "rawMarkdown": "1.Noise label\n https://github.com/haochenglouis/cores\n\n2.label balance\nhttps://github.com/blackfeather-wang/ISDA-for-Deep-Networks/blob/master/Image%20classification%20on%20CIFAR/ISDA.py\n\nhttps://github.com/unique-chan/Complement-Cross-Entropy\n\n3.2019+2020dataset\nhttps://www.kaggle.com/tahsin/cassava-leaf-disease-merged",
      "votes": 11
    },
    {
      "id": 1174208,
      "postDate": "2021-01-28T10:43:29.717Z",
      "content": "<p>If anyone wants to use tfrecords for the merged data :)<br>\n<a href=\"https://www.kaggle.com/ashish2001/20192020-merged-tfrecords-512x512/code\" target=\"_blank\">https://www.kaggle.com/ashish2001/20192020-merged-tfrecords-512x512/code</a></p>",
      "rawMarkdown": "If anyone wants to use tfrecords for the merged data :)\nhttps://www.kaggle.com/ashish2001/20192020-merged-tfrecords-512x512/code",
      "votes": 2,
      "replies": [
        {
          "id": 1174737,
          "postDate": "2021-01-28T17:03:38.517Z",
          "content": "<p>good job！！</p>",
          "rawMarkdown": "good job！！",
          "votes": 1,
          "replies": [
            {
              "id": 2456538,
              "postDate": "2023-09-26T09:02:48.143Z",
              "rawMarkdown": "",
              "isDeleted": true
            }
          ]
        }
      ]
    },
    {
      "id": 1184442,
      "postDate": "2021-02-03T14:28:45.487Z",
      "content": "<p>Have you tried these thins already? Which one is helpful , Thanks!</p>",
      "rawMarkdown": "Have you tried these thins already? Which one is helpful , Thanks!",
      "replies": [
        {
          "id": 1185862,
          "postDate": "2021-02-04T12:38:02.330Z",
          "content": "<p>3&amp;2 are useful</p>",
          "rawMarkdown": "3&2 are useful"
        }
      ]
    },
    {
      "id": 1173563,
      "postDate": "2021-01-28T00:44:59.420Z",
      "content": "<p>Thanks for sharing! +upvoted :) I'm using 2019+2020 dataset and it is really good. The easiest way to load 2019 dataset to notebooks. I'll try out all of these.</p>",
      "rawMarkdown": "Thanks for sharing! +upvoted :) I'm using 2019+2020 dataset and it is really good. The easiest way to load 2019 dataset to notebooks. I'll try out all of these.",
      "replies": [
        {
          "id": 1173919,
          "postDate": "2021-01-28T07:08:57.570Z",
          "content": "<p>congratulations！😁</p>",
          "rawMarkdown": "congratulations！😁"
        }
      ]
    }
  ],
  "comments": [
    {
      "id": 1174208,
      "author_name": "Ashish Goswami",
      "author_url": "",
      "post_date": "2021-01-28T10:43:29.717000",
      "content": "<p>If anyone wants to use tfrecords for the merged data :)<br>\n<a href=\"https://www.kaggle.com/ashish2001/20192020-merged-tfrecords-512x512/code\" target=\"_blank\">https://www.kaggle.com/ashish2001/20192020-merged-tfrecords-512x512/code</a></p>",
      "votes": 2,
      "replies": [
        {
          "id": 1174737,
          "author_name": "DarknessZX",
          "author_url": "",
          "post_date": "2021-01-28T17:03:38.517000",
          "content": "<p>good job！！</p>",
          "votes": 1,
          "replies": [
            {
              "id": 2456538,
              "author_name": "",
              "author_url": "",
              "post_date": "2023-09-26T09:02:48.143000",
              "content": "",
              "votes": 0,
              "replies": []
            }
          ]
        }
      ]
    },
    {
      "id": 1184442,
      "author_name": "xsg",
      "author_url": "",
      "post_date": "2021-02-03T14:28:45.487000",
      "content": "<p>Have you tried these thins already? Which one is helpful , Thanks!</p>",
      "votes": 0,
      "replies": [
        {
          "id": 1185862,
          "author_name": "DarknessZX",
          "author_url": "",
          "post_date": "2021-02-04T12:38:02.330000",
          "content": "<p>3&amp;2 are useful</p>",
          "votes": 0,
          "replies": []
        }
      ]
    },
    {
      "id": 1173563,
      "author_name": "Dongkyu Kim",
      "author_url": "",
      "post_date": "2021-01-28T00:44:59.420000",
      "content": "<p>Thanks for sharing! +upvoted :) I'm using 2019+2020 dataset and it is really good. The easiest way to load 2019 dataset to notebooks. I'll try out all of these.</p>",
      "votes": 0,
      "replies": [
        {
          "id": 1173919,
          "author_name": "DarknessZX",
          "author_url": "",
          "post_date": "2021-01-28T07:08:57.570000",
          "content": "<p>congratulations！😁</p>",
          "votes": 0,
          "replies": []
        }
      ]
    }
  ],
  "raw_markdown_by_id": {
    "1173187": "1.Noise label\n https://github.com/haochenglouis/cores\n\n2.label balance\nhttps://github.com/blackfeather-wang/ISDA-for-Deep-Networks/blob/master/Image%20classification%20on%20CIFAR/ISDA.py\n\nhttps://github.com/unique-chan/Complement-Cross-Entropy\n\n3.2019+2020dataset\nhttps://www.kaggle.com/tahsin/cassava-leaf-disease-merged",
    "1174208": "If anyone wants to use tfrecords for the merged data :)\nhttps://www.kaggle.com/ashish2001/20192020-merged-tfrecords-512x512/code",
    "1184442": "Have you tried these thins already? Which one is helpful , Thanks!",
    "1173563": "Thanks for sharing! +upvoted :) I'm using 2019+2020 dataset and it is really good. The easiest way to load 2019 dataset to notebooks. I'll try out all of these."
  }
}