{
  "id": 155459,
  "title": "Resized JPG Images: 300x300 & 640x640",
  "url": "/competitions/siim-isic-melanoma-classification/discussion/155459",
  "author_name": "",
  "post_date": "2020-06-01T18:37:04.554741300Z",
  "votes": 11,
  "comment_count": 3,
  "views": 0,
  "content": "<p>Since the JPG images are very large and take a lot of time to load, I have created a resized dataset for test and train JPG images. I have resized images in RGB color space in the following sizes:\n- 300x300\n- 640x640</p>\n\n<p>Dataset: <a href=\"https://www.kaggle.com/bitthal/resize-jpg-siimisic-melanoma-classification\">https://www.kaggle.com/bitthal/resize-jpg-siimisic-melanoma-classification</a></p>\n\n<p>The kernel for creating data dataset with different size:\n<a href=\"https://www.kaggle.com/bitthal/resizing-siim-isic-images\">https://www.kaggle.com/bitthal/resizing-siim-isic-images</a></p>",
  "messages": [
    {
      "id": "870564",
      "postDate": "06/01/2020 18:37:04",
      "content": "<p>Since the JPG images are very large and take a lot of time to load, I have created a resized dataset for test and train JPG images. I have resized images in RGB color space in the following sizes:\n- 300x300\n- 640x640</p>\n\n<p>Dataset: <a href=\"https://www.kaggle.com/bitthal/resize-jpg-siimisic-melanoma-classification\">https://www.kaggle.com/bitthal/resize-jpg-siimisic-melanoma-classification</a></p>\n\n<p>The kernel for creating data dataset with different size:\n<a href=\"https://www.kaggle.com/bitthal/resizing-siim-isic-images\">https://www.kaggle.com/bitthal/resizing-siim-isic-images</a></p>",
      "rawMarkdown": "Since the JPG images are very large and take a lot of time to load, I have created a resized dataset for test and train JPG images. I have resized images in RGB color space in the following sizes:\n- 300x300\n- 640x640\n\nDataset: https://www.kaggle.com/bitthal/resize-jpg-siimisic-melanoma-classification\n\nThe kernel for creating data dataset with different size:\nhttps://www.kaggle.com/bitthal/resizing-siim-isic-images",
      "votes": null
    },
    {
      "id": "870753",
      "postDate": "06/01/2020 22:05:01",
      "content": "<p>Thanks, was thinking of doing that inline, pulling in is easier.</p>",
      "rawMarkdown": "Thanks, was thinking of doing that inline, pulling in is easier.",
      "votes": null
    },
    {
      "id": "871717",
      "postDate": "06/02/2020 15:37:23",
      "content": "<p>Thanks Shubhankar. I uploaded 256x256 as TFRecords with meta data inside <a href=\"https://www.kaggle.com/cdeotte/melanoma-256x256\">here</a> and 512x512 as TFRecords with meta data inside <a href=\"https://www.kaggle.com/cdeotte/melanoma-512x512\">here</a>. We're giving Kagglers lots of size options. (I'm also uploading 768x768 now).</p>",
      "rawMarkdown": "Thanks Shubhankar. I uploaded 256x256 as TFRecords with meta data inside [here][1] and 512x512 as TFRecords with meta data inside [here][2]. We're giving Kagglers lots of size options. (I'm also uploading 768x768 now).\n\n[1]: https://www.kaggle.com/cdeotte/melanoma-256x256\n[2]: https://www.kaggle.com/cdeotte/melanoma-512x512",
      "votes": null
    },
    {
      "id": "873115",
      "postDate": "06/03/2020 19:56:47",
      "content": "<p>512x512 would be alos nice too. Great work</p>",
      "rawMarkdown": "512x512 would be alos nice too. Great work",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 870753,
      "author_name": "meckdahl",
      "author_url": "",
      "post_date": "06/01/2020 22:05:01",
      "content": "<p>Thanks, was thinking of doing that inline, pulling in is easier.</p>",
      "votes": null,
      "replies": []
    },
    {
      "id": 871717,
      "author_name": "cdeotte",
      "author_url": "",
      "post_date": "06/02/2020 15:37:23",
      "content": "<p>Thanks Shubhankar. I uploaded 256x256 as TFRecords with meta data inside <a href=\"https://www.kaggle.com/cdeotte/melanoma-256x256\">here</a> and 512x512 as TFRecords with meta data inside <a href=\"https://www.kaggle.com/cdeotte/melanoma-512x512\">here</a>. We're giving Kagglers lots of size options. (I'm also uploading 768x768 now).</p>",
      "votes": null,
      "replies": []
    },
    {
      "id": 873115,
      "author_name": "awsaf49",
      "author_url": "",
      "post_date": "06/03/2020 19:56:47",
      "content": "<p>512x512 would be alos nice too. Great work</p>",
      "votes": null,
      "replies": []
    }
  ],
  "raw_markdown_by_id": {
    "870564": "Since the JPG images are very large and take a lot of time to load, I have created a resized dataset for test and train JPG images. I have resized images in RGB color space in the following sizes:\n- 300x300\n- 640x640\n\nDataset: https://www.kaggle.com/bitthal/resize-jpg-siimisic-melanoma-classification\n\nThe kernel for creating data dataset with different size:\nhttps://www.kaggle.com/bitthal/resizing-siim-isic-images",
    "870753": "Thanks, was thinking of doing that inline, pulling in is easier.",
    "871717": "Thanks Shubhankar. I uploaded 256x256 as TFRecords with meta data inside [here][1] and 512x512 as TFRecords with meta data inside [here][2]. We're giving Kagglers lots of size options. (I'm also uploading 768x768 now).\n\n[1]: https://www.kaggle.com/cdeotte/melanoma-256x256\n[2]: https://www.kaggle.com/cdeotte/melanoma-512x512",
    "873115": "512x512 would be alos nice too. Great work"
  },
  "source": "meta"
}