{
  "id": 316483,
  "title": "Announcement: DeepMAC segmentation masks are now available!",
  "url": "/competitions/iwildcam2022-fgvc9/discussion/316483",
  "author_name": "",
  "post_date": "2022-04-02T09:01:39.869363300Z",
  "votes": 5,
  "comment_count": 1,
  "views": 0,
  "content": "<p>We have now published DeepMAC segmentation masks for the bounding boxes identified by MegaDetector V4. Data is available on Kaggle and can also be downloaded directly via <a href=\"https://github.com/visipedia/iwildcam_comp#data-downloads\" target=\"_blank\">the competition's GitHub page</a>. We hope these will help you get more insights into the data and build better models.</p>\n<p>We are also providing an updated notebook to visualize the masks: <a href=\"https://www.kaggle.com/stefanistrate/iwildcam-2022-visualize-deepmac-instance-masks\" target=\"_blank\">https://www.kaggle.com/stefanistrate/iwildcam-2022-visualize-deepmac-instance-masks</a></p>\n<p>Happy coding!</p>",
  "messages": [
    {
      "id": "1742756",
      "postDate": "04/02/2022 09:01:39",
      "content": "<p>We have now published DeepMAC segmentation masks for the bounding boxes identified by MegaDetector V4. Data is available on Kaggle and can also be downloaded directly via <a href=\"https://github.com/visipedia/iwildcam_comp#data-downloads\" target=\"_blank\">the competition's GitHub page</a>. We hope these will help you get more insights into the data and build better models.</p>\n<p>We are also providing an updated notebook to visualize the masks: <a href=\"https://www.kaggle.com/stefanistrate/iwildcam-2022-visualize-deepmac-instance-masks\" target=\"_blank\">https://www.kaggle.com/stefanistrate/iwildcam-2022-visualize-deepmac-instance-masks</a></p>\n<p>Happy coding!</p>",
      "rawMarkdown": "We have now published DeepMAC segmentation masks for the bounding boxes identified by MegaDetector V4. Data is available on Kaggle and can also be downloaded directly via [the competition's GitHub page](https://github.com/visipedia/iwildcam_comp#data-downloads). We hope these will help you get more insights into the data and build better models.\n\nWe are also providing an updated notebook to visualize the masks: https://www.kaggle.com/stefanistrate/iwildcam-2022-visualize-deepmac-instance-masks\n\nHappy coding!",
      "votes": null
    },
    {
      "id": "1743966",
      "postDate": "04/03/2022 13:11:34",
      "content": "<p>Thank you for sharing the links !</p>",
      "rawMarkdown": "Thank you for sharing the links !",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 1743966,
      "author_name": "nanditab35",
      "author_url": "",
      "post_date": "04/03/2022 13:11:34",
      "content": "<p>Thank you for sharing the links !</p>",
      "votes": null,
      "replies": []
    }
  ],
  "raw_markdown_by_id": {
    "1742756": "We have now published DeepMAC segmentation masks for the bounding boxes identified by MegaDetector V4. Data is available on Kaggle and can also be downloaded directly via [the competition's GitHub page](https://github.com/visipedia/iwildcam_comp#data-downloads). We hope these will help you get more insights into the data and build better models.\n\nWe are also providing an updated notebook to visualize the masks: https://www.kaggle.com/stefanistrate/iwildcam-2022-visualize-deepmac-instance-masks\n\nHappy coding!",
    "1743966": "Thank you for sharing the links !"
  },
  "source": "meta"
}