{
  "id": 173246,
  "title": "Anyone with tfrecords of Training Dataset ?",
  "url": "/competitions/landmark-retrieval-2020/discussion/173246",
  "author_name": "",
  "post_date": "2020-08-08T13:09:42.474342900Z",
  "votes": 3,
  "comment_count": 1,
  "views": 0,
  "content": "<p>Hi everyone. I am following the training pipeline from this link to beat the baseline.  It creates the tfrecords of training and the validation datasets which take about 12 hours and 500 GB of space. I am just curious has anyone tried it and created the tfrecords ? If yes. Are they willing to share them cause this will make the competition more accessible for people.Thanks </p>\n<p><a href=\"https://github.com/tensorflow/models/blob/master/research/delf/delf/python/training/README.md\" target=\"_blank\">https://github.com/tensorflow/models/blob/master/research/delf/delf/python/training/README.md</a></p>",
  "messages": [
    {
      "id": "962820",
      "postDate": "08/08/2020 13:09:42",
      "content": "<p>Hi everyone. I am following the training pipeline from this link to beat the baseline.  It creates the tfrecords of training and the validation datasets which take about 12 hours and 500 GB of space. I am just curious has anyone tried it and created the tfrecords ? If yes. Are they willing to share them cause this will make the competition more accessible for people.Thanks </p>\n<p><a href=\"https://github.com/tensorflow/models/blob/master/research/delf/delf/python/training/README.md\" target=\"_blank\">https://github.com/tensorflow/models/blob/master/research/delf/delf/python/training/README.md</a></p>",
      "rawMarkdown": "Hi everyone. I am following the training pipeline from this link to beat the baseline.  It creates the tfrecords of training and the validation datasets which take about 12 hours and 500 GB of space. I am just curious has anyone tried it and created the tfrecords ? If yes. Are they willing to share them cause this will make the competition more accessible for people.Thanks \n\n\nhttps://github.com/tensorflow/models/blob/master/research/delf/delf/python/training/README.md",
      "votes": null
    },
    {
      "id": "964410",
      "postDate": "08/09/2020 20:40:50",
      "content": "<p><a href=\"https://www.kaggle.com/c/landmark-retrieval-2020/discussion/173572\">https://www.kaggle.com/c/landmark-retrieval-2020/discussion/173572</a></p>",
      "rawMarkdown": "https://www.kaggle.com/c/landmark-retrieval-2020/discussion/173572",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 964410,
      "author_name": "chandanverma",
      "author_url": "",
      "post_date": "08/09/2020 20:40:50",
      "content": "<p><a href=\"https://www.kaggle.com/c/landmark-retrieval-2020/discussion/173572\">https://www.kaggle.com/c/landmark-retrieval-2020/discussion/173572</a></p>",
      "votes": null,
      "replies": []
    }
  ],
  "raw_markdown_by_id": {
    "962820": "Hi everyone. I am following the training pipeline from this link to beat the baseline.  It creates the tfrecords of training and the validation datasets which take about 12 hours and 500 GB of space. I am just curious has anyone tried it and created the tfrecords ? If yes. Are they willing to share them cause this will make the competition more accessible for people.Thanks \n\n\nhttps://github.com/tensorflow/models/blob/master/research/delf/delf/python/training/README.md",
    "964410": "https://www.kaggle.com/c/landmark-retrieval-2020/discussion/173572"
  },
  "source": "meta"
}