{
  "id": 94649,
  "title": "[0.3-3GB] Re-sized and compressed test data-set (512x, 256x, 128x)",
  "url": "/competitions/open-images-2019-visual-relationship/discussion/94649",
  "author_name": "Anish Agnihotri",
  "post_date": "2019-06-05T23:51:59.048000",
  "votes": 17,
  "comment_count": 1,
  "views": 0,
  "content": "<p><strong>Why download 9.7GB when you can download ~400MB?</strong> <em>Hooray</em></p>\n\n<p>Hey everyone,</p>\n\n<p>It looks like this is another one of those competitions with giant data-sets. In order to make it easier for everyone to compete, I am going to be re-sizing the <code>train</code>, <code>validation</code>, and <code>testing</code> data for the competition (for people who have limited download bandwidth or resources. I'm starting by sharing various sizes of the <code>testing</code> data-set, with more coming soon.</p>\n\n<p><strong>Note:</strong> These dimensions are not proportional, since the images are not exact squares. If there is demand for a forced-proportional data-set, I'd be happy to share that as well.</p>\n\n<h1>Downloads</h1>\n\n<p><strong>Original data-set</strong>\nUncompressed size: <code>~20GB</code></p>\n\n<p><strong><code>512x</code> data-set</strong>\nUncompressed size: <code>3.4GB</code>\nDownload link: <a href=\"https://drive.google.com/file/d/15AATyBwhP45GXd2CquVtFoNgsRldMG9z/view?usp=sharing\">Drive</a></p>\n\n<p><strong><code>256x</code> data-set</strong>\nUncompressed size: <code>1.2GB</code>\nDownload link: <a href=\"https://drive.google.com/file/d/1vlxh1mqmXL3GT_FQ3FwG9WpeHAfTF62u/view?usp=sharing\">Drive</a></p>\n\n<p><strong><code>128x</code> data-set</strong>\nUncompressed size: <code>~480MB</code>\nDownload link: <a href=\"https://drive.google.com/file/d/1LTkg1OLORQx7rKm_X-Etz-Ck-ayiKSD6/view?usp=sharing\">Drive</a></p>\n\n<h1>Additional information</h1>\n\n<p>For <a href=\"https://www.kaggle.com/c/landmark-recognition-2019/discussion/91770\">process, limitations, and specific download instructions</a> (if you're using a CLI, these might be easier), please refer to the post I made for the last competition of this sort. The instructions are the same.</p>\n\n<p>Cheers!</p>\n\n<p>Anish</p>",
  "messages": [
    {
      "id": 544823,
      "postDate": "2019-06-05T23:51:59.050Z",
      "content": "<p><strong>Why download 9.7GB when you can download ~400MB?</strong> <em>Hooray</em></p>\n\n<p>Hey everyone,</p>\n\n<p>It looks like this is another one of those competitions with giant data-sets. In order to make it easier for everyone to compete, I am going to be re-sizing the <code>train</code>, <code>validation</code>, and <code>testing</code> data for the competition (for people who have limited download bandwidth or resources. I'm starting by sharing various sizes of the <code>testing</code> data-set, with more coming soon.</p>\n\n<p><strong>Note:</strong> These dimensions are not proportional, since the images are not exact squares. If there is demand for a forced-proportional data-set, I'd be happy to share that as well.</p>\n\n<h1>Downloads</h1>\n\n<p><strong>Original data-set</strong>\nUncompressed size: <code>~20GB</code></p>\n\n<p><strong><code>512x</code> data-set</strong>\nUncompressed size: <code>3.4GB</code>\nDownload link: <a href=\"https://drive.google.com/file/d/15AATyBwhP45GXd2CquVtFoNgsRldMG9z/view?usp=sharing\">Drive</a></p>\n\n<p><strong><code>256x</code> data-set</strong>\nUncompressed size: <code>1.2GB</code>\nDownload link: <a href=\"https://drive.google.com/file/d/1vlxh1mqmXL3GT_FQ3FwG9WpeHAfTF62u/view?usp=sharing\">Drive</a></p>\n\n<p><strong><code>128x</code> data-set</strong>\nUncompressed size: <code>~480MB</code>\nDownload link: <a href=\"https://drive.google.com/file/d/1LTkg1OLORQx7rKm_X-Etz-Ck-ayiKSD6/view?usp=sharing\">Drive</a></p>\n\n<h1>Additional information</h1>\n\n<p>For <a href=\"https://www.kaggle.com/c/landmark-recognition-2019/discussion/91770\">process, limitations, and specific download instructions</a> (if you're using a CLI, these might be easier), please refer to the post I made for the last competition of this sort. The instructions are the same.</p>\n\n<p>Cheers!</p>\n\n<p>Anish</p>",
      "rawMarkdown": "**Why download 9.7GB when you can download ~400MB?** *Hooray*\n\nHey everyone,\n\nIt looks like this is another one of those competitions with giant data-sets. In order to make it easier for everyone to compete, I am going to be re-sizing the `train`, `validation`, and `testing` data for the competition (for people who have limited download bandwidth or resources. I'm starting by sharing various sizes of the `testing` data-set, with more coming soon.\n\n**Note:** These dimensions are not proportional, since the images are not exact squares. If there is demand for a forced-proportional data-set, I'd be happy to share that as well.\n\n# Downloads\n\n**Original data-set**\nUncompressed size: `~20GB`\n\n**`512x` data-set**\nUncompressed size: `3.4GB`\nDownload link: [Drive](https://drive.google.com/file/d/15AATyBwhP45GXd2CquVtFoNgsRldMG9z/view?usp=sharing)\n\n**`256x` data-set**\nUncompressed size: `1.2GB`\nDownload link: [Drive](https://drive.google.com/file/d/1vlxh1mqmXL3GT_FQ3FwG9WpeHAfTF62u/view?usp=sharing)\n\n**`128x` data-set**\nUncompressed size: `~480MB`\nDownload link: [Drive](https://drive.google.com/file/d/1LTkg1OLORQx7rKm_X-Etz-Ck-ayiKSD6/view?usp=sharing)\n\n# Additional information\nFor [process, limitations, and specific download instructions](https://www.kaggle.com/c/landmark-recognition-2019/discussion/91770) (if you're using a CLI, these might be easier), please refer to the post I made for the last competition of this sort. The instructions are the same.\n\nCheers!\n\nAnish\n\n",
      "votes": 17
    },
    {
      "id": 569616,
      "postDate": "2019-07-07T02:57:24.903Z",
      "rawMarkdown": "",
      "isDeleted": true
    }
  ],
  "comments": [
    {
      "id": 569616,
      "author_name": "",
      "author_url": "",
      "post_date": "2019-07-07T02:57:24.903000",
      "content": "",
      "votes": 0,
      "replies": []
    }
  ],
  "raw_markdown_by_id": {
    "544823": "**Why download 9.7GB when you can download ~400MB?** *Hooray*\n\nHey everyone,\n\nIt looks like this is another one of those competitions with giant data-sets. In order to make it easier for everyone to compete, I am going to be re-sizing the `train`, `validation`, and `testing` data for the competition (for people who have limited download bandwidth or resources. I'm starting by sharing various sizes of the `testing` data-set, with more coming soon.\n\n**Note:** These dimensions are not proportional, since the images are not exact squares. If there is demand for a forced-proportional data-set, I'd be happy to share that as well.\n\n# Downloads\n\n**Original data-set**\nUncompressed size: `~20GB`\n\n**`512x` data-set**\nUncompressed size: `3.4GB`\nDownload link: [Drive](https://drive.google.com/file/d/15AATyBwhP45GXd2CquVtFoNgsRldMG9z/view?usp=sharing)\n\n**`256x` data-set**\nUncompressed size: `1.2GB`\nDownload link: [Drive](https://drive.google.com/file/d/1vlxh1mqmXL3GT_FQ3FwG9WpeHAfTF62u/view?usp=sharing)\n\n**`128x` data-set**\nUncompressed size: `~480MB`\nDownload link: [Drive](https://drive.google.com/file/d/1LTkg1OLORQx7rKm_X-Etz-Ck-ayiKSD6/view?usp=sharing)\n\n# Additional information\nFor [process, limitations, and specific download instructions](https://www.kaggle.com/c/landmark-recognition-2019/discussion/91770) (if you're using a CLI, these might be easier), please refer to the post I made for the last competition of this sort. The instructions are the same.\n\nCheers!\n\nAnish\n\n",
    "569616": ""
  }
}