{
  "id": 572892,
  "title": "I need memory",
  "url": "/competitions/birdclef-2025/discussion/572892",
  "author_name": "",
  "post_date": "2025-04-12T03:09:45.105915400Z",
  "votes": 1,
  "comment_count": 4,
  "views": 0,
  "content": "<p>Dear kaggler</p>\n<p>I'm trying an approach where I first convert audio signals into images, save them, and then perform image-based recognition. However, the program stops due to insufficient memory. Has anyone who took the same approach managed to solve this issue? If so, I would really appreciate your help.🤣</p>",
  "messages": [
    {
      "id": "3176975",
      "postDate": "04/12/2025 03:09:45",
      "content": "<p>Dear kaggler</p>\n<p>I'm trying an approach where I first convert audio signals into images, save them, and then perform image-based recognition. However, the program stops due to insufficient memory. Has anyone who took the same approach managed to solve this issue? If so, I would really appreciate your help.🤣</p>",
      "rawMarkdown": "Dear kaggler\n\nI'm trying an approach where I first convert audio signals into images, save them, and then perform image-based recognition. However, the program stops due to insufficient memory. Has anyone who took the same approach managed to solve this issue? If so, I would really appreciate your help.🤣",
      "votes": null
    },
    {
      "id": "3177020",
      "postDate": "04/12/2025 05:33:36",
      "content": "<p>Assume you’re having the issue in a kaggle notebook?     If yes than sharing it offers the best hope of help.   Your question pretty wide ranging right now.   </p>",
      "rawMarkdown": "Assume you’re having the issue in a kaggle notebook?     If yes than sharing it offers the best hope of help.   Your question pretty wide ranging right now.",
      "votes": null
    },
    {
      "id": "3177173",
      "postDate": "04/12/2025 11:22:34",
      "content": "<p>I assume you mean disk space available (not RAM). Try this:</p>\n<ol>\n<li>Lowering image resolutions (you don't need 4k for waveform charts lol).</li>\n<li>Processing in chunks and zipping.<br>\nIf that doesn't help, you may also process train data in several separate notebooks, ofc, and them add them into input in your baseline version etc.</li>\n</ol>\n<p>These approaches might help with RAM situation too though, but you maybe also try garbage collecting etc. after saving chunks of data to the disk space.</p>",
      "rawMarkdown": "I assume you mean disk space available (not RAM). Try this:\n1. Lowering image resolutions (you don't need 4k for waveform charts lol).\n2. Processing in chunks and zipping.\nIf that doesn't help, you may also process train data in several separate notebooks, ofc, and them add them into input in your baseline version etc.\n\nThese approaches might help with RAM situation too though, but you maybe also try garbage collecting etc. after saving chunks of data to the disk space.",
      "votes": null
    },
    {
      "id": "3177303",
      "postDate": "04/12/2025 14:50:21",
      "content": "<p>Sorry for the abstract question. I think I can solve it by using garbage collection to free up memory and stop drawing with matplot.</p>",
      "rawMarkdown": "Sorry for the abstract question. I think I can solve it by using garbage collection to free up memory and stop drawing with matplot.",
      "votes": null
    },
    {
      "id": "3177307",
      "postDate": "04/12/2025 14:53:52",
      "content": "<p>The Kaggle kernel stopped partway through and the program stopped running, so I thought it was due to RAM. However, after applying some techniques like garbage collection, it started working again.</p>",
      "rawMarkdown": "The Kaggle kernel stopped partway through and the program stopped running, so I thought it was due to RAM. However, after applying some techniques like garbage collection, it started working again.",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 3177020,
      "author_name": "pcjimmmy",
      "author_url": "",
      "post_date": "04/12/2025 05:33:36",
      "content": "<p>Assume you’re having the issue in a kaggle notebook?     If yes than sharing it offers the best hope of help.   Your question pretty wide ranging right now.   </p>",
      "votes": null,
      "replies": [
        {
          "id": 3177303,
          "author_name": "cahein1371",
          "author_url": "",
          "post_date": "04/12/2025 14:50:21",
          "content": "<p>Sorry for the abstract question. I think I can solve it by using garbage collection to free up memory and stop drawing with matplot.</p>",
          "votes": null,
          "replies": []
        }
      ]
    },
    {
      "id": 3177173,
      "author_name": "alexandergremyakov",
      "author_url": "",
      "post_date": "04/12/2025 11:22:34",
      "content": "<p>I assume you mean disk space available (not RAM). Try this:</p>\n<ol>\n<li>Lowering image resolutions (you don't need 4k for waveform charts lol).</li>\n<li>Processing in chunks and zipping.<br>\nIf that doesn't help, you may also process train data in several separate notebooks, ofc, and them add them into input in your baseline version etc.</li>\n</ol>\n<p>These approaches might help with RAM situation too though, but you maybe also try garbage collecting etc. after saving chunks of data to the disk space.</p>",
      "votes": null,
      "replies": [
        {
          "id": 3177307,
          "author_name": "cahein1371",
          "author_url": "",
          "post_date": "04/12/2025 14:53:52",
          "content": "<p>The Kaggle kernel stopped partway through and the program stopped running, so I thought it was due to RAM. However, after applying some techniques like garbage collection, it started working again.</p>",
          "votes": null,
          "replies": []
        }
      ]
    }
  ],
  "raw_markdown_by_id": {
    "3176975": "Dear kaggler\n\nI'm trying an approach where I first convert audio signals into images, save them, and then perform image-based recognition. However, the program stops due to insufficient memory. Has anyone who took the same approach managed to solve this issue? If so, I would really appreciate your help.🤣",
    "3177020": "Assume you’re having the issue in a kaggle notebook?     If yes than sharing it offers the best hope of help.   Your question pretty wide ranging right now.",
    "3177173": "I assume you mean disk space available (not RAM). Try this:\n1. Lowering image resolutions (you don't need 4k for waveform charts lol).\n2. Processing in chunks and zipping.\nIf that doesn't help, you may also process train data in several separate notebooks, ofc, and them add them into input in your baseline version etc.\n\nThese approaches might help with RAM situation too though, but you maybe also try garbage collecting etc. after saving chunks of data to the disk space.",
    "3177303": "Sorry for the abstract question. I think I can solve it by using garbage collection to free up memory and stop drawing with matplot.",
    "3177307": "The Kaggle kernel stopped partway through and the program stopped running, so I thought it was due to RAM. However, after applying some techniques like garbage collection, it started working again."
  },
  "source": "meta"
}