{
  "id": 685852,
  "title": "🌿 Plant Disease Model Zoo: Predict in Seconds (No Training Needed)",
  "url": "/competitions/plant-pathology-2021-fgvc8/discussion/685852",
  "author_name": "Subham Divakar",
  "post_date": "2026-03-29T10:24:32.742000",
  "votes": 0,
  "comment_count": 0,
  "views": 0,
  "content": "<p>Hey Kaggle community 👋</p>\n<p>I wanted to share something I’ve been working on for quite some time.</p>\n<p><a href=\"https://www.kaggle.com/code/shubhamdivakar/plant-disease-model-zoo-one-library-100-models\" target=\"_blank\">https://www.kaggle.com/code/shubhamdivakar/plant-disease-model-zoo-one-library-100-models</a></p>\n<p>For the past 5+ years, I’ve been exploring plant disease detection using deep learning—starting from my college days as a personal learning journey, and continuing alongside my work as a full-time software engineer with active research interests.</p>\n<p>One major problem I kept facing (and I’m sure many of you did too):</p>\n<p>❗ Every project starts from scratch — training models, preprocessing, benchmarking…</p>\n<p>So I built a solution 👇</p>\n<p>🌱 Introducing: Plant Disease Model Zoo</p>\n<p>👉 Kaggle Notebook: (<a href=\"https://www.kaggle.com/code/shubhamdivakar/plant-disease-model-zoo-one-library-100-models\" target=\"_blank\">https://www.kaggle.com/code/shubhamdivakar/plant-disease-model-zoo-one-library-100-models</a>)\n👉 GitHub: <a href=\"https://github.com/shubham10divakar/plantdoc-predictor\" target=\"_blank\">https://github.com/shubham10divakar/plantdoc-predictor</a></p>\n<p>👉 PyPI: <a href=\"https://pypi.org/project/plantdoc-predictor/\" target=\"_blank\">https://pypi.org/project/plantdoc-predictor/</a></p>\n<p>🔥 What this does\n✅ State of Art pretrained plant disease models\n⚡ Plug-and-play (no training required)\n🧠 Feature extraction for research\n🔬 Supports experimentation &amp; benchmarking</p>\n<p>👉 Think of it as a Model Zoo specifically for plant disease detection\nYou can add you model here too, go to github and contribute</p>",
  "messages": [
    {
      "id": 3431047,
      "postDate": "2026-03-29T10:24:32.743Z",
      "content": "<p>Hey Kaggle community 👋</p>\n<p>I wanted to share something I’ve been working on for quite some time.</p>\n<p><a href=\"https://www.kaggle.com/code/shubhamdivakar/plant-disease-model-zoo-one-library-100-models\" target=\"_blank\">https://www.kaggle.com/code/shubhamdivakar/plant-disease-model-zoo-one-library-100-models</a></p>\n<p>For the past 5+ years, I’ve been exploring plant disease detection using deep learning—starting from my college days as a personal learning journey, and continuing alongside my work as a full-time software engineer with active research interests.</p>\n<p>One major problem I kept facing (and I’m sure many of you did too):</p>\n<p>❗ Every project starts from scratch — training models, preprocessing, benchmarking…</p>\n<p>So I built a solution 👇</p>\n<p>🌱 Introducing: Plant Disease Model Zoo</p>\n<p>👉 Kaggle Notebook: (<a href=\"https://www.kaggle.com/code/shubhamdivakar/plant-disease-model-zoo-one-library-100-models\" target=\"_blank\">https://www.kaggle.com/code/shubhamdivakar/plant-disease-model-zoo-one-library-100-models</a>)\n👉 GitHub: <a href=\"https://github.com/shubham10divakar/plantdoc-predictor\" target=\"_blank\">https://github.com/shubham10divakar/plantdoc-predictor</a></p>\n<p>👉 PyPI: <a href=\"https://pypi.org/project/plantdoc-predictor/\" target=\"_blank\">https://pypi.org/project/plantdoc-predictor/</a></p>\n<p>🔥 What this does\n✅ State of Art pretrained plant disease models\n⚡ Plug-and-play (no training required)\n🧠 Feature extraction for research\n🔬 Supports experimentation &amp; benchmarking</p>\n<p>👉 Think of it as a Model Zoo specifically for plant disease detection\nYou can add you model here too, go to github and contribute</p>",
      "rawMarkdown": "Hey Kaggle community 👋\n\nI wanted to share something I’ve been working on for quite some time.\n\nhttps://www.kaggle.com/code/shubhamdivakar/plant-disease-model-zoo-one-library-100-models\n\nFor the past 5+ years, I’ve been exploring plant disease detection using deep learning—starting from my college days as a personal learning journey, and continuing alongside my work as a full-time software engineer with active research interests.\n\nOne major problem I kept facing (and I’m sure many of you did too):\n\n❗ Every project starts from scratch — training models, preprocessing, benchmarking…\n\nSo I built a solution 👇\n\n🌱 Introducing: Plant Disease Model Zoo\n\n👉 Kaggle Notebook: (https://www.kaggle.com/code/shubhamdivakar/plant-disease-model-zoo-one-library-100-models)\n👉 GitHub: https://github.com/shubham10divakar/plantdoc-predictor\n\n👉 PyPI: https://pypi.org/project/plantdoc-predictor/\n\n🔥 What this does\n✅ State of Art pretrained plant disease models\n⚡ Plug-and-play (no training required)\n🧠 Feature extraction for research\n🔬 Supports experimentation & benchmarking\n\n👉 Think of it as a Model Zoo specifically for plant disease detection\nYou can add you model here too, go to github and contribute"
    }
  ],
  "comments": [],
  "raw_markdown_by_id": {
    "3431047": "Hey Kaggle community 👋\n\nI wanted to share something I’ve been working on for quite some time.\n\nhttps://www.kaggle.com/code/shubhamdivakar/plant-disease-model-zoo-one-library-100-models\n\nFor the past 5+ years, I’ve been exploring plant disease detection using deep learning—starting from my college days as a personal learning journey, and continuing alongside my work as a full-time software engineer with active research interests.\n\nOne major problem I kept facing (and I’m sure many of you did too):\n\n❗ Every project starts from scratch — training models, preprocessing, benchmarking…\n\nSo I built a solution 👇\n\n🌱 Introducing: Plant Disease Model Zoo\n\n👉 Kaggle Notebook: (https://www.kaggle.com/code/shubhamdivakar/plant-disease-model-zoo-one-library-100-models)\n👉 GitHub: https://github.com/shubham10divakar/plantdoc-predictor\n\n👉 PyPI: https://pypi.org/project/plantdoc-predictor/\n\n🔥 What this does\n✅ State of Art pretrained plant disease models\n⚡ Plug-and-play (no training required)\n🧠 Feature extraction for research\n🔬 Supports experimentation & benchmarking\n\n👉 Think of it as a Model Zoo specifically for plant disease detection\nYou can add you model here too, go to github and contribute"
  }
}