{
  "id": 157756,
  "title": "DarkNet Pytorch model for PANDA competition",
  "url": "/competitions/prostate-cancer-grade-assessment/discussion/157756",
  "author_name": "Tasnim Nishat Islam",
  "post_date": "2020-06-11T23:24:10.964000",
  "votes": 1,
  "comment_count": 0,
  "views": 0,
  "content": "<p>Find the script file: <a href=\"https://www.kaggle.com/tasnimnishatislam/dnmodelmanami-py\">https://www.kaggle.com/tasnimnishatislam/dnmodelmanami-py</a>\nInput data to run the script file:\n<a href=\"https://www.kaggle.com/tasnimnishatislam/gleasonyolo\">https://www.kaggle.com/tasnimnishatislam/gleasonyolo</a></p>\n\n<p>Get the intuition from:\n<a href=\"https://www.youtube.com/watch?v=yE2iDYuPxzc&amp;t=42s\">https://www.youtube.com/watch?v=yE2iDYuPxzc&amp;t=42s</a>\n<a href=\"https://www.youtube.com/watch?v=lTBFIwSGxrY&amp;t=1s\">https://www.youtube.com/watch?v=lTBFIwSGxrY&amp;t=1s</a></p>\n\n<ol>\n<li>The whole model was written following the video tutorial(<a href=\"https://www.youtube.com/watch?v=lTBFIwSGxrY&amp;t=1s\">link</a>)</li>\n<li>yolo3.weights downloaded from <a href=\"https://pjreddie.com/darknet/yolo/\">YOLO official website</a></li>\n<li>In the cfg file, \nin total 3 [yolo], classes = n (number of classes: here 6(0-5))\nin previous layer of each [yolo], filters = [4+1+(n = 6)]*3 = 33</li>\n<li>in the data file, \"gleason.names\" was added listing the class names, (named them 0-5)</li>\n<li>Then it was tested on some randomly generated test data</li>\n</ol>\n\n<p>Hope to soon upgrade the version of the main script!</p>",
  "messages": [
    {
      "id": 882562,
      "postDate": "2020-06-11T23:24:10.963Z",
      "content": "<p>Find the script file: <a href=\"https://www.kaggle.com/tasnimnishatislam/dnmodelmanami-py\">https://www.kaggle.com/tasnimnishatislam/dnmodelmanami-py</a>\nInput data to run the script file:\n<a href=\"https://www.kaggle.com/tasnimnishatislam/gleasonyolo\">https://www.kaggle.com/tasnimnishatislam/gleasonyolo</a></p>\n\n<p>Get the intuition from:\n<a href=\"https://www.youtube.com/watch?v=yE2iDYuPxzc&amp;t=42s\">https://www.youtube.com/watch?v=yE2iDYuPxzc&amp;t=42s</a>\n<a href=\"https://www.youtube.com/watch?v=lTBFIwSGxrY&amp;t=1s\">https://www.youtube.com/watch?v=lTBFIwSGxrY&amp;t=1s</a></p>\n\n<ol>\n<li>The whole model was written following the video tutorial(<a href=\"https://www.youtube.com/watch?v=lTBFIwSGxrY&amp;t=1s\">link</a>)</li>\n<li>yolo3.weights downloaded from <a href=\"https://pjreddie.com/darknet/yolo/\">YOLO official website</a></li>\n<li>In the cfg file, \nin total 3 [yolo], classes = n (number of classes: here 6(0-5))\nin previous layer of each [yolo], filters = [4+1+(n = 6)]*3 = 33</li>\n<li>in the data file, \"gleason.names\" was added listing the class names, (named them 0-5)</li>\n<li>Then it was tested on some randomly generated test data</li>\n</ol>\n\n<p>Hope to soon upgrade the version of the main script!</p>",
      "rawMarkdown": "Find the script file: https://www.kaggle.com/tasnimnishatislam/dnmodelmanami-py\nInput data to run the script file:\nhttps://www.kaggle.com/tasnimnishatislam/gleasonyolo\n\nGet the intuition from:\nhttps://www.youtube.com/watch?v=yE2iDYuPxzc&amp;t=42s\nhttps://www.youtube.com/watch?v=lTBFIwSGxrY&amp;t=1s\n\n1. The whole model was written following the video tutorial([link](https://www.youtube.com/watch?v=lTBFIwSGxrY&amp;t=1s))\n2. yolo3.weights downloaded from [YOLO official website](https://pjreddie.com/darknet/yolo/)\n3. In the cfg file, \nin total 3 [yolo], classes = n (number of classes: here 6(0-5))\nin previous layer of each [yolo], filters = [4+1+(n = 6)]*3 = 33\n4. in the data file, \"gleason.names\" was added listing the class names, (named them 0-5)\n5. Then it was tested on some randomly generated test data\n\nHope to soon upgrade the version of the main script!\n\n\n",
      "votes": 1
    }
  ],
  "comments": [],
  "raw_markdown_by_id": {
    "882562": "Find the script file: https://www.kaggle.com/tasnimnishatislam/dnmodelmanami-py\nInput data to run the script file:\nhttps://www.kaggle.com/tasnimnishatislam/gleasonyolo\n\nGet the intuition from:\nhttps://www.youtube.com/watch?v=yE2iDYuPxzc&amp;t=42s\nhttps://www.youtube.com/watch?v=lTBFIwSGxrY&amp;t=1s\n\n1. The whole model was written following the video tutorial([link](https://www.youtube.com/watch?v=lTBFIwSGxrY&amp;t=1s))\n2. yolo3.weights downloaded from [YOLO official website](https://pjreddie.com/darknet/yolo/)\n3. In the cfg file, \nin total 3 [yolo], classes = n (number of classes: here 6(0-5))\nin previous layer of each [yolo], filters = [4+1+(n = 6)]*3 = 33\n4. in the data file, \"gleason.names\" was added listing the class names, (named them 0-5)\n5. Then it was tested on some randomly generated test data\n\nHope to soon upgrade the version of the main script!\n\n\n"
  }
}