{
  "id": 178872,
  "title": "Beginner Notebook on Image Preprocessing Techniques",
  "url": "/competitions/digit-recognizer/discussion/178872",
  "author_name": "Nathan Zhong",
  "post_date": "2020-08-31T17:12:37.109000",
  "votes": 4,
  "comment_count": 4,
  "views": null,
  "content": "<p>Hello everyone. I have just published an <a href=\"https://www.kaggle.com/nzhongahtan/simple-preprocessing-techinques-using-minst-data\" target=\"_blank\">Image Preprocessing Notebook</a> that shows how different preprocessing techniques are used on the MINST digit dataset. I explain what each technique is and what effect it has on the image. The code is simple to follow and gives straightforward examples as to how to implement these techniques. I cover:</p>\n<ul>\n<li>Normalization</li>\n<li>Averaging</li>\n<li>Gaussian Filtering</li>\n<li>Median Filtering</li>\n<li>Bilateral Filtering</li>\n<li>Dilation</li>\n<li>Erosion</li>\n<li>Opening and Closing</li>\n<li>Edge Sharpening</li>\n</ul>\n<p>Check it out <a href=\"https://www.kaggle.com/nzhongahtan/simple-preprocessing-techinques-using-minst-data\" target=\"_blank\">here</a> and feel free to leave comments on improvements or questions. If you found this helpful, it would be greatly appreciated if you could upvote this notebook. Thank you!</p>",
  "messages": [
    {
      "id": 993135,
      "postDate": "2020-08-31T17:12:37.110Z",
      "content": "<p>Hello everyone. I have just published an <a href=\"https://www.kaggle.com/nzhongahtan/simple-preprocessing-techinques-using-minst-data\" target=\"_blank\">Image Preprocessing Notebook</a> that shows how different preprocessing techniques are used on the MINST digit dataset. I explain what each technique is and what effect it has on the image. The code is simple to follow and gives straightforward examples as to how to implement these techniques. I cover:</p>\n<ul>\n<li>Normalization</li>\n<li>Averaging</li>\n<li>Gaussian Filtering</li>\n<li>Median Filtering</li>\n<li>Bilateral Filtering</li>\n<li>Dilation</li>\n<li>Erosion</li>\n<li>Opening and Closing</li>\n<li>Edge Sharpening</li>\n</ul>\n<p>Check it out <a href=\"https://www.kaggle.com/nzhongahtan/simple-preprocessing-techinques-using-minst-data\" target=\"_blank\">here</a> and feel free to leave comments on improvements or questions. If you found this helpful, it would be greatly appreciated if you could upvote this notebook. Thank you!</p>",
      "rawMarkdown": "Hello everyone. I have just published an [Image Preprocessing Notebook](https://www.kaggle.com/nzhongahtan/simple-preprocessing-techinques-using-minst-data) that shows how different preprocessing techniques are used on the MINST digit dataset. I explain what each technique is and what effect it has on the image. The code is simple to follow and gives straightforward examples as to how to implement these techniques. I cover:\n\n- Normalization\n- Averaging\n- Gaussian Filtering\n- Median Filtering\n- Bilateral Filtering\n- Dilation\n- Erosion\n- Opening and Closing\n- Edge Sharpening\n\nCheck it out [here](https://www.kaggle.com/nzhongahtan/simple-preprocessing-techinques-using-minst-data) and feel free to leave comments on improvements or questions. If you found this helpful, it would be greatly appreciated if you could upvote this notebook. Thank you!",
      "votes": 4
    },
    {
      "id": 993316,
      "postDate": "2020-08-31T20:42:09.763Z",
      "content": "<p>Awesome, very clear and well documented! Upvoted 👍</p>",
      "rawMarkdown": "Awesome, very clear and well documented! Upvoted 👍",
      "votes": 1,
      "replies": [
        {
          "id": 993360,
          "postDate": "2020-08-31T21:30:16.020Z",
          "content": "<p>Thank you!</p>",
          "rawMarkdown": "Thank you!",
          "votes": 2
        }
      ]
    },
    {
      "id": 993224,
      "postDate": "2020-08-31T18:28:12.407Z",
      "content": "<p>Thanks for sharing the list of techniques.👍 </p>",
      "rawMarkdown": "Thanks for sharing the list of techniques.👍 ",
      "votes": 1,
      "replies": [
        {
          "id": 993361,
          "postDate": "2020-08-31T21:30:40.937Z",
          "content": "<p>Glad to see you enjoyed it!</p>",
          "rawMarkdown": "Glad to see you enjoyed it!",
          "votes": 2
        }
      ]
    }
  ],
  "comments": [
    {
      "id": 993316,
      "author_name": "Thaddeus Segura",
      "author_url": "",
      "post_date": "2020-08-31T20:42:09.763000",
      "content": "<p>Awesome, very clear and well documented! Upvoted 👍</p>",
      "votes": 1,
      "replies": [
        {
          "id": 993360,
          "author_name": "Nathan Zhong",
          "author_url": "",
          "post_date": "2020-08-31T21:30:16.020000",
          "content": "<p>Thank you!</p>",
          "votes": 2,
          "replies": []
        }
      ]
    },
    {
      "id": 993224,
      "author_name": "Ujwal Kandi",
      "author_url": "",
      "post_date": "2020-08-31T18:28:12.407000",
      "content": "<p>Thanks for sharing the list of techniques.👍 </p>",
      "votes": 1,
      "replies": [
        {
          "id": 993361,
          "author_name": "Nathan Zhong",
          "author_url": "",
          "post_date": "2020-08-31T21:30:40.937000",
          "content": "<p>Glad to see you enjoyed it!</p>",
          "votes": 2,
          "replies": []
        }
      ]
    }
  ],
  "raw_markdown_by_id": {
    "993135": "Hello everyone. I have just published an [Image Preprocessing Notebook](https://www.kaggle.com/nzhongahtan/simple-preprocessing-techinques-using-minst-data) that shows how different preprocessing techniques are used on the MINST digit dataset. I explain what each technique is and what effect it has on the image. The code is simple to follow and gives straightforward examples as to how to implement these techniques. I cover:\n\n- Normalization\n- Averaging\n- Gaussian Filtering\n- Median Filtering\n- Bilateral Filtering\n- Dilation\n- Erosion\n- Opening and Closing\n- Edge Sharpening\n\nCheck it out [here](https://www.kaggle.com/nzhongahtan/simple-preprocessing-techinques-using-minst-data) and feel free to leave comments on improvements or questions. If you found this helpful, it would be greatly appreciated if you could upvote this notebook. Thank you!",
    "993316": "Awesome, very clear and well documented! Upvoted 👍",
    "993224": "Thanks for sharing the list of techniques.👍 "
  }
}