{
  "fetched_at": "2026-10-19T09:13:26Z",
  "source_url": "https://www.kaggle.com/competitions/DL2020/data",
  "pages": [
    {
      "name": "data-description",
      "content": "# Dataset Description\nWe offer a total of three types of image datasets: cheetahs, jaguars, hyenas, and tigers.\nAll images size is 400(H) * 400(W) * 3(RGB)\n\nIn each class include,\n900 training images and 100 validation images are provided.\n\nEach label of an image is specified in the image name. and its folder name\nTherefore, you can use the image name to create classification ground truth.\nTotally, 4K labeled images are provided for the training dataset\n\nYou can see 404 test images which are contaminated but label are not provided",
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    {
      "name": "Description",
      "content": "# Introduction\n\nWelcome to the  ****Professor Hyoseok Hwang's Deep Learning class(2020)**** classification competition. 😃👋👋 \n\n\n# Goal of Competition\n\nThrough this competition, \nwe hope to improve deep learning skills and improve PyTorch coding skills so that you can finally have a wide perspective on the deep learning model. 💪💪 \n\n# Dataset Description\n\nWe offer a total of three types of image datasets: ****cheetahs, jaguars, hyenas, and tigers.****\nAll images size is 400(H) * 400(W) * 3(RGB)\n\nIn each class include,\n**900 training images** and **100 validation images** are provided.\n\nEach label of an image is specified in the **image name**. and its **folder name**\nTherefore, you can use the image name to create classification ground truth.\nTotally, 4K labeled images are provided for the training dataset\n\nYou can see **404 test images** which are contaminated but label is not provided\n\nWe look forward to seeing good results. 👍 👍 👍",
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    {
      "name": "rules",
      "content": "This is a page where you can include rules that participants must accept before joining. You may wish to include rules like:\n\n - Don't cheat!\n - Apply yourself!\n - Have fun!",
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      "hasIsPublished": false,
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    {
      "name": "Evaluation Method",
      "content": "# Evaluation Method\n\nOur evaluation method uses only accuracy.\n\nTherefore, there is no limit to ****data preprocessing(data augmentation)**** to increase accuracy.\nHowever, models trained without using the provided dataset will be \"0\" points.\n",
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    {
      "name": "Contact",
      "content": "# Contact\n\n✔️ Prof. Hyoseok Hwang: hshwang@gachon.ac.kr\n✔️ TA: Jihu Kim: paransky9577@gmail.com\n✔️ TA: Byunghoon Hwang: byunghoonhwang97@gmail.com\n\nOnly questions about the dataset and competitions are acceptable\n",
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      "hasIsPublished": false,
      "postTitle": "",
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    },
    {
      "name": "Submission Format",
      "content": "You must submit CSV file format for get test accuracy\n\nHere is an example\n| Id | category |\n| --- | --- |\n| 01025 | cheetah |\n| 5450 | jauger |\n| 026 | jaguar |\n|  ... | ... |\n\nId column is id number of an image file\nThe class column is class(string) of an image\nYou can refer example code to make submission file",
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