{
  "fetched_at": "2026-10-18T13:55:34Z",
  "source_url": "https://www.kaggle.com/competitions/dl-hack-track-1-cv/data",
  "pages": [
    {
      "name": "data-description",
      "content": "# Dataset\n\nThe train set contains 35,000 high resolution (512x512) images equally split into and real and fake samples. The test set contains 5,000 images of the same resolution.\n\n# Submission\n\nThe final submission must contain two columns - **\"id\"**: image id and **\"p_real\"**: predicted probability of the image being real. Sample submission file can be found in the provided dataset\n\nFor more information please visit: https://analytics-club-iitm.github.io/DL-Hack-20-21/track1",
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      "postTitle": "",
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    },
    {
      "name": "Description",
      "content": "# Description\n\nRecent progress in Computer Vision (specifically in Generative models) has enabled the creation of high-resolution deep fakes which are practically indistinguishable from real ones. However, when this technology falls into the wrong hands, it can be used maliciously as a source of misinformation, manipulation, harassment, and persuasion. Identifying manipulated media is a technically demanding and rapidly evolving challenge.\n\nIn this challenge, you will be required to classify images as \"real\" or \"fake\". The goal of this challenge is to spur students to build new and innovative solutions that can help detect deep fakes and manipulated media. \n\nFor more information please visit: https://analytics-club-iitm.github.io/DL-Hack-20-21/track1",
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      "hasIsPublished": false,
      "postTitle": "",
      "hasPostTitle": false,
      "mimeType": "",
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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!",
      "isPublished": false,
      "hasIsPublished": false,
      "postTitle": "",
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}