{
  "fetched_at": "2026-10-19T07:57:49Z",
  "source_url": "https://www.kaggle.com/competitions/applications-of-deep-learning-wustl-spring-2024/data",
  "pages": [
    {
      "name": "data-description",
      "content": "This dataset contains images of people generated by Stable Diffusion. For each image, you are to determine how old the person is. The ages were defined by giving Stable Diffusion random prompts that included a requested age. Ages will range between 20 and 90 years old.\n\n## Files\n\n*   **train.csv** - the training set\n*   **test.csv** - the test set\n*   **sample_submission.csv** - a sample submission file in the correct format\n\n## Columns\n\n*   `id` - The numeric id of each person\n*   `filename` - The image filename for this id\n*   `age` - The age that was provided to the Stable Diffusion prompt to generate this person\n",
      "isPublished": false,
      "hasIsPublished": false,
      "postTitle": "",
      "hasPostTitle": false,
      "mimeType": "",
      "hasMimeType": false
    },
    {
      "name": "Description",
      "content": "Can you predict the age that was used in Stable Diffusion prompts to generate pictures of people? This competition provides nearly 20K images for you learn to predict the ages of these computer generated individuals.",
      "isPublished": false,
      "hasIsPublished": false,
      "postTitle": "",
      "hasPostTitle": false,
      "mimeType": "",
      "hasMimeType": false
    },
    {
      "name": "Evaluation",
      "content": "Submissions will be automatically evaluated by Kaggle.\n\n---\n\nSubmissions are evaluated on [RMSE](https://en.wikipedia.org/wiki/Root-mean-square_deviation) between the predicted probability and the observed target.\n\n\n## Submission File\nFor each image id, predict the correct age.\n\n    id, age\n    2,24.23\n    1,38.12\n    2,40.22\n    etc.",
      "isPublished": false,
      "hasIsPublished": false,
      "postTitle": "",
      "hasPostTitle": false,
      "mimeType": "",
      "hasMimeType": false
    },
    {
      "name": "rules",
      "content": "You may use any code that you like for this competition, as well as code generated by LLMs such as ChatGPT or GitHub Copilot. Team may consist of up to 5 people and may span the two sections. People from outside the class are allowed to enter.",
      "isPublished": false,
      "hasIsPublished": false,
      "postTitle": "",
      "hasPostTitle": false,
      "mimeType": "",
      "hasMimeType": false
    },
    {
      "name": "abstract",
      "content": "For this competition you are given images of people that were generated by Stable Diffusion using a variety of prompts where I specified the age of the person being generated. Your task is to determine the age that was specified in the prompt to create each person. The dataset consists of 512x512 sized images, such as these:\n\n![Generated Person 1](https://data.heatonresearch.com/images/wustl/kaggle/2024-spring/1.jpg)\n![Generated Person 2](https://data.heatonresearch.com/images/wustl/kaggle/2024-spring/6.jpg)\n![Generated Person 3](https://data.heatonresearch.com/images/wustl/kaggle/2024-spring/7.jpg)\n\nThe image set comes from a diverse set of people. The ages are drawn from a normal distribution with mean and standard deviation matching the USA population as of 2024. \n\n![Generated Person 3](https://data.heatonresearch.com/images/wustl/kaggle/2024-spring/diverse.jpg)\n\nRemember, you are trying to predict the age that was used in the prompt, which may not necessarily create a realistic human at that age. For example here are some ages for what the model generated.\n\n### Age 20\n![Generated Person Age 20](https://data.heatonresearch.com/images/wustl/kaggle/2024-spring/age-20.jpg)\n\n### Age 30\n![Generated Person Age 20](https://data.heatonresearch.com/images/wustl/kaggle/2024-spring/age-30.jpg)\n\n### Age 40\n![Generated Person Age 40](https://data.heatonresearch.com/images/wustl/kaggle/2024-spring/age-40.jpg)\n\n### Age 50\n![Generated Person Age 50](https://data.heatonresearch.com/images/wustl/kaggle/2024-spring/age-50.jpg)\n\n### Age 60\n![Generated Person Age 60](https://data.heatonresearch.com/images/wustl/kaggle/2024-spring/age-60.jpg)\n\n### Age 70\n![Generated Person Age 70](https://data.heatonresearch.com/images/wustl/kaggle/2024-spring/age-70.jpg)\n\n### Age 80\n![Generated Person Age 80](https://data.heatonresearch.com/images/wustl/kaggle/2024-spring/age-80.jpg)\n\n### Age 90\n![Generated Person Age 90](https://data.heatonresearch.com/images/wustl/kaggle/2024-spring/age-90.jpg)\n",
      "isPublished": false,
      "hasIsPublished": false,
      "postTitle": "",
      "hasPostTitle": false,
      "mimeType": "",
      "hasMimeType": false
    }
  ]
}