{
  "fetched_at": "2026-10-19T09:06:01Z",
  "source_url": "https://www.kaggle.com/competitions/com3025-2022-challenge-week2-and-3-extend/data",
  "pages": [
    {
      "name": "data-description",
      "content": "# Directory Structure\n- train\n  - The image files for the training set\n- train.csv\n  - The labels for the training set\n- test\n  - The image files for the test set\n- submission_sample.csv\n  - The sample of submission file\n\n---\n\nThe evaluation metric for this competition is Accuracy.\n\n## Submission Format\n\nsubmission files should contain two columns: `file_path` and `label`. A header will be needed for the submission, so the first line will start with the header information.\n\n\nThe file header **must** contain a header. Details can be found on Overview/Evaluation page.\n",
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      "name": "Description",
      "content": "# Deadline\nDeadline for LSA: 08/23/2022 4:00 PM\nDeadline for EC Students: 08/30/2022 4:00 PM\n# Overview\nThis challenge concerns the automated classification of images through machine learning techniques. You will work on flower data, where training samples and their ground truth are provided. You will develop suitable classification techniques that will make predictions on unseen test data. The performance will be measured upon submission of the prediction results. A leaderboard will be published after each submission. **You need to use your URN as the Team Name** in the Kaggle page. **Otherwise, your score won't be recorded.** Multiple submissions are encouraged if you wish to improve your models. The latest model for each student will be used for the assessment. You may save multiple prediction results and choose the best one for the final submission.\n\n# Important Rule\nYou need to use your URN as the Team Name in the Kaggle page. Otherwise, your score won't be recorded.\n\n# Code Submission\nYou need to submit your code to Surreylearn before the code submission due date (see SurreyLearn for further detail)\n\n# Participation\nPlease click the join competition button on the page to join it. Otherwise, you cannot submit your result.\n\n# Dataset\n### Overview\nThis is a dataset about **Flower**, and there are 102 types of flowers in this dataset that need to be classified.\n### Dataset Size\n- Training set: 2040 images\n- Testing set: 6149 images\n### Training and Testing Data\nWe will provide the images and labels for the training set and images for the testing set.\n\n# Evaluation\nWe will evaluate your prediction result on the testing set. So you will need to submit the result in this competition page. **The minimum requirement of this challenge is 60% testing accuracy.**\n \n# Submission Format\nYour submission should be a csv file, with two columns in it, the first is the id of the test image and the second is its label. We will provide an example of the submission file in the Data Section.",
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    {
      "name": "Evaluation",
      "content": "# The evaluation metric for this competition is Accuracy.\n\n## Submission Format\n\nsubmission files should contain two columns: `file_path` and `label`. A header will be needed for the submission, so the first line will start with the header information.\n\n\nThe file header **must** contain a header and have the following format:\n```\nfile_path, label\ntest/e6ce4c1c-7d46-44da-858f-96df75a04c38.jpg,68\ntest/15a72939-137f-49d0-b433-3660b3bad9d4.jpg,32\ntest/f85f4732-777d-46c9-bcad-22cacd282141.jpg,99\ntest/e0f43080-93b9-46a6-864e-57e52d238cb2.jpg,22\ntest/c5e244fc-61a8-4ac4-a2ed-cadc18a41469.jpg,81\ntest/67fa0847-554b-4cad-889c-6f8b53ad54f7.jpg,26\ntest/df33ffa6-98a2-46b0-9bec-b7c6aef55578.jpg,21\ntest/d87136ab-98f1-421a-8824-c025baf37d4d.jpg,86\ntest/1dae34d4-016d-435c-88a3-0202311d0bdb.jpg,77\ntest/33b04bac-0336-4c2c-b319-40a189d7c997.jpg,26\ntest/7251826b-3db9-404b-9e64-b3e96b52624b.jpg,2\ntest/da01dbfe-da8d-43e6-ab35-7092b377ccb9.jpg,19\ntest/d752d5ff-86cc-4342-b51a-afb07dc8c277.jpg,21\ntest/20782bb0-a8f4-4184-a093-1a1118d39a4d.jpg,31\ntest/c312f967-6714-4965-9b39-d169fc9206b5.jpg,94\ntest/188d7e2d-8ffb-497b-a780-c81a1fe4de31.jpg,27\ntest/a5b01826-ca76-4ae7-b031-2aa06e197500.jpg,32\n...\n```\n\nAn example submission is provided on the data page.",
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    {
      "name": "rules",
      "content": "\n# Important Rule\nYou need to use your URN as the Team Name in the Kaggle page. Otherwise, your score won't be recorded.\n\n# Code Submission\nYou need to submit your code to Surreylearn before the code submission due date (see SurreyLearn for further detail)\n\n# Participation\nPlease click the join competition button on the page to join it. Otherwise, you cannot submit your result.\n\n# Dataset\n### Overview\nThis is a dataset about **Flower**, and there are 102 types of flowers in this dataset that need to be classified.\n### Dataset Size\n- Training set: 2040 images\n- Testing set: 6149 images\n### Training and Testing Data\nWe will provide the images and labels for the training set and images for the testing set.\n\n# Evaluation\nWe will evaluate your prediction result on the testing set. So you will need to submit the result in this competition page. **The minimum requirement of this challenge is 60% testing accuracy.**\n \n# Submission Format\nYour submission should be a csv file, with two columns in it, the first is the id of the test image and the second is its label. We will provide an example of the submission file in the Data Section.",
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