Forfatter: Mihai Nan
On Christmas Eve, Santa Claus's workshop is busier than ever. Elves are preparing gifts, reindeer are polishing their bells, and Santa himself… appears in thousands of photos sent from all around the world.
The problem is that not all these images actually capture the real Santa Claus. Some show costumes, others figurines, advertisements, or people dressed up. To avoid delivering the wrong gifts, Santa needs your help!
Your task is to build a binary image classification model that decides whether an image contains Santa Claus or not.
The dataset is provided as an archive containing images organized into two directories, along with the CSV files train.csv and test.csv.
There are two classes:
label = 1)label = 0)dataset/
├── train/
│ ├── img_000001.jpg
│ ├── img_000002.jpg
│ └── ...
├── test/
│ ├── img_001234.jpg
│ ├── img_001235.jpg
│ └── ...
├── train.csv
└── test.csv
Contains the images used for training the model.
Columns:
train/img_000123.jpg)1 → Santa Claus0 → Not Santa ClausContains the images for which predictions must be generated.
Columns:
⚠️ Note: This file does NOT contain the
labelcolumn. It must be predicted by your model.
For each image in the test set, your model must decide:
The results will be compared against the ground truth labels, which are kept secret by the organizers.
The performance of your solution will be evaluated using the F1-score, a metric that combines precision and recall, suitable for binary classification problems.
Formula:
You must submit a CSV file with exactly two columns, in the following format:
| Column | Type | Description |
|---|---|---|
| image_path | string | Path to the image in test/ |
| label | integer | Prediction (0 or 1) |
image_path,label
test/img_001234.jpg,1
test/img_001235.jpg,0
test/img_001236.jpg,1
🎅 Santa Claus is counting on you!
Help him identify the correct images and deliver gifts on time!