Number of categories in concatenated Images

🏞️ Number of Categories in a Concatenated Image

For this task, you need to implement a model capable of estimating the number of distinct categories in an image created by concatenating several smaller images.

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🔹 Dataset

The dataset is provided as images with associated CSV files:

• train.csv: contains examples for training the model

  Column	Type	Description
  SampleID	integer	Unique identifier for each example
  ImagePath	string	Path to the concatenated image
  Label	integer	Number of distinct categories in the image

• test.csv: contains examples for prediction

  Column	Type	Description
  SampleID	integer	Unique identifier
  ImagePath	string	Path to the concatenated image

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⚙️ Evaluation Metric

The score for each example is calculated as follows:

• If the predicted value equals the true value → 1 point
• If the predicted value differs from the true value by one (+1/-1) → 0.5 points
• Otherwise → 0 points

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📨 Submission File Format

The submission file must be a CSV with two columns:

Column	Type	Description
SampleID	integer	Unique identifier of the row in the test set
PredictedLabel	integer	Predicted number of distinct categories in the image

🔹 Example submission.csv

SampleID	PredictedLabel
1	4
2	2
3	3

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🖼️ Example Interpretation of the Label

If a concatenated image contains multiple objects, the label represents the number of distinct categories.

🏞️ Example

• The image contains: a dog, a car, and another dog
• Number of distinct categories = 2 (category "dog" and category "car")

Thus, the model must recognize the different classes in the image and return an integer corresponding to the number of distinct classes.