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The archive of a thousand rooms

Author: Mihai Nan

Hard
Your best score: N/A
Problem Description

🔢🧮 The archive of a thousand cameras 📚📷

📖 Description 🌌

At the heart of a secret research institute lies The archive of a thousand Cameras, an underground labyrinth with chambers monitored 24/7 by smart cameras. Each room captures objects, furniture, electronic devices, or symbols of mysterious experiments.

For unknown reasons, some of the archive data have lost their numerical labels: recordings show the question “how many objects of type X are in the image?”, but the answer is missing. Researchers tried to manually reconstruct the information, but thousands of images are impossible to process without help.

This is where you step in.

You have been entrusted with the role of a “Numerical Visual Analyst”, the only person authorized to build a multimodal model capable of looking at an image, understanding the question, and correctly answering with a single number.

Your mission is to use your expertise in Artificial Intelligence algorithms to restore the archive.


📁 Dataset Structure

There are two main files and a folder with images.

1. train.csv — Training Data

sample_idquestionanswerimage_id
TRAIN0000how many chairs are there6image888
TRAIN0001how many pictures are on the wall2image942
TRAIN0002how many chairs are there10image1404

2. test.csv — Data without answers

sample_idquestionimage_id
TEST0000how many drawers are thereimage1362
TEST0001how many televisions are thereimage169
TEST0002how many flags are visibleimage1326

3. Images directory

images/
image888.png
image942.png
image1404.png
image1362.png
image169.png
image1326.png

📤 Submission Format

The submission.csv file should have the following format:

sample_idanswer
TEST00004
TEST00011
TEST00023

🎯 Evaluation Metric

Since the answers are numbers, the official evaluation uses MAE:

MAE

The final score is calculated based on the MAE obtained using the following rules:

  • MAE ≤ 0.2 → 100 points
  • MAE ≥ 1 → 0 points
  • For intermediate values, the score is scaled proportionally between 0 and 100.
Submit Solution
Upload output file and optionally source code for evaluation.

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