---
datasets:
- ZoneTwelve/Thermal-Heatmap-Source-Localization
tags:
- benchmark
- heatmap
- physics
- source-localization
- synthetic
license: apache-2.0
pretty_name: Thermal Heatmap Source Localization (ThermBench)
---

# ThermBench 🔥 — Thermal Heatmap Source Localization Benchmark

## 📝 Summary
**ThermBench** is a physics-inspired **synthetic dataset** designed to evaluate algorithms that infer **hidden thermal sources** from an observed **heat diffusion map**.

Each data sample contains:
- an **observed heatmap** (matrix of values),
- and the **ground-truth sources**: `(row, col, intensity)`.

Diffusion follows inverse Manhattan distance:

\[
H(i,j) \;=\; \sum_{s=1}^{K} \frac{I_s}{d(i,j,s)+1}
\]

where \(d\) is the Manhattan distance to source \(s\).

---

## 📊 Dataset Structure

- **level**: Difficulty tier (`very_easy`, `easy`, `medium`, `hard`, `extreme`)
- **input_text**: Heatmap formatted as:
  ```
  N M
  K
  <N rows of values>
  ```
- **output_text**: True source positions and intensities in format:
  ```
  row col intensity
  ```

### Example
```json
{
  "level": "easy",
  "input_text": "5 5\n2\n10 8 6 5 4\n8 10 7 6 5\n6 7 10 7 6\n5 6 7 10 8\n4 5 6 8 10",
  "output_text": "1 1 10.0\n5 5 10.0"
}
```

---

## 🚀 Usage

```python
from datasets import load_dataset

dataset = load_dataset(
    "ZoneTwelve/Thermal-Heatmap-Source-Localization",
    split="train"
)
print(dataset[0])
```

---

## 🎚 Difficulty Levels

- **very_easy** → 3×3 grid, 1 source
- **easy** → 5×5 grid, 2 sources
- **medium** → 10×10 grid, 3 sources
- **hard** → 20×20 grid, 5 sources
- **extreme** → 30×30 grid, 7 sources

Each level contains 100 samples → **500 total**.

A fuzzy extension of ThermBench introduces noise, intensity jitter, and rounding differences to simulate real‑world sensor readings.

---

## 🔧 Intended Applications
- Benchmarking **inverse problem solvers**
- Robustness studies for optimization/AI
- Educational resource for algorithm development

---

## 📜 License
Apache License 2.0 © ZoneTwelve