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---
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datasets:
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- ZoneTwelve/Thermal-Heatmap-Source-Localization
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tags:
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- benchmark
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- heatmap
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- physics
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- source-localization
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- synthetic
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license: apache-2.0
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pretty_name: Thermal Heatmap Source Localization (ThermBench)
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---
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# ThermBench 🔥 — Thermal Heatmap Source Localization Benchmark
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## 📝 Summary
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**ThermBench** is a physics-inspired **synthetic dataset** designed to evaluate algorithms that infer **hidden thermal sources** from an observed **heat diffusion map**.
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Each data sample contains:
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- an **observed heatmap** (matrix of values),
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- and the **ground-truth sources**: `(row, col, intensity)`.
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Diffusion follows inverse Manhattan distance:
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\[
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H(i,j) \;=\; \sum_{s=1}^{K} \frac{I_s}{d(i,j,s)+1}
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\]
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where \(d\) is the Manhattan distance to source \(s\).
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---
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## 📊 Dataset Structure
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- **level**: Difficulty tier (`very_easy`, `easy`, `medium`, `hard`, `extreme`)
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- **input_text**: Heatmap formatted as:
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```
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N M
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K
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<N rows of values>
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```
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- **output_text**: True source positions and intensities in format:
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```
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row col intensity
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```
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### Example
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```json
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{
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"level": "easy",
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"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",
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"output_text": "1 1 10.0\n5 5 10.0"
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}
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```
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---
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## 🚀 Usage
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```python
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from datasets import load_dataset
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dataset = load_dataset(
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"ZoneTwelve/Thermal-Heatmap-Source-Localization",
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split="train"
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)
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print(dataset[0])
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```
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---
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## 🎚 Difficulty Levels
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- **very_easy** → 3×3 grid, 1 source
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- **easy** → 5×5 grid, 2 sources
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- **medium** → 10×10 grid, 3 sources
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- **hard** → 20×20 grid, 5 sources
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- **extreme** → 30×30 grid, 7 sources
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Each level contains 100 samples → **500 total**.
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A fuzzy extension of ThermBench introduces noise, intensity jitter, and rounding differences to simulate real‑world sensor readings.
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---
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## 🔧 Intended Applications
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- Benchmarking **inverse problem solvers**
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- Robustness studies for optimization/AI
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- Educational resource for algorithm development
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---
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## 📜 License
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Apache License 2.0 © ZoneTwelve
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