# Color Datasets Summary

## Color Naming Datasets (with actual color names)

### 1. xkcd Color Survey (`xkcd_colors.txt`)
- **Source**: https://xkcd.com/color/rgb.txt
- **License**: CC0 (Public Domain)
- **Count**: 949 colors
- **Format**: `name<tab>hex`
- **Example names**: "cloudy blue", "macaroni and cheese", "dusty teal", "toxic green"
- **Description**: Results from Randall Munroe's color naming survey with 2M+ responses

### 2. Combined Color Names (`colornames_combined.csv`)
- **Source**: https://github.com/helightdev/ColorNames
- **License**: CC0 (Public Domain)
- **Count**: 3,546 colors
- **Format**: CSV with columns: name, hex, R, G, B, L, a, b (CIELAB)
- **Sources combined**: xkcd + RAL colors + thecolorapi.com
- **Example names**: "Green Beige", "Sand Yellow", "Honey Yellow", "Traffic Orange"

### 3. World Color Survey (WCS)
- **Source**: https://www1.icsi.berkeley.edu/wcs/data.html
- **License**: Academic/Research
- **Count**: 2,616 informants, 110 languages, 330 Munsell color samples
- **Description**: Cross-linguistic color naming data mapped to Munsell coordinates
- **Note**: Server was unreachable; data may need alternative access

## colour-datasets Library (23 datasets, 185MB)

All datasets are cached at `~/.colour-science/colour-datasets/` and accessible via API.

### Munsell Color Spectral Data

| ID | Dataset | Samples | Description |
|----|---------|---------|-------------|
| 3269912 | Munsell Matt (Spectrophotometer) | 1,269 | Full hue coverage, Values 2.5-9.0 |
| 3269914 | Munsell Matt (AOTF) | 1,250 | Encoded Munsell IDs |
| 3269916 | Munsell Glossy (Spectrophotometer) | 32 | Limited samples |
| 3269918 | Munsell Glossy (All) | 1,600 | Numeric IDs |

### Natural Material Spectra

| ID | Dataset | Content |
|----|---------|---------|
| 3269920 | Forest Colors | birch (337), pine (370), spruce (349) |
| 3269922 | Paper Spectra | cardboard, newsprint, paper |
| 3269924 | Lumber Spectra | aspen, birch, pine, spruce |
| 3269926 | Agfa IT8.7/2 Set | 289 color patches |

### Camera Spectral Sensitivity

| ID | Dataset | Cameras |
|----|---------|---------|
| 8314702 | Solomatov & Akkaynak (2023) | 1012 estimated + ground truth |
| 6590768 | Physlight - Winquist (2022) | 17 cameras (Canon, Sony, Nikon) |
| 4297288 | Zhao et al. (2009) | 12 cameras |
| 3245883 | Jiang et al. (2013) | 28 cameras |

### Color Appearance & Perception

| ID | Dataset | Description |
|----|---------|-------------|
| 4394536 | LUTCHI Color Appearance | Luo & Rhodes (1997) |
| 3367463 | Constant Hue Loci | Hung & Berns (1995) |
| 3362536 | Constant Perceived-Hue | Ebner & Fairchild (1998) |
| 3270903 | Corresponding-Colour | 37 datasets, Luo & Rhodes (1999) |
| 3252742 | Observer Functions | Asano (2015) - categorical observers |

### Reference Standards

| ID | Dataset | Description |
|----|---------|-------------|
| 3245895 | ColorChecker SG/Classic | X-Rite (2016) - 24 patches with names |
| 3245875 | Labsphere SRS-99-020 | Reference reflectance standard |

### Lighting & Color Processing

| ID | Dataset | Description |
|----|---------|-------------|
| 4642271 | Cine Lighting Spectra | Arri, Dedolight, Kinoflo |
| 4051012 | LED Spectra | 29 commercial LEDs |
| 4050598 | Spectral Upsampling | sRGB, ACES, BT.2020, ProPhoto |
| 3372171 | RAW to ACES | Camera/illuminant training data |

## Access Methods

```python
# xkcd colors
with open('xkcd_colors.txt') as f:
    for line in f:
        if not line.startswith('#'):
            name, hex_code = line.strip().split('\t')

# Combined colors (includes CIELAB)
import csv
with open('colornames_combined.csv') as f:
    reader = csv.DictReader(f)
    for row in reader:
        name = row['name']
        rgb = (int(row['R']), int(row['G']), int(row['B']))
        lab = (float(row['L']), float(row['a']), float(row['b']))

# Munsell spectral data
import colour_datasets
data = colour_datasets.load('3269912')
munsell_spectra = data['munsell']  # dict of Munsell notation → SpectralDistribution
```

## Next Steps for Color Name Research

1. Convert xkcd/combined colors to Munsell notation using MunsellSpace library
2. Map color names to Munsell color space regions
3. Explore ISCC-NBS color categories for each named color
4. Build a lookup system: color name → RGB → Munsell → ISCC-NBS category
