skywater_seg / data /README.md
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# ADE20K Sky-Water-Person Split Files
These split files list ADE20K images that contain at least one of the
target classes (sky, water, person).
## Format
Each line is a path relative to the ADE20K image root
(`ADEChallengeData2016/images/`):
```
validation/ADE_val_00000001.jpg
training/ADE_train_00000001.jpg
```
## Expected Dataset Layout
```
ADEChallengeData2016/
β”œβ”€β”€ images/
β”‚ β”œβ”€β”€ training/
β”‚ β”‚ β”œβ”€β”€ ADE_train_00000001.jpg
β”‚ β”‚ └── ...
β”‚ └── validation/
β”‚ β”œβ”€β”€ ADE_val_00000001.jpg
β”‚ └── ...
└── annotations/
β”œβ”€β”€ training/
β”‚ β”œβ”€β”€ ADE_train_00000001.png
β”‚ └── ...
└── validation/
β”œβ”€β”€ ADE_val_00000001.png
└── ...
```
## Class Mapping
ADE20K raw labels β†’ skywater 4-class scheme:
| ADE20K ID | ADE20K Name | Target Class |
|-----------|-------------|--------------|
| 3 | sky | 1 (Sky) |
| 13 | person | 3 (Person) |
| 22 | water | 2 (Water) |
| 27 | sea | 2 (Water) |
| 61 | lake | 2 (Water) |
| 105 | pond | 2 (Water) |
| 110 | fountain | 2 (Water) |
| 114 | waterfall | 2 (Water) |
| 129 | river | 2 (Water) |
| (all others) | β€” | 0 (Background) |
## Obtaining ADE20K
Download from: https://groups.csail.mit.edu/vision/datasets/ADE20K/
Use the `ADEChallengeData2016` subset (training + validation).