sttkw/TAID-Dataset
TAID-Dataset Terrain intrinsic decomposition dataset with 16,000 scenes and one row per scene. Columns and numeric spaces Input, A, S, V: 8-bit RGB PNG. Byte values represent linear values in [0, 1], quantized as round(clamp(x, 0, 1) * 255). No sRGB/gamma transfer function is applied. D: NumPy .npy bytes (float32, HWC RGB), in linear HDR space [0, 5]. water_mask: 8-bit one-hot RGB PNG (R=water, G=terrain, B=sky). D_filename: original-style filename for the… See the full description on the dataset page: https://huggingface.co/datasets/sttkw/TAID-Dataset.
TAID-Dataset
Terrain intrinsic decomposition dataset with 16,000 scenes and one row per scene.
Columns and numeric spaces
Input,A,S,V: 8-bit RGB PNG. Byte values represent linear values in[0, 1], quantized asround(clamp(x, 0, 1) * 255). No sRGB/gamma transfer function is applied.D: NumPy.npybytes (float32, HWC RGB), in linear HDR space[0, 5].water_mask: 8-bit one-hot RGB PNG (R=water,G=terrain,B=sky).D_filename: original-style filename for the corresponding NPY payload.
Load diffuse shading with:
import io
import numpy as np
from datasets import load_dataset
row = load_dataset("ShunTatsukawa/TAID-Dataset", split="train")[0]
D = np.load(io.BytesIO(row["D"]), allow_pickle=False)The source diffuse target used log1p(D) / log1p(5). This repository stores the inverse-transformed value expm1(encoded * log1p(5)); it is not log-space.
License
This dataset is licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0).
