Cybernaut101/floorplan_dataset_images_10000_simple_labels

rPlan Floorplan Dataset (32x32)

Floorplan images from the rPlan dataset, resized to 32x32 pixels. Stored as compressed Parquet with numpy arrays for efficient loading.

Dataset Format

Each sample contains:

• id: Image identifier (string)
• room_labels: 32x32 uint8 numpy array - basic room types (13 unique classes)
• interior_mask: 32x32 uint8 numpy array - interior/exterior mask (255 = interior, 0 = exterior)

Room Color Mapping (13 Classes)

Class ID	Color Value	Class Name
0	0	Living Room
1	21	Master Room
2	42	Kitchen
3	63	Bathroom
4	85	Dining Room
5	106	Child Room
6	127	Study Room
7	148	Second Room
8	170	Guest Room
9	191	Balcony
10	212	Entrance
11	233	Storage
12	255	External Area

Usage

from datasets import load_dataset
import numpy as np

# Load the dataset
ds = load_dataset("Cybernaut101/floorplan_dataset_images_10000_simple_labels")

# Access a sample
sample = ds["train"][0]
room_labels = np.array(sample["room_labels"])  # 32x32 uint8
interior_mask = np.array(sample["interior_mask"])    # 32x32 uint8

# Iterate over the dataset
for sample in ds["train"]:
    room_labels = np.array(sample["room_labels"])
    interior_mask = np.array(sample["interior_mask"])
    # ... your processing here

# Color value -> class name mapping
ROOM_COLOR_MAP = {
    0: "living room",
    21: "master room",
    42: "kitchen",
    63: "bathroom",
    85: "dining room",
    106: "child room",
    127: "study room",
    148: "second room",
    170: "guest room",
    191: "balcony",
    212: "entrance",
    233: "storage",
    255: "external area",
}

License

Please refer to the original rPlan dataset license for usage terms.