README.md

---
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
dataset_info:
  features:
  - name: image
    dtype: image
  - name: timestamp_ms
    dtype: int64
  - name: width
    dtype: int64
  - name: height
    dtype: int64
  - name: machine_id
    dtype: string
  - name: instance_mask
    dtype: image
  - name: image_id
    dtype: string
  - name: semantic_mask
    dtype: image
  - name: review_status
    dtype: string
  splits:
  - name: train
    num_bytes: 7376790
    num_examples: 89
  download_size: 7353338
  dataset_size: 7376790
---
# ndimensions/sementic-segmentation-test

Semantic segmentation dataset in COCO format with direct index masks.

## Classes (80 total)

| ID | Name | Color (RGB) |
|---:|------|-------------|
| 0 | background | (0, 0, 0) |
| 1 | floor | (57, 107, 229) |
| 2 | curtain | (135, 210, 31) |
| 3 | jacket | (191, 66, 175) |
| 4 | chair | (57, 229, 200) |
| 5 | wall | (210, 128, 31) |
| 6 | door | (97, 66, 191) |
| 7 | access panel | (64, 229, 57) |
| 8 | door handle | (210, 31, 91) |
| 9 | light switch | (66, 144, 191) |
| 10 | baseboard | (215, 229, 57) |
| 11 | door hinge | (172, 31, 210) |
| 12 | vent | (66, 191, 128) |
| 13 | doorway | (229, 92, 57) |
| 14 | door frame | (31, 46, 210) |
| 15 | trash can | (113, 191, 66) |
| 16 | couch | (229, 57, 172) |
| 17 | pillar | (31, 203, 210) |
| 18 | mop | (191, 159, 66) |
| 19 | bed | (135, 57, 229) |
| 20 | mirror | (31, 210, 60) |
| 21 | fire extinguisher | (191, 66, 82) |
| 22 | electrical outlet | (57, 129, 229) |
| 23 | small furniture | (158, 210, 31) |
| 24 | desk | (190, 66, 191) |
| 25 | wood floor | (57, 229, 178) |
| 26 | cleaning tool | (210, 105, 31) |
| 27 | themostat | (82, 66, 191) |
| 28 | office chair | (86, 229, 57) |
| 29 | hinge | (210, 31, 114) |
| 30 | hallway | (66, 160, 191) |
| 31 | furniture | (229, 221, 57) |
| 32 | ventilation grate | (150, 31, 210) |
| 33 | high chair | (66, 191, 113) |
| 34 | window sill | (229, 70, 57) |
| 35 | rolled item | (31, 69, 210) |
| 36 | cardboard box | (129, 191, 66) |
| 37 | wall outlet | (229, 57, 194) |
| 38 | mattress | (31, 210, 194) |
| 39 | window | (191, 144, 66) |
| 40 | refrigerator | (113, 57, 229) |
| 41 | cabinet | (31, 210, 38) |
| 42 | artwork | (191, 66, 98) |
| 43 | kitchen counter | (57, 151, 229) |
| 44 | vase | (181, 210, 31) |
| 45 | computer monitor | (174, 66, 191) |
| 46 | fan | (57, 229, 156) |
| 47 | toy car | (210, 82, 31) |
| 48 | person | (66, 67, 191) |
| 49 | floor lamp | (108, 229, 57) |
| 50 | ventilation grille | (210, 31, 137) |
| 51 | oven | (66, 176, 191) |
| 52 | range hood | (229, 199, 57) |
| 53 | kick plate | (127, 31, 210) |
| 54 | handle | (66, 191, 97) |
| 55 | robot | (229, 57, 65) |
| 56 | monitor | (31, 92, 210) |
| 57 | clothing pile | (145, 191, 66) |
| 58 | cable | (229, 57, 216) |
| 59 | bag | (31, 210, 171) |
| 60 | laptop | (191, 128, 66) |
| 61 | vacuum cleaner | (91, 57, 229) |
| 62 | bed frame | (47, 210, 31) |
| 63 | cloth | (191, 66, 114) |
| 64 | box | (57, 173, 229) |
| 65 | outlet | (204, 210, 31) |
| 66 | shoe | (159, 66, 191) |
| 67 | container | (57, 229, 134) |
| 68 | bathtub | (210, 59, 31) |
| 69 | bucket | (66, 83, 191) |
| 70 | 3d printer | (130, 229, 57) |
| 71 | window frame | (210, 31, 159) |
| 72 | power cord | (66, 191, 190) |
| 73 | computer tower | (229, 177, 57) |
| 74 | toilet | (104, 31, 210) |
| 75 | stick | (66, 191, 81) |
| 76 | table | (229, 57, 87) |
| 77 | picture frame | (31, 115, 210) |
| 78 | sneaker | (161, 191, 66) |
| 79 | toy | (220, 57, 229) |


## Columns
- `image`: RGB image
- `semantic_mask`: Semantic segmentation mask (pixel value = class ID)
- `instance_mask`: Instance segmentation mask (pixel value = instance ID)
- `image_id`: Unique image identifier
- `review_status`: Review lifecycle (pending → in_review → completed)

## Files
- `annotations/train.json`: COCO format annotations
- `labelmap.txt`: Class definitions with colors

## Statistics
- Samples: 89
- Classes: 80
- Split: train