--- 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: 6609517 num_examples: 89 download_size: 6607674 dataset_size: 6609517 --- # ndimensions/sementic-segmentation-test Semantic segmentation dataset in COCO format with direct index masks. ## Classes (92 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 | latch | (86, 229, 57) | | 29 | hinge | (210, 31, 114) | | 30 | window sill | (66, 160, 191) | | 31 | box | (229, 221, 57) | | 32 | furniture | (150, 31, 210) | | 33 | mattress | (66, 191, 113) | | 34 | refrigerator | (229, 70, 57) | | 35 | painting | (31, 69, 210) | | 36 | oven | (129, 191, 66) | | 37 | cabinet | (229, 57, 194) | | 38 | window | (31, 210, 194) | | 39 | person | (191, 144, 66) | | 40 | fan | (113, 57, 229) | | 41 | computer monitor | (31, 210, 38) | | 42 | monitor | (191, 66, 98) | | 43 | range hood | (57, 151, 229) | | 44 | handle | (181, 210, 31) | | 45 | hardwood floor | (174, 66, 191) | | 46 | kitchen cabinet | (57, 229, 156) | | 47 | kick plate | (210, 82, 31) | | 48 | cabinet door | (66, 67, 191) | | 49 | appliance | (108, 229, 57) | | 50 | office chair | (210, 31, 137) | | 51 | robot | (66, 176, 191) | | 52 | computer tower | (229, 199, 57) | | 53 | clothing | (127, 31, 210) | | 54 | pole | (66, 191, 97) | | 55 | wheel | (229, 57, 65) | | 56 | chair wheel | (31, 92, 210) | | 57 | cabinetry | (145, 191, 66) | | 58 | stick | (229, 57, 216) | | 59 | cardboard box | (31, 210, 171) | | 60 | bed frame | (191, 128, 66) | | 61 | frame | (91, 57, 229) | | 62 | sheet | (47, 210, 31) | | 63 | smart plug | (191, 66, 114) | | 64 | bedding | (57, 173, 229) | | 65 | light fixture | (204, 210, 31) | | 66 | cable | (159, 66, 191) | | 67 | bucket | (57, 229, 134) | | 68 | toilet | (210, 59, 31) | | 69 | window frame | (66, 83, 191) | | 70 | 3d printer | (130, 229, 57) | | 71 | plug | (210, 31, 159) | | 72 | computer case | (66, 191, 190) | | 73 | fixture | (229, 177, 57) | | 74 | toilet seat | (104, 31, 210) | | 75 | ventilation grille | (66, 191, 81) | | 76 | picture frame | (229, 57, 87) | | 77 | shoe | (31, 115, 210) | | 78 | ceiling | (161, 191, 66) | | 79 | artwork | (220, 57, 229) | | 80 | outlet | (31, 210, 148) | | 81 | stand | (191, 112, 66) | | 82 | hallway | (69, 57, 229) | | 83 | bag | (70, 210, 31) | | 84 | laptop | (191, 66, 130) | | 85 | power outlet | (57, 195, 229) | | 86 | counter | (210, 193, 31) | | 87 | sink | (143, 66, 191) | | 88 | electrical cord | (57, 229, 112) | | 89 | window panel | (210, 36, 31) | | 90 | floor lamp | (66, 99, 191) | | 91 | column | (152, 229, 57) | ## 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: 92 - Split: train