File size: 2,880 Bytes
379b9bc | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 | # ClimbInst: Climbing Hold Instance Segmentation Dataset
ClimbInst is an instance segmentation dataset for climbing holds and volumes on indoor climbing walls. It was developed to support research in climbing-hold instance segmentation and related computer vision applications.
The dataset contains **1,509 images** with a total of **89,020 annotated instances**. Climbing holds and volumes are represented using a single unified class.
## Dataset Structure
The dataset is divided into training, validation, and test splits:
```text
ClimbInst/
├── train/
│ ├── images/
│ └── annotations/
├── validation/
│ ├── images/
│ └── annotations/
└── test/
├── images/
└── annotations/
```
### Dataset Statistics
| Split | Images | Annotated Instances |
| -------- | -------- | -------- |
| Train | 1,169 | 71,319 |
| Validation | 290 | 14,268 |
| Test | 50 | 3,433 |
| **Total** | **1,509** | **89,020** |
The test set is independent of the training and validation data.
## Dataset Construction
Images used to construct ClimbInst were collected from multiple sources, including publicly available climbing-wall datasets and separately collected climbing-wall imagery.
Initial instance masks were generated using **SAM3** as an annotation-assistance mechanism. The generated masks were subsequently manually inspected and corrected using **Labelme**. Incorrect masks were refined or removed, and climbing holds missed during the initial annotation process were manually added.
Both climbing holds and climbing volumes are annotated as a single unified class.
## Annotations
The dataset provides instance-level segmentation annotations for climbing holds and volumes.
Each training, validation, and test split contains its corresponding images and annotations.
## Intended Use
ClimbInst is intended to support research and development involving:
- Climbing-hold instance segmentation
- Climbing-hold detection
- Computer vision for indoor climbing
- Digital representation of climbing walls
- Climbing route selection and analysis
- Related computer vision applications
## Dataset Sources
ClimbInst incorporates climbing-wall imagery collected from multiple sources, including publicly available datasets and separately collected images.
The publicly available datasets used during dataset construction include:
- **Indoor Climbing Gym Hold and Route Segmentation** — T. Sláma, Kaggle
https://www.kaggle.com/datasets/tomasslama/indoor-climbing-gym-hold-segmentation
- **Climbing Holds and Volumes** — Roboflow
https://app.roboflow.com/weedlabelling/climbing-holds-and-volumes-zdgn3/browse
## License
License information is provided according to the applicable usage and redistribution terms of the constituent image sources. |