| # ClimbInst: Climbing Hold Instance Segmentation Dataset |
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| 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. |
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| 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. |
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| ## Dataset Structure |
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| The dataset is divided into training, validation, and test splits: |
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| ```text |
| ClimbInst/ |
| ├── train/ |
| │ ├── images/ |
| │ └── annotations/ |
| ├── validation/ |
| │ ├── images/ |
| │ └── annotations/ |
| └── test/ |
| ├── images/ |
| └── annotations/ |
| ``` |
| ### Dataset Statistics |
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| | Split | Images | Annotated Instances | |
| | -------- | -------- | -------- | |
| | Train | 1,169 | 71,319 | |
| | Validation | 290 | 14,268 | |
| | Test | 50 | 3,433 | |
| | **Total** | **1,509** | **89,020** | |
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| The test set is independent of the training and validation data. |
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| ## Dataset Construction |
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| Images used to construct ClimbInst were collected from multiple sources, including publicly available climbing-wall datasets and separately collected climbing-wall imagery. |
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| 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. |
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| Both climbing holds and climbing volumes are annotated as a single unified class. |
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| ## Annotations |
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| The dataset provides instance-level segmentation annotations for climbing holds and volumes. |
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| Each training, validation, and test split contains its corresponding images and annotations. |
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| ## Intended Use |
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| ClimbInst is intended to support research and development involving: |
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| - Climbing-hold instance segmentation |
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| - Climbing-hold detection |
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| - Computer vision for indoor climbing |
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| - Digital representation of climbing walls |
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| - Climbing route selection and analysis |
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| - Related computer vision applications |
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| ## Dataset Sources |
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| ClimbInst incorporates climbing-wall imagery collected from multiple sources, including publicly available datasets and separately collected images. |
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| The publicly available datasets used during dataset construction include: |
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| - **Indoor Climbing Gym Hold and Route Segmentation** — T. Sláma, Kaggle |
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| https://www.kaggle.com/datasets/tomasslama/indoor-climbing-gym-hold-segmentation |
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| - **Climbing Holds and Volumes** — Roboflow |
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| https://app.roboflow.com/weedlabelling/climbing-holds-and-volumes-zdgn3/browse |
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| ## License |
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| License information is provided according to the applicable usage and redistribution terms of the constituent image sources. |
