Climbing Holds and Volumes Computer Vision Project

robworkspace

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Description

Project Overview: This project aims to develop a robust and efficient system for identifying and classifying climbing holds and climbing volumes on indoor climbing walls.

Data Collection: To achieve accurate detection and classification, an extensive dataset of climbing wall images is being created. This dataset include diverse climbing routes with various types of holds and volumes, captured from different angles, lighting conditions, and backgrounds. The images will cover a wide range of climbing holds, such as jugs, crimps, slopers, pockets, and various climbing volumes, including cubes, wedges, and features of different shapes and sizes.

Annotation: Each image in the dataset has been meticulously annotated with bounding boxes around individual climbing holds and climbing volumes. Annotation has been perform by me. However, to enhance the quality of the dataset, external contributions and collaboration from the climbing community are welcomed.

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Cite This Project

LICENSE
CC BY 4.0

If you use this dataset in a research paper, please cite it using the following BibTeX:

                        @misc{
                            climbing-holds-and-volumes-c91sa_dataset,
                            title = { Climbing Holds and Volumes Dataset },
                            type = { Open Source Dataset },
                            author = { robworkspace },
                            howpublished = { \url{ https://universe.roboflow.com/robworkspace-xfv3r/climbing-holds-and-volumes-c91sa } },
                            url = { https://universe.roboflow.com/robworkspace-xfv3r/climbing-holds-and-volumes-c91sa },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2024 },
                            month = { aug },
                            note = { visited on 2024-11-24 },
                            }
                        
                    

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