Nine-balls-segmentation Computer Vision Project

AI

Updated 2 years ago

93

views

0

downloads
Classes (16)
1-yellow-ball
2-blue-ball
3-red-ball
4-pink-ball
5-orange-ball
6-green-ball
7-brown-ball
8-black-ball
9-half-yellow-ball
table-bottom
table-left-bottom
table-left-top
table-right-bottom
table-right-top
table-top
white-ball
Description

Here are a few use cases for this project:

  1. Sports Analytics: In pool/billiard games, the model could be used to analyze player strategies, track ball trajectories, or calculate hit accuracy by identifying the different balls on the table. This information can enhance player performance and provide valuable insights to coaches or commentators.

  2. Augmented Reality Games: Developers can incorporate the model into augmented reality applications. Users could digitally interact with real-world pool games, adding a layer of customizability and interactivity, such as showing ball paths, predicting results, or more novel gaming concepts.

  3. Robotic Pool/Billiard Player: Robot designers could use this model for developing pool/billiard robots. By recognizing different balls and areas of the table, the robot could strategize, take shots, and even compete with human players.

  4. Quality Control in Manufacturing: Producers of pool/billiard equipment could use this model to automatically inspect the product's color, texture, and dimension—the model could identify whether painted balls have the right color, are properly numbered, and that tables meet specifications.

  5. Pool/Billiard Game Tutoring App: For teaching and learning purposes, this model could be used in a tutoring app, highlighting different balls and explaining their importance, leading to the development of strategies and helping to visualize possible moves.

Supervision

Build Computer Vision Applications Faster with Supervision

Visualize and process your model results with our reusable computer vision tools.

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{
                            nine-balls-segmentation-abntv_dataset,
                            title = { Nine-balls-segmentation Dataset },
                            type = { Open Source Dataset },
                            author = { AI },
                            howpublished = { \url{ https://universe.roboflow.com/ai-79z1a/nine-balls-segmentation-abntv } },
                            url = { https://universe.roboflow.com/ai-79z1a/nine-balls-segmentation-abntv },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { apr },
                            note = { visited on 2024-12-25 },
                            }