kongres_2022 Object Detection Dataset and Pre-Trained Model by Bryd

Images

1391 images

Explore Dataset

Here are a few use cases for this project:

Cat-themed Card Game: Utilize the "kongres_2022" computer vision model to develop a mobile or web-based cat-themed card game, where players need to identify and match cat classes based on the provided symbols (pass, x, _1, d, xx, s, _3, h, nt, _6, _5, _7, _4, _2, c, alert, _8, _10, _k, hand, _9, _j, cats) to score points and progress through levels.
Cat Behavior Monitoring: Use the model to analyze video footages of cats in home environments. The model could match the identified cat classes with specific cat behaviors, helping cat owners better understand their pets and detect potential health issues or abnormal behaviors early on.
Cat Cafe Customer Experience: Implement "kongres_2022" in a cat cafe to enhance customer experience by offering interactive visuals or augmented reality features that highlight the different cat classes when customers interact with the cats in the cafe.
Educational Tool for Veterinarians: Develop a course or educational material incorporating the "kongres_2022" model to help aspiring veterinarians, pet caregivers, or students understand various cat behaviors or features, based on the cat classes detected from videos or images.
Cat Adoption Platform: Use the computer vision model in a cat adoption platform, allowing users to search and filter available cats using the cat classes provided. This can help potential adopters find a cat with specific characteristics or behaviors they desire, increasing the likelihood of successful adoptions.

Trained Model API

This project has a trained model available that you can try in your browser and use to get predictions via our Hosted Inference API and other deployment methods.

Cite This Project

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

@misc{
                            kongres_2022_dataset,
                            title = { kongres_2022 Dataset },
                            type = { Open Source Dataset },
                            author = { Bryd },
                            howpublished = { \url{ https://universe.roboflow.com/bryd/kongres_2022 } },
                            url = { https://universe.roboflow.com/bryd/kongres_2022 },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { may },
                            note = { visited on 2024-05-02 },
                            }