Roboflow Universe kang kang

kang Computer Vision Project

Download this Dataset Try Pre-Trained Model

TRY THIS MODEL

Drop an image or

browse your device

Images

5856 images

Explore Dataset

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{
                            kang-epkik_dataset,
                            title = { kang Dataset },
                            type = { Open Source Dataset },
                            author = { kang },
                            howpublished = { \url{ https://universe.roboflow.com/kang-hswts/kang-epkik } },
                            url = { https://universe.roboflow.com/kang-hswts/kang-epkik },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { sep },
                            note = { visited on 2024-05-08 },
                            }

Connect Your Model With Program Logic

Find utilities and guides to help you start using the kang project in your project.

supervision

Find utilities to work with this project in Python.

Roboflow Learn

Build the knowledge you need to evaluate and deploy your model.

Source

kang

Last Updated

8 months ago

Project Type

Object Detection

Subject

sign-language

Views: 45

Downloads: 5

License

CC BY 4.0

Classes

brushTooth company1 company2 don'tKnow1 don'tKnow2 drive1 drive2 eat father1 father2 go1 go2 go3 goHome1 goHome2 he/she ma? me morning1 morning2 mother1 mother2 night1 night2 night3 noodle scooter1 scooter2 shower1 shower2 sleep sorry1 sorry2 study teacher test1 test2 thanks1 thanks2 thing time1 time2 today tomorrow1 tomorrow2 wake1 wake2 what whatNow whether1 whether2 work1 work2 you 不知道1 不知道2 事情什麼今天他你們公司1 公司2 刷牙去1 去2 去3 吃嗎回家1 回家2 對不起1 對不起2 工作1 工作2 怎麼辦我早上1 早上2 明天1 明天2 時間1 時間2 晚上1 晚上2 晚上3 有沒有1 有沒有2 機車1 機車2 洗澡1 洗澡2 睡老師考試1 考試2 謝謝1 謝謝2 讀書醒1 醒2 開車1 開車2 麵

Object Detection Model