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| title: AIOT Inference | |
| emoji: 🐨 | |
| colorFrom: yellow | |
| colorTo: purple | |
| sdk: gradio | |
| sdk_version: 5.9.0 | |
| app_file: app.py | |
| pinned: false | |
| Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference | |
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| # BurnSync Classification Model | |
| ## Authors | |
| * Hsuan-Ying, Liu | |
| * Affiliation: National Taiwan University, NTUEE | |
| * Email: stevenliu901205@gmail.com | |
| * Chi-En Dai | |
| * Affiliation: National Taiwan University, NTUGICE | |
| * Email: dcn0629@gmail.com | |
| **If you have any question about this project, do not hesitate to contact us for detail explanation!!!** | |
| ## Introduction | |
| This is a repository we held on Hugging Face to deploy our exercise classification model. It is able to classify four types of exercise — push-up, sit-up, squat and dumbbell. We also applied sliding window to count the repetitions of the exercise sequence. The input of this model is a json file with IMU data sequence. The output is a json file with the exercise type and the repetition count inside. To know more about our project, please refer to our **BurnSync** repository below. | |
| ## Repositories | |
| * [BurnSync Repository](https://github.com/lsy1205/BurnSync.git) | |
| * [BurnSync Website](https://github.com/lsy1205/BurnSync_website.git) | |