Pytorch Based - Efficient and Lightweight Ear Segmentation
Project description
Efficient and Lightweight Ear Segmentation
Download Model 📂
⚙️ Requirements ⚙️
- Python 3.8 to Python3.10 (Virtualenv recommended)
- Display Server for showing results
- Optional: poetry
- Optional: Nvidia CUDA for cuda usage
🛠️ Installation 🛠️
Pip installation
pip install -r requirements.txt
Poetry installation
poetry shell
poetry install
Optional (If you have multiple python installation)
poetry env use $(which python3.10)
poetry shell
poetry install
Usage
usage: earsegmentationai_cli.py [-h] -m {c,p} [-d [{cpu,cuda}]] [-fp FOLDERPATH] [-id [DEVICEID]]
options:
-h, --help show this help message and exit
-m {c,p}, --mode {c,p}
Select camera or picture mode
-d [{cpu,cuda}], --device [{cpu,cuda}]
Run in gpu or cpu mode
-fp FOLDERPATH, --folderpath FOLDERPATH
Folder path for image(s) for image mode only
-id [DEVICEID], --deviceId [DEVICEID]
Camera deviceId /dev/videoX for camera mode only
Webcam Mode 📷
python earsegmentationai_cli.py --mode c --device cpu
python earsegmentationai_cli.py --mode c --device cuda
python earsegmentationai_cli.py --mode c --deviceId 1 --device cuda
Image Mode 🖼️
python earsegmentationai_cli.py --mode p --fp /path/xxx/
Youtube Video 📸 ✨
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