Step 1: Install NetsPresso GUI
Install the NetsPresso GUI to enhance your training and optimization process more efficiently π.
Software Requirements
- OS: Linux, MacOS (Sonoma and later), Windows 10 (limited support)
- NetsPresso Python Package: 1.12.1
NetsPresso GUI Installation
Install Docker Image (CPU Mac only)
docker run -it -d --ipc=host --name on-prem-tester -p 7999:7998 notadevteam/on-prem-jupyter:0.2
Install Docker Image (GPU Server)
docker run -it -d --ipc=host --gpus all --name on-prem-tester -p 7999:7998 notadevteam/on-prem-jupyter:0.2
Once the pull is complete, it means the Jupyter Server has been successfully installed on your computer. You can then launch the GUI client to connect to the server.
You should see that a project folder has been created in the specified directory at 'http://localhost:7999' or compatible server IP. The sample dataset folder is pre-installed for easy model training.
The list of sample datasets are as follows:
- Image Classification - Cifar100 (link)
- Object Detection - Traffic Sign
- Semantic Segmentation - VOC2012 (link)
Server Setting
Once you have successfully installed and signed in to the NetsPresso GUI, set your server host to train your model.
Updated 1 day ago