Try a Colab demo

Add a shortcut to the shared demo data in your own Google Drive:

• Open the link to access the shared data: https://drive.google.com/drive/folders/1YOKEYUWadK_DwKCRzelywr_ihQchb9FV?usp=sharing.

• Add a shortcut to the shared data in your Google Drive.

  

• Save it to "My Drive".

  

• Open the Colab link: https://colab.research.google.com/drive/113uoe5Dwg_8gnNy5NWwWjKCa91qKd-25?usp=sharing

• Follow the instructions in the Colab notebook to run the demo.

Try a demo on your own computers

If you wanted to run peaknet on your own computers, please follow the installtation guide below.

Installation guide

• Make sure your sytem has conda installed, otherwise please refer to the anaconda installation page for the installation.

• Create a conda environment for running peaknet. Let'call this environment peaknet for now. Python version greater than 3.6 is required.

  conda create --name peaknet python=3.9
  

• Activate the conda environment.

  conda activate peaknet
  

• Install pip for your conda environment peaknet.

  conda install pip
  

  Then, you can use which pip to check if pip is a system-wide command or a command pointing to the conda environment.

• Install torch and cupy that require GPUs. Our cuda version is 12.0.

  # Install torch
  conda install pytorch pytorch-cuda=11.8 -c pytorch -c nvidia
  
  # Install cupy
  conda install -c conda-forge cupy
  

• Install tqdm, scikit-image and h5py.

  conda install tqdm scikit-image h5py
  

• (Demo specific) Install matplotlib for visualization using the demo.

  conda install matplotlib
  

• Finally, install peaknet directly with a github link (it should take less than one minute to install).

  pip install git+https://github.com/carbonscott/peaknet --upgrade
  

Download data and the jupyter notebook

• Download the demo data from the shared folder: https://drive.google.com/drive/folders/1YOKEYUWadK_DwKCRzelywr_ihQchb9FV?usp=sharing

  

• Download the jupyter notebook from the Colab link:

  

• Copy and paste the downloaded jupyter notebook to the folder containing the demo data.

• You can start running the notebook from the Demo section.