A collection of tools for painting super-resolution images. The Picasso software is complemented by our Nature Protocols publication (https://www.nature.com/nprot/journal/v12/n6/abs/nprot.2017.024.html).
Download and run the one-click installer file for Windows from http://www.jungmannlab.org/. Note that this is the Picasso version presented in the Nature Protocols publication. Feel free to reach out via picasso@jungmannlab.org to get the latest installer of the current commit. For the platform-independent usage of Picasso (e.g., with Linux and Mac Os X) please follow the advanced installation instructions.
As an alternative to the stand-alone program for end-users, Picasso can be installed as a Python package. This is the preferred option to use Picasso's internal routines in custom Python programs. For windows, one is still possible to use Picasso as an end-user by creating the respective shortcuts. This allows Picasso to be used on the same system by both programmers and end-users.
We highly recommend the Anaconda or Miniconda Python distribution which comes with a powerful package manager.
The following packages are required:
h5py matplotlib numba numpy scipy pyqt=4 pyyaml scikit-learn colorama lmfit tqdm
When using Anaconda or Miniconda, most can be installed via conda install <package>. However, some packages need to be obtained from third-party conda channels. Visit anaconda.org to search for them. Use pip as a last resort to install packages from PyPi. See instructions below as reference:
Sample instructions to create an environment with conda are as follows:
- Open the console and create a new conda environment:
conda create --name picasso python=3.5 - Activate the environment:
source activate picassofor Linux / Mac Os X oractivate picassofor Windows. - Install the necessary packages with conda:
conda install h5py matplotlib numba numpy scipy pyqt=4 pyyaml scikit-learn colorama tqdm - Additionally install packages with pip:
pip install lmfit - Continue with Installation
- Note that sometimes outdated packages can cause problems. If you experience errors, please check whether your packages have the right version (e.g. see issue #4).
- Open the console,
cdto the directory where you want to install and rungit clone https://github.com/jungmannlab/picassoAlternatively, download the zip file and unzip it. - Change to the downloaded directory and run
python setup.py install.
Run the PowerShell script "createShortcuts.ps1" in the gui directory.
This should be doable by right-clicking on the script and choosing "Run with PowerShell". Alternatively, run the command powershell ./createShortcuts.ps1 in the command line. Use the generated shortcuts in the top level directory to start GUI components. Users can drag these shortcuts to their Desktop, Start Menu or Task Bar.
The individual modules of picasso can be started as follows:
- Open the console, activate the enviroment:
source activate picassofor Linux / Mac Os X oractivate picassofor Windows. - Start the picasso modules via
python -m picasso .., e.g.python -m picasso renderfor the render module
To enable GPU fitting, follow instructions on Gpufit to install the Gpufit python library in your conda environment. Picasso Localize will automatically import the library if present and enables a checkbox for GPU fitting when selecting the LQ-Method.
Contributors: Joerg Schnitzbauer, Maximilian Strauss
Copyright (c) 2015-2018 Jungmann Lab, Max Planck Institute of Biochemistry
- Design icon based on "Hexagon by Creative Stalls from the Noun Project"
- Simulate icon based on "Microchip by Futishia from the Nount Project"
- Localize icon based on "Mountains by MONTANA RUCOBO from the Noun Project"
- Filter icon based on "Funnel by José Campos from the Noun Project"
- Render icon based on "Paint Palette by Vectors Market from the Noun Project"
- Average icon based on "Layers by Creative Stall from the Noun Project"