Example data for using napari-pyclesperanto-assistant

CalibZAPWfixed_000154_max.tif * Maximum projection of a part of a Drosophila melanogaster embryo showing cell divisions, marked with histone-GFP. Imaged using lightsheet microscopy in Gene Myers lab, MPI-CBG / CSBD Dresden CLIJ_benchmarking_000350.raw.tif * 3D Volume of a Drosophila melanogaster during gastrulation marked histone-GFP. Imaged using lightsheet microscopy in Gene Myers lab, MPI-CBG / CSBD Dresden. This dataset was earlier published https://bds.mpi-cbg.de/CLIJ_benchmarking_data<br> <br> EM_C_6_c0.tif2 * Arabidopsis ovule primordium * This file has been resaved to TIF * It originates from https://datadryad.org/stash/dataset/doi:10.5061/dryad.02v6wwq2c It was originally available under CC0 Public Domain by Baroux, Célia, University of Zurich, Mendocilla-Sato, Ethel, University of Zurich, Autran, Daphné, IRD Montpellier<br> <br> Haase_MRT_tfl3d1.tif * This MRI dataset of the author was acquired at University Hospital Carl Gustav Carus of the University of Technology, TU Dresden as part of academic training of students in the Department of Radiology<br> <br> tissue.tif, tissue_measurements.tif * Simulated tissue + measurement. Code provided for reporducibility: import pyclesperanto_prototype as cle<br> import numpy as np<br> import matplotlib<br> from numpy.random import random cle.select_device("RTX") # Generate artificial cells as test data<br> tissue = cle.artificial_tissue_2d() # fill it with random measurements<br> values = random([int(cle.maximum_of_all_pixels(tissue))])<br> for i, y in enumerate(values):<br> if (i != 95):<br> values[i] = values[i] * 10 + 45<br> else:<br> values[i] = values[i] * 10 + 90 measurements = cle.push(np.asarray([values])) # visualize measurements in space<br> tissue_measurements = cle.replace_intensities(tissue, measurements)