{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "**In case of problems or questions, please first check the list of [Frequently Asked Questions (FAQ)](https://stardist.net/docs/faq.html).**\n", "\n", "Please shutdown all other training/prediction notebooks before running this notebook (as those might occupy the GPU memory otherwise)." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Using TensorFlow backend.\n" ] } ], "source": [ "from __future__ import print_function, unicode_literals, absolute_import, division\n", "import sys\n", "import numpy as np\n", "import matplotlib\n", "matplotlib.rcParams[\"image.interpolation\"] = None\n", "import matplotlib.pyplot as plt\n", "%matplotlib inline\n", "%config InlineBackend.figure_format = 'retina'\n", "\n", "from glob import glob\n", "from tqdm import tqdm\n", "from tifffile import imread\n", "from csbdeep.utils import Path, normalize\n", "\n", "from stardist import fill_label_holes, random_label_cmap, calculate_extents, gputools_available\n", "from stardist.matching import matching, matching_dataset\n", "from stardist.models import Config2D, StarDist2D, StarDistData2D\n", "\n", "np.random.seed(42)\n", "lbl_cmap = random_label_cmap()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Data\n", "\n", "We assume that data has already been downloaded via notebook [1_data.ipynb](1_data.ipynb). \n", "\n", "