.. note:: :class: sphx-glr-download-link-note Click :ref:`here ` to download the full example code .. rst-class:: sphx-glr-example-title .. _sphx_glr_advanced_image_processing_auto_examples_plot_watershed_segmentation.py: Watershed segmentation ======================= This example shows how to do segmentation with watershed. .. image:: /advanced/image_processing/auto_examples/images/sphx_glr_plot_watershed_segmentation_001.png :class: sphx-glr-single-img .. code-block:: python import numpy as np from skimage.morphology import watershed from skimage.feature import peak_local_max import matplotlib.pyplot as plt from scipy import ndimage # Generate an initial image with two overlapping circles x, y = np.indices((80, 80)) x1, y1, x2, y2 = 28, 28, 44, 52 r1, r2 = 16, 20 mask_circle1 = (x - x1) ** 2 + (y - y1) ** 2 < r1 ** 2 mask_circle2 = (x - x2) ** 2 + (y - y2) ** 2 < r2 ** 2 image = np.logical_or(mask_circle1, mask_circle2) # Now we want to separate the two objects in image # Generate the markers as local maxima of the distance # to the background distance = ndimage.distance_transform_edt(image) local_maxi = peak_local_max( distance, indices=False, footprint=np.ones((3, 3)), labels=image) markers = ndimage.label(local_maxi)[0] labels = watershed(-distance, markers, mask=image) plt.figure(figsize=(9, 3.5)) plt.subplot(131) plt.imshow(image, cmap='gray', interpolation='nearest') plt.axis('off') plt.subplot(132) plt.imshow(-distance, interpolation='nearest') plt.axis('off') plt.subplot(133) plt.imshow(labels, cmap='nipy_spectral', interpolation='nearest') plt.axis('off') plt.subplots_adjust(hspace=0.01, wspace=0.01, top=1, bottom=0, left=0, right=1) plt.show() **Total running time of the script:** ( 0 minutes 0.055 seconds) .. _sphx_glr_download_advanced_image_processing_auto_examples_plot_watershed_segmentation.py: .. only :: html .. container:: sphx-glr-footer :class: sphx-glr-footer-example .. container:: sphx-glr-download :download:`Download Python source code: plot_watershed_segmentation.py ` .. container:: sphx-glr-download :download:`Download Jupyter notebook: plot_watershed_segmentation.ipynb ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_