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        "author": "Casper van der Wel",
        "author_email": "caspervdw@gmail.com",
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        "description": "# pimsviewer\n[![Anaconda-Server Badge](https://anaconda.org/conda-forge/pimsviewer/badges/version.svg)](https://anaconda.org/conda-forge/pimsviewer)\n\nA graphical user interface (GUI) for PIMS (screenshot below)\n\nThis viewer was based on `skimage.viewer.CollectionViewer` ([docs](http://scikit-image.org/docs/dev/user_guide/viewer.html))\nand is able to work with N-dimensional image files that are opened by PIMS.\n\nAlso, it exposes a matplotlib plotting area on which images can be (dynamically)\nannotated, making use of the `Plugin` infrastructure.\n\n## Installation\n\nPimsviewer can be installed using conda:\n\n```\nconda install -c conda-forge pimsviewer\n```\n\nAlternatively, it can also be installed using pip:\n\n```\npip install pimsviewer \n```\n\n## Starting the viewer\n\nAfter installing the viewer, an executable `pimsviewer` is available. Simply run the command via your terminal/command line interface.\nIt is also possible to specify a reader. `pimsviewer --help` will list all installed readers, for example:\n\n```\n$ pimsviewer --help\nUsage: pimsviewer [OPTIONS] [FILE]\n\nOptions:\n  --reader-class [ImageSequenceND|NorpixSeq|SpeStack|TiffStack_pil|MoviePyReader|ImageReaderND|ReaderSequence|ImageIOReader|ImageSequence|TiffStack_tifffile|TiffSeries|TiffStack_libtiff|BioformatsReader|PyAVReaderTimed|PyAVReaderIndexed|MM_TiffStack|ImageReader|FramesSequenceND|Cine]\n                                  Reader with which to open the file.\n  --help                          Show this message and exit.\n```\n\n## Using the viewer from Python\nYou can use the viewer in a Python script as follows:\n\n```\nfrom pimsviewer import Viewer\nviewer = Viewer()\nviewer.show()\n```\nOptionally you may include a reader:\n\n```\nimport pims\nfrom pimsviewer import Viewer\nviewer = Viewer(pims.open('path/to/file'))\nviewer.show()\n```\n\n## Example: evaluating the effect of a processing function\nThis example adds a processing function that adds an adjustable amount of noise\nto an image. The amount of noise is tunable with a slider, which is displayed\non the right of the image window.\n\n```\nimport numpy as np\nimport pims\nfrom pimsviewer import Viewer, ProcessPlugin, Slider\n\nreader = pims.open('path/to/file')\n\ndef add_noise(img, noise_level):\n    return img + np.random.random(img.shape) * noise_level / 100 * img.max()\n\nAddNoise = ProcessPlugin(add_noise, 'Add noise', dock='right')\nAddNoise += Slider('noise_level', low=0, high=100, value=10,\n                   orientation='vertical')\nviewer = Viewer(reader) + AddNoise\nviewer.show()\n```\n\n## Example: annotating features on a video\nThis example annotates features that were obtained via trackpy onto a video.\n\n```\nimport trackpy as tp\nfrom pimsviewer import Viewer, AnnotatePlugin\nreader = pims.open('path/to/file')\nf = tp.batch(reader, diameter=15)\n(Viewer(reader) + AnnotatePlugin(f)).show()\n```\n\n## Example: selecting features on a video\nThis example annotates features on a video, allows to hide and move\nfeatures, and returns the adapted dataframe.\n\n```\nimport trackpy as tp\nfrom pimsviewer import Viewer, SelectionPlugin\nreader = pims.open('path/to/file')\nf = tp.batch(reader, diameter=15)\nf = tp.link_df(f, search_range=10)\nviewer = Viewer(reader) + SelectionPlugin(f)\nf_result = viewer.show()\n```\n\n## Example: designing a custom plotting function\nThis dynamically shows the effect of `tp.locate`.\n\n```\nimport trackpy as tp\nfrom pimsviewer import Viewer, Slider, PlottingPlugin\n\ndef locate_and_plot(image, radius, minmass, separation, ax):\n    f = tp.locate(image, diameter=radius * 2 + 1, minmass=minmass,\n                  separation=separation)\n    if len(f) == 0:\n        return\n    return ax.plot(f['x'], f['y'], markersize=15, markeredgewidth=2,\n                   markerfacecolor='none', markeredgecolor='r',\n                   marker='o', linestyle='none')\n\nreader = pims.open('path/to/file')\nLocate = PlottingPlugin(locate_and_plot, 'Locate', dock='right')\nLocate += Slider('radius', 2, 20, 7, value_type='int', orientation='vertical')\nLocate += Slider('separation', 1, 100, 7, value_type='float', orientation='vertical')\nLocate += Slider('minmass', 1, 10000, 100, value_type='int', orientation='vertical')\nviewer = Viewer(reader) + Locate\nviewer.show()\n```\n\n## Screenshot\n\n![Screenshot](/screenshot.png?raw=true)\n\n",
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