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        "author": "Yushi Yang",
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        "description": "# SegView\n\nvisualise the 3D segmentation result\n\n## Install\n\n- The most convenient way would be: `pip3 install segview`\n- You can also Include the file `segview.py` in your project directory\n\n(SegView only support Python 3.5+, because it requires `PyQt5`)\n\n## Use SegView\n\n```python\nsegview.render_label(label, metadata, alpha=1) # see the 3D model of labels\n\nsegview.annotate_label(image, label, axis=-1)  # see the 2D slice with labels along different axes\n\nsegview.render_image(image, metadata)  # see the 3D render of an image\n\nsegview.render_image(image, metadata, feature)  # see the 3D image with features\n\nsegview.annotate_feature(image, label)  # see 2D slice with features\n```\n\n- `label` is a 3D `numpy` array\n    - Usually it is the result of image segmentation, having the same structure\n    - Value `0` corresponds to the background\n    - Its shape is `(x, y, z)`.\n- `feature` is a 2D `numpy` array\n    - Usually it is the result of intensity maxima locating\n    - It is 3D positions, `[(x1, y1, z1), (x2, y2, z2), ...]`\n    - Its shape is `(feature_number, 3)`\n- `metadata` is a dictionary containing the voxel size\n    - It is only used in 3D visualisation, as many z-stack images have lower resolutions along z-axis\n    - `{'voxel_size_x': 1, 'voxel_size_y': 1, 'voxel_size_z': 1}`\n- `alpha` adjusts the brightness of the result\n\n\n",
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