This document contains developer documentation for BioImage Suite Web.

Creating New BisWeb Modules in Python

Please read the JavaScript version of this document before reading this one. The JS description is more detailed and the description here simply focuses on the differences between the JS and the Python versions. Please also look at the core document BisWebPython.md for an introduction to the use of Python in the BioImage Suite Web environment.

The SmoothImage Module in Python

This module, which can be found in python/modules/smoothImage.py, directly mimics and in part depends on the JS modules from js/modules/smoothImage.js

Descriptions

The JS document describes the creation of Module descriptions. The inital Python Modules are simply adaptations of the JS modules to allow use of the C++ code from Python, and hence use the same descriptions as the paired JS modules. The only change is the mapping of true and false to True and False (Python uses uppercase boolean names). The Python file buildcpp/modules_desc.py is created by compiletools/bis_createmoduledescriptions.js. This contains “Pythonized” versions of all the module descriptions in a giant dictionary object. For the smoothImage module this has the form:

    "smoothImage": {
        "name": "Smooth",
        "description": "This algorithm performes image smoothing using a 2D/3D Gaussian kernel",
        "author": "Zach Saltzman",
        "version": "1.0",
        "inputs": [
            {
                "type": "image",
                "name": "Input Image",
                "description": "Load the image to be smoothed",
                "varname": "input",
                "shortname": "i",
                "required": True,
                "guiviewertype": "image",
                "guiviewer": "viewer1"
            }
        ],
        "outputs": [
            {
                "type": "image",
                "name": "Output Image",
                "description": "Save the output image",
                "varname": "output",
                "shortname": "o",
                "required": True,
                "extension": ".nii.gz",
                "guiviewertype": "image",
                "guiviewer": "viewer1"
            }
        ],
        "buttonName": "Smooth",
        "shortname": "sm",
        "params": [
            {
                "name": "Sigma",
                "description": "The gaussian kernel standard deviation (either in voxels or mm)",
                "priority": 1,
                "advanced": False,
                "gui": "slider",
                "varname": "sigma",
                "default": 1,
                "type": "float",
                "low": 0,
                "high": 8
            },
            {
                "name": "In mm?",
                "description": "Determines whether kernel standard deviation (sigma) will be measured in millimeters or voxels",
                "priority": 7,
                "advanced": False,
                "gui": "check",
                "varname": "inmm",
                "type": "boolean",
                "default": True
            },
            {
                "name": "Radius Factor",
                "description": "This affects the size of the convolution kernel which is computed as sigma*radius+1",
                "priority": 2,
                "advanced": True,
                "gui": "slider",
                "type": "float",
                "default": 2,
                "lowbound": 1,
                "highbound": 4,
                "varname": "radiusfactor"
            },
            {
                "name": "Debug",
                "description": "Toggles debug logging",
                "priority": 1000,
                "advanced": True,
                "gui": "check",
                "varname": "debug",
                "type": "boolean",
                "default": False
            }
        ]
    }

First comes the header

#!/usr/bin/env python3

import sys
import bis_path;
import math
import numpy as np
import argparse
import bis_basemodule
import bis_objects

This is a critical import. This module is automatically generated from JS code (using the script compiletools/bis_createmoduledescriptions.js)

import modules_desc;

This is the C++ code wrapper.

import biswrapper as libbis;

Here is the actual class:

class smoothImage(bis_basemodule.baseModule):

The constructor is practically identical to the JS version.

    def __init__(self):
        super().__init__();
        self.name='smoothImage';

The description is simply extracted from the modules_desc module.

    def createDescription(self):
        return modules_desc.descriptions['smoothImage'];

The only interesting function is directInvokeAlgorithm.

    def directInvokeAlgorithm(self,vals):
        print('oooo invoking: smoothImage with vals', vals);

        input = self.inputs['input'];
        s = (vals['sigma']);

The actual C++ call is contained in a try ... except block.

        try:
            self.outputs['output'] = libbis.gaussianSmoothImageWASM(input,
                                                                    paramobj={
                                                                        "sigmas": [s, s, s],
                                                                        "inmm": self.parseBoolean(vals['inmm']),
                                                                        "radiusfactor": vals['radiusfactor'],
                                                                    }, debug=self.parseBoolean(vals['debug']))
        except:

If this fails, print a detailed log and return False

            e = sys.exc_info()[0]
            print('---- Failed to invoke algorithm',e);
            return False

If success, return True;

        return True

if __name__ == '__main__':
    import bis_commandline;
    import bis_commandline; sys.exit(bis_commandline.loadParse(smoothImage(),sys.argv,False));

This page is part of BioImage Suite Web. We gratefully acknowledge support from the NIH Brain Initiative under grant R24 MH114805 (Papademetris X. and Scheinost D. PIs, Dept. of Radiology and Biomedical Imaging, Yale School of Medicine.)