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Tetragramm
GitHub Repository: Tetragramm/opencv
 Path: blob/master/modules/python/test/test_mser.py
16337 views
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#!/usr/bin/env python

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'''

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MSER detector test

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'''

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# Python 2/3 compatibility

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from __future__ import print_function

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import numpy as np

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import cv2 as cv

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from tests_common import NewOpenCVTests

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class mser_test(NewOpenCVTests):

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    def test_mser(self):

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        img = self.get_sample('cv/mser/puzzle.png', 0)

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        smallImg = [

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         [255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255],

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         [255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255],

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         [255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255],

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         [255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255],

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         [255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255],

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         [255, 255, 255, 255, 255,   0,   0,   0,   0, 255, 255, 255, 255, 255, 255, 255, 255, 255,   0,   0,   0,   0, 255, 255, 255, 255],

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         [255, 255, 255, 255, 255,   0,   0,   0,   0,   0, 255, 255, 255, 255, 255, 255, 255, 255,   0,   0,   0,   0, 255, 255, 255, 255],

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         [255, 255, 255, 255, 255,   0,   0,   0,   0,   0, 255, 255, 255, 255, 255, 255, 255, 255,   0,   0,   0,   0, 255, 255, 255, 255],

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         [255, 255, 255, 255, 255,   0,   0,   0,   0, 255, 255, 255, 255, 255, 255, 255, 255, 255,   0,   0,   0,   0, 255, 255, 255, 255],

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         [255, 255, 255, 255, 255, 255,   0,   0, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255,   0,   0, 255, 255, 255, 255, 255],

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         [255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255],

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         [255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255],

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         [255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255],

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         [255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255, 255]

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        ]

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        thresharr = [ 0, 70, 120, 180, 255 ]

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        kDelta = 5

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        mserExtractor = cv.MSER_create()

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        mserExtractor.setDelta(kDelta)

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        np.random.seed(10)

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        for _i in range(100):

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            use_big_image = int(np.random.rand(1,1)*7) != 0

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            invert = int(np.random.rand(1,1)*2) != 0

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            binarize = int(np.random.rand(1,1)*5) != 0 if use_big_image else False

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            blur = int(np.random.rand(1,1)*2) != 0

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            thresh = thresharr[int(np.random.rand(1,1)*5)]

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            src0 = img if use_big_image else np.array(smallImg).astype('uint8')

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            src = src0.copy()

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            kMinArea = 256 if use_big_image else 10

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            kMaxArea = int(src.shape[0]*src.shape[1]/4)

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            mserExtractor.setMinArea(kMinArea)

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            mserExtractor.setMaxArea(kMaxArea)

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            if invert:

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                cv.bitwise_not(src, src)

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            if binarize:

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                _, src = cv.threshold(src, thresh, 255, cv.THRESH_BINARY)

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            if blur:

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                src = cv.GaussianBlur(src, (5, 5), 1.5, 1.5)

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            minRegs = 7 if use_big_image else 2

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            maxRegs = 1000 if use_big_image else 20

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            if binarize and (thresh == 0 or thresh == 255):

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                minRegs = maxRegs = 0

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            msers, boxes = mserExtractor.detectRegions(src)

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            nmsers = len(msers)

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            self.assertEqual(nmsers, len(boxes))

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            self.assertLessEqual(minRegs, nmsers)

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            self.assertGreaterEqual(maxRegs, nmsers)

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if __name__ == '__main__':

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    NewOpenCVTests.bootstrap()

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