mirror of https://github.com/opencv/opencv.git
Open Source Computer Vision Library
https://opencv.org/
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80 lines
2.6 KiB
80 lines
2.6 KiB
#!/usr/bin/env python |
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from __future__ import print_function |
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import unittest |
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import sys |
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import hashlib |
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import os |
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import numpy as np |
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import cv2 |
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# Python 3 moved urlopen to urllib.requests |
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try: |
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from urllib.request import urlopen |
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except ImportError: |
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from urllib import urlopen |
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class NewOpenCVTests(unittest.TestCase): |
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# path to local repository folder containing 'samples' folder |
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repoPath = None |
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extraTestDataPath = None |
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# github repository url |
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repoUrl = 'https://raw.github.com/opencv/opencv/master' |
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def get_sample(self, filename, iscolor = cv2.IMREAD_COLOR): |
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if not filename in self.image_cache: |
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filedata = None |
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if NewOpenCVTests.repoPath is not None: |
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candidate = NewOpenCVTests.repoPath + '/' + filename |
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if os.path.isfile(candidate): |
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with open(candidate, 'rb') as f: |
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filedata = f.read() |
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if NewOpenCVTests.extraTestDataPath is not None: |
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candidate = NewOpenCVTests.extraTestDataPath + '/' + filename |
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if os.path.isfile(candidate): |
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with open(candidate, 'rb') as f: |
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filedata = f.read() |
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if filedata is None: |
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return None#filedata = urlopen(NewOpenCVTests.repoUrl + '/' + filename).read() |
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self.image_cache[filename] = cv2.imdecode(np.fromstring(filedata, dtype=np.uint8), iscolor) |
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return self.image_cache[filename] |
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def setUp(self): |
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cv2.setRNGSeed(10) |
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self.image_cache = {} |
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def hashimg(self, im): |
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""" Compute a hash for an image, useful for image comparisons """ |
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return hashlib.md5(im.tostring()).hexdigest() |
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if sys.version_info[:2] == (2, 6): |
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def assertLess(self, a, b, msg=None): |
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if not a < b: |
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self.fail('%s not less than %s' % (repr(a), repr(b))) |
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def assertLessEqual(self, a, b, msg=None): |
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if not a <= b: |
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self.fail('%s not less than or equal to %s' % (repr(a), repr(b))) |
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def assertGreater(self, a, b, msg=None): |
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if not a > b: |
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self.fail('%s not greater than %s' % (repr(a), repr(b))) |
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def intersectionRate(s1, s2): |
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x1, y1, x2, y2 = s1 |
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s1 = np.array([[x1, y1], [x2,y1], [x2, y2], [x1, y2]]) |
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x1, y1, x2, y2 = s2 |
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s2 = np.array([[x1, y1], [x2,y1], [x2, y2], [x1, y2]]) |
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area, intersection = cv2.intersectConvexConvex(s1, s2) |
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return 2 * area / (cv2.contourArea(s1) + cv2.contourArea(s2)) |
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def isPointInRect(p, rect): |
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if rect[0] <= p[0] and rect[1] <=p[1] and p[0] <= rect[2] and p[1] <= rect[3]: |
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return True |
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else: |
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return False |