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