#!/usr/bin/env python from __future__ import print_function import unittest import random import time import math import sys import array import tarfile import hashlib import os import getopt import operator import functools import numpy as np import cv2 import argparse # 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 # 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 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()).digest() 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))) # Tests to run first; check the handful of basic operations that the later tests rely on class Hackathon244Tests(NewOpenCVTests): def test_int_array(self): a = np.array([-1, 2, -3, 4, -5]) absa0 = np.abs(a) self.assertTrue(cv2.norm(a, cv2.NORM_L1) == 15) absa1 = cv2.absdiff(a, 0) self.assertEqual(cv2.norm(absa1, absa0, cv2.NORM_INF), 0) def test_imencode(self): a = np.zeros((480, 640), dtype=np.uint8) flag, ajpg = cv2.imencode("img_q90.jpg", a, [cv2.IMWRITE_JPEG_QUALITY, 90]) self.assertEqual(flag, True) self.assertEqual(ajpg.dtype, np.uint8) self.assertGreater(ajpg.shape[0], 1) self.assertEqual(ajpg.shape[1], 1) def test_projectPoints(self): objpt = np.float64([[1,2,3]]) imgpt0, jac0 = cv2.projectPoints(objpt, np.zeros(3), np.zeros(3), np.eye(3), np.float64([])) imgpt1, jac1 = cv2.projectPoints(objpt, np.zeros(3), np.zeros(3), np.eye(3), None) self.assertEqual(imgpt0.shape, (objpt.shape[0], 1, 2)) self.assertEqual(imgpt1.shape, imgpt0.shape) self.assertEqual(jac0.shape, jac1.shape) self.assertEqual(jac0.shape[0], 2*objpt.shape[0]) def test_estimateAffine3D(self): pattern_size = (11, 8) pattern_points = np.zeros((np.prod(pattern_size), 3), np.float32) pattern_points[:,:2] = np.indices(pattern_size).T.reshape(-1, 2) pattern_points *= 10 (retval, out, inliers) = cv2.estimateAffine3D(pattern_points, pattern_points) self.assertEqual(retval, 1) if cv2.norm(out[2,:]) < 1e-3: out[2,2]=1 self.assertLess(cv2.norm(out, np.float64([[1, 0, 0, 0], [0, 1, 0, 0], [0, 0, 1, 0]])), 1e-3) self.assertEqual(cv2.countNonZero(inliers), pattern_size[0]*pattern_size[1]) def test_fast(self): fd = cv2.FastFeatureDetector_create(30, True) img = self.get_sample("samples/data/right02.jpg", 0) img = cv2.medianBlur(img, 3) imgc = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR) keypoints = fd.detect(img) self.assertTrue(600 <= len(keypoints) <= 700) for kpt in keypoints: self.assertNotEqual(kpt.response, 0) def check_close_angles(self, a, b, angle_delta): self.assertTrue(abs(a - b) <= angle_delta or abs(360 - abs(a - b)) <= angle_delta) def check_close_pairs(self, a, b, delta): self.assertLessEqual(abs(a[0] - b[0]), delta) self.assertLessEqual(abs(a[1] - b[1]), delta) def check_close_boxes(self, a, b, delta, angle_delta): self.check_close_pairs(a[0], b[0], delta) self.check_close_pairs(a[1], b[1], delta) self.check_close_angles(a[2], b[2], angle_delta) def test_geometry(self): npt = 100 np.random.seed(244) a = np.random.randn(npt,2).astype('float32')*50 + 150 img = np.zeros((300, 300, 3), dtype='uint8') be = cv2.fitEllipse(a) br = cv2.minAreaRect(a) mc, mr = cv2.minEnclosingCircle(a) be0 = ((150.2511749267578, 150.77322387695312), (158.024658203125, 197.57696533203125), 37.57804489135742) br0 = ((161.2974090576172, 154.41793823242188), (199.2301483154297, 207.7177734375), -9.164555549621582) mc0, mr0 = (160.41790771484375, 144.55152893066406), 136.713500977 self.check_close_boxes(be, be0, 5, 15) self.check_close_boxes(br, br0, 5, 15) self.check_close_pairs(mc, mc0, 5) self.assertLessEqual(abs(mr - mr0), 5) def test_inheritance(self): bm = cv2.StereoBM_create() bm.getPreFilterCap() # from StereoBM bm.getBlockSize() # from SteroMatcher boost = cv2.ml.Boost_create() boost.getBoostType() # from ml::Boost boost.getMaxDepth() # from ml::DTrees boost.isClassifier() # from ml::StatModel if __name__ == '__main__': parser = argparse.ArgumentParser(description='run OpenCV python tests') parser.add_argument('--repo', help='use sample image files from local git repository (path to folder), ' 'if not set, samples will be downloaded from github.com') parser.add_argument('--data', help=' use data files from local folder (path to folder), ' 'if not set, data files will be downloaded from docs.opencv.org') args, other = parser.parse_known_args() print("Testing OpenCV", cv2.__version__) print("Local repo path:", args.repo) NewOpenCVTests.repoPath = args.repo random.seed(0) unit_argv = [sys.argv[0]] + other; unittest.main(argv=unit_argv)