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121 lines
4.4 KiB
Python
121 lines
4.4 KiB
Python
#/usr/bin/env python
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import unittest
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import random
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import time
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import math
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import sys
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import array
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import urllib
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import tarfile
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import hashlib
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import os
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import getopt
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import operator
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import functools
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import numpy as np
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import cv2
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import cv2.cv as cv
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class NewOpenCVTests(unittest.TestCase):
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def get_sample(self, filename, iscolor = cv.CV_LOAD_IMAGE_COLOR):
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if not filename in self.image_cache:
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filedata = urllib.urlopen("https://raw.github.com/Itseez/opencv/master/" + 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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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()).digest()
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# Tests to run first; check the handful of basic operations that the later tests rely on
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class Hackathon244Tests(NewOpenCVTests):
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def test_int_array(self):
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a = np.array([-1, 2, -3, 4, -5])
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absa0 = np.abs(a)
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self.assert_(cv2.norm(a, cv2.NORM_L1) == 15)
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absa1 = cv2.absdiff(a, 0)
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self.assertEqual(cv2.norm(absa1, absa0, cv2.NORM_INF), 0)
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def test_imencode(self):
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a = np.zeros((480, 640), dtype=np.uint8)
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flag, ajpg = cv2.imencode("img_q90.jpg", a, [cv2.IMWRITE_JPEG_QUALITY, 90])
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self.assertEqual(flag, True)
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self.assertEqual(ajpg.dtype, np.uint8)
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self.assertGreater(ajpg.shape[0], 1)
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self.assertEqual(ajpg.shape[1], 1)
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def test_projectPoints(self):
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objpt = np.float64([[1,2,3]])
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imgpt0, jac0 = cv2.projectPoints(objpt, np.zeros(3), np.zeros(3), np.eye(3), np.float64([]))
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imgpt1, jac1 = cv2.projectPoints(objpt, np.zeros(3), np.zeros(3), np.eye(3), None)
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self.assertEqual(imgpt0.shape, (objpt.shape[0], 1, 2))
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self.assertEqual(imgpt1.shape, imgpt0.shape)
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self.assertEqual(jac0.shape, jac1.shape)
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self.assertEqual(jac0.shape[0], 2*objpt.shape[0])
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def test_estimateAffine3D(self):
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pattern_size = (11, 8)
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pattern_points = np.zeros((np.prod(pattern_size), 3), np.float32)
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pattern_points[:,:2] = np.indices(pattern_size).T.reshape(-1, 2)
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pattern_points *= 10
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(retval, out, inliers) = cv2.estimateAffine3D(pattern_points, pattern_points)
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self.assertEqual(retval, 1)
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if cv2.norm(out[2,:]) < 1e-3:
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out[2,2]=1
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self.assertLess(cv2.norm(out, np.float64([[1, 0, 0, 0], [0, 1, 0, 0], [0, 0, 1, 0]])), 1e-3)
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self.assertEqual(cv2.countNonZero(inliers), pattern_size[0]*pattern_size[1])
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def test_fast(self):
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fd = cv2.FastFeatureDetector(30, True)
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img = self.get_sample("samples/cpp/right02.jpg", 0)
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img = cv2.medianBlur(img, 3)
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imgc = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR)
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keypoints = fd.detect(img)
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self.assert_(600 <= len(keypoints) <= 700)
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for kpt in keypoints:
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self.assertNotEqual(kpt.response, 0)
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def check_close_angles(self, a, b, angle_delta):
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self.assert_(abs(a - b) <= angle_delta or
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abs(360 - abs(a - b)) <= angle_delta)
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def check_close_pairs(self, a, b, delta):
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self.assertLessEqual(abs(a[0] - b[0]), delta)
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self.assertLessEqual(abs(a[1] - b[1]), delta)
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def check_close_boxes(self, a, b, delta, angle_delta):
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self.check_close_pairs(a[0], b[0], delta)
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self.check_close_pairs(a[1], b[1], delta)
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self.check_close_angles(a[2], b[2], angle_delta)
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def test_geometry(self):
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npt = 100
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np.random.seed(244)
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a = np.random.randn(npt,2).astype('float32')*50 + 150
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img = np.zeros((300, 300, 3), dtype='uint8')
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be = cv2.fitEllipse(a)
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br = cv2.minAreaRect(a)
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mc, mr = cv2.minEnclosingCircle(a)
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be0 = ((150.2511749267578, 150.77322387695312), (158.024658203125, 197.57696533203125), 37.57804489135742)
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br0 = ((161.2974090576172, 154.41793823242188), (199.2301483154297, 207.7177734375), -9.164555549621582)
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mc0, mr0 = (160.41790771484375, 144.55152893066406), 136.713500977
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self.check_close_boxes(be, be0, 5, 15)
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self.check_close_boxes(br, br0, 5, 15)
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self.check_close_pairs(mc, mc0, 5)
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self.assertLessEqual(abs(mr - mr0), 5)
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if __name__ == '__main__':
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print "testing", cv2.__version__
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random.seed(0)
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unittest.main()
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