[opencv] 73/98: Fix for nonlocal data requirement in test2.py
Mattia Rizzolo
mattia at debian.org
Tue Oct 4 17:51:28 UTC 2016
This is an automated email from the git hooks/post-receive script.
mattia pushed a commit to annotated tag 2.4.13
in repository opencv.
commit 34b3d31f5499ea258ff60a2821144f903fc7a1a3
Author: Vitaly Tuzov <vitaly.tuzov at itseez.com>
Date: Tue Apr 5 11:21:22 2016 +0300
Fix for nonlocal data requirement in test2.py
---
modules/python/test/test2.py | 17 +--------
modules/python/test/ticket_6.py | 78 -----------------------------------------
2 files changed, 1 insertion(+), 94 deletions(-)
diff --git a/modules/python/test/test2.py b/modules/python/test/test2.py
index 815993e..cbdfc17 100644
--- a/modules/python/test/test2.py
+++ b/modules/python/test/test2.py
@@ -8,22 +8,7 @@ import numpy as np
import cv2
import cv2.cv as cv
-class NewOpenCVTests(unittest.TestCase):
-
- def get_sample(self, filename, iscolor = cv.CV_LOAD_IMAGE_COLOR):
- if not filename in self.image_cache:
- filedata = urllib2.urlopen("https://raw.github.com/Itseez/opencv/2.4/" + filename).read()
- image = cv2.imdecode(np.fromstring(filedata, dtype=np.uint8), iscolor)
- self.assertFalse(image is None)
- self.image_cache[filename] = image
- 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()
+from tests_common import NewOpenCVTests
# Tests to run first; check the handful of basic operations that the later tests rely on
diff --git a/modules/python/test/ticket_6.py b/modules/python/test/ticket_6.py
deleted file mode 100755
index 7249ff2..0000000
--- a/modules/python/test/ticket_6.py
+++ /dev/null
@@ -1,78 +0,0 @@
-#!/usr/bin/env python
-
-import urllib
-import cv2.cv as cv
-import Image
-import unittest
-
-class TestLoadImage(unittest.TestCase):
- def setUp(self):
- open("large.jpg", "w").write(urllib.urlopen("http://www.cs.ubc.ca/labs/lci/curious_george/img/ROS_bug_imgs/IMG_3560.jpg").read())
-
- def test_load(self):
- pilim = Image.open("large.jpg")
- cvim = cv.LoadImage("large.jpg")
- self.assert_(len(pilim.tostring()) == len(cvim.tostring()))
-
-class Creating(unittest.TestCase):
- size=(640, 480)
- repeat=100
- def test_0_Create(self):
- image = cv.CreateImage(self.size, cv.IPL_DEPTH_8U, 1)
- cnt=cv.CountNonZero(image)
- self.assertEqual(cnt, 0, msg="Created image is not black. CountNonZero=%i" % cnt)
-
- def test_2_CreateRepeat(self):
- cnt=0
- for i in range(self.repeat):
- image = cv.CreateImage(self.size, cv.IPL_DEPTH_8U, 1)
- cnt+=cv.CountNonZero(image)
- self.assertEqual(cnt, 0, msg="Created images are not black. Mean CountNonZero=%.3f" % (1.*cnt/self.repeat))
-
- def test_2a_MemCreated(self):
- cnt=0
- v=[]
- for i in range(self.repeat):
- image = cv.CreateImage(self.size, cv.IPL_DEPTH_8U, 1)
- cv.FillPoly(image, [[(0, 0), (0, 100), (100, 0)]], 0)
- cnt+=cv.CountNonZero(image)
- v.append(image)
- self.assertEqual(cnt, 0, msg="Memorized images are not black. Mean CountNonZero=%.3f" % (1.*cnt/self.repeat))
-
- def test_3_tostirng(self):
- image = cv.CreateImage(self.size, cv.IPL_DEPTH_8U, 1)
- image.tostring()
- cnt=cv.CountNonZero(image)
- self.assertEqual(cnt, 0, msg="After tostring(): CountNonZero=%i" % cnt)
-
- def test_40_tostringRepeat(self):
- cnt=0
- image = cv.CreateImage(self.size, cv.IPL_DEPTH_8U, 1)
- cv.Set(image, cv.Scalar(0,0,0,0))
- for i in range(self.repeat*100):
- image.tostring()
- cnt=cv.CountNonZero(image)
- self.assertEqual(cnt, 0, msg="Repeating tostring(): Mean CountNonZero=%.3f" % (1.*cnt/self.repeat))
-
- def test_41_CreateToStringRepeat(self):
- cnt=0
- for i in range(self.repeat*100):
- image = cv.CreateImage(self.size, cv.IPL_DEPTH_8U, 1)
- cv.Set(image, cv.Scalar(0,0,0,0))
- image.tostring()
- cnt+=cv.CountNonZero(image)
- self.assertEqual(cnt, 0, msg="Repeating create and tostring(): Mean CountNonZero=%.3f" % (1.*cnt/self.repeat))
-
- def test_4a_MemCreatedToString(self):
- cnt=0
- v=[]
- for i in range(self.repeat):
- image = cv.CreateImage(self.size, cv.IPL_DEPTH_8U, 1)
- cv.Set(image, cv.Scalar(0,0,0,0))
- image.tostring()
- cnt+=cv.CountNonZero(image)
- v.append(image)
- self.assertEqual(cnt, 0, msg="Repeating and memorizing after tostring(): Mean CountNonZero=%.3f" % (1.*cnt/self.repeat))
-
-if __name__ == '__main__':
- unittest.main()
--
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