Open Source Computer Vision Library
https://opencv.org/
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54 lines
1.6 KiB
54 lines
1.6 KiB
#/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.assert_(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.assert_(flag == True and ajpg.dtype == np.uint8 and ajpg.shape[0] > 1 and ajpg.shape[1] == 1) |
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if __name__ == '__main__': |
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print "testing", cv.__version__ |
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random.seed(0) |
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unittest.main()
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