mirror of
https://github.com/opencv/opencv.git
synced 2024-11-30 14:29:49 +08:00
90 lines
3.5 KiB
Python
90 lines
3.5 KiB
Python
#!/usr/bin/env python
|
|
from __future__ import print_function
|
|
|
|
import numpy as np
|
|
import cv2
|
|
|
|
from tests_common import NewOpenCVTests
|
|
|
|
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)
|
|
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
|
|
|
|
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)
|
|
|
|
if __name__ == '__main__':
|
|
import unittest
|
|
unittest.main()
|