fixed test_precornerdetect, test_findstereocorrespondence, test_calchist

This commit is contained in:
Alexander Shishkov 2011-06-14 13:58:02 +00:00
parent b9f5a2f4ee
commit d22b94757c
2 changed files with 65 additions and 4 deletions

View File

@ -2107,8 +2107,8 @@ class DocumentFragmentTests(OpenCVTests):
sys.path.append("../doc/python_fragments")
def test_precornerdetect(self):
from precornerdetect import precornerdetect
im = self.get_sample("samples/c/right01.jpg", 0)
from test_functions import precornerdetect
im = self.get_sample("samples/cpp/right01.jpg", 0)
imf = cv.CreateMat(im.rows, im.cols, cv.CV_32FC1)
cv.ConvertScale(im, imf)
(r0,r1) = precornerdetect(imf)
@ -2117,7 +2117,7 @@ class DocumentFragmentTests(OpenCVTests):
self.assertEqual(im.rows, r.rows)
def test_findstereocorrespondence(self):
from findstereocorrespondence import findstereocorrespondence
from test_functions import findstereocorrespondence
(l,r) = [self.get_sample("doc/pics/tsukuba_%s.png" % c, cv.CV_LOAD_IMAGE_GRAYSCALE) for c in "lr"]
(disparity_left, disparity_right) = findstereocorrespondence(l, r)
@ -2127,7 +2127,7 @@ class DocumentFragmentTests(OpenCVTests):
# self.snap(disparity_left_visual)
def test_calchist(self):
from calchist import hs_histogram
from test_functions import hs_histogram
i1 = self.get_sample("samples/c/lena.jpg")
i2 = self.get_sample("doc/pics/building.jpg")
i3 = cv.CloneMat(i1)

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@ -0,0 +1,61 @@
import sys
import cv
def hs_histogram(src):
# Convert to HSV
hsv = cv.CreateImage(cv.GetSize(src), 8, 3)
cv.CvtColor(src, hsv, cv.CV_BGR2HSV)
# Extract the H and S planes
h_plane = cv.CreateMat(src.rows, src.cols, cv.CV_8UC1)
s_plane = cv.CreateMat(src.rows, src.cols, cv.CV_8UC1)
cv.Split(hsv, h_plane, s_plane, None, None)
planes = [h_plane, s_plane]
h_bins = 30
s_bins = 32
hist_size = [h_bins, s_bins]
# hue varies from 0 (~0 deg red) to 180 (~360 deg red again */
h_ranges = [0, 180]
# saturation varies from 0 (black-gray-white) to
# 255 (pure spectrum color)
s_ranges = [0, 255]
ranges = [h_ranges, s_ranges]
scale = 10
hist = cv.CreateHist([h_bins, s_bins], cv.CV_HIST_ARRAY, ranges, 1)
cv.CalcHist([cv.GetImage(i) for i in planes], hist)
(_, max_value, _, _) = cv.GetMinMaxHistValue(hist)
hist_img = cv.CreateImage((h_bins*scale, s_bins*scale), 8, 3)
for h in range(h_bins):
for s in range(s_bins):
bin_val = cv.QueryHistValue_2D(hist, h, s)
intensity = cv.Round(bin_val * 255 / max_value)
cv.Rectangle(hist_img,
(h*scale, s*scale),
((h+1)*scale - 1, (s+1)*scale - 1),
cv.RGB(intensity, intensity, intensity),
cv.CV_FILLED)
return hist_img
def precornerdetect(image):
# assume that the image is floating-point
corners = cv.CloneMat(image)
cv.PreCornerDetect(image, corners, 3)
dilated_corners = cv.CloneMat(image)
cv.Dilate(corners, dilated_corners, None, 1)
corner_mask = cv.CreateMat(image.rows, image.cols, cv.CV_8UC1)
cv.Sub(corners, dilated_corners, corners)
cv.CmpS(corners, 0, corner_mask, cv.CV_CMP_GE)
return (corners, corner_mask)
def findstereocorrespondence(image_left, image_right):
# image_left and image_right are the input 8-bit single-channel images
# from the left and the right cameras, respectively
(r, c) = (image_left.rows, image_left.cols)
disparity_left = cv.CreateMat(r, c, cv.CV_16S)
disparity_right = cv.CreateMat(r, c, cv.CV_16S)
state = cv.CreateStereoGCState(16, 2)
cv.FindStereoCorrespondenceGC(image_left, image_right, disparity_left, disparity_right, state, 0)
return (disparity_left, disparity_right)