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提交 f886651c 编写于 作者: A Andrey Kamaev
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Drop old python samples and tests

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Showing with 161 addition and 5434 deletion
modules/python/src2/cv2.cpp
浏览文件 @ f886651c
......@@ -1102,6 +1102,17 @@ static PyObject *pycvCreateTrackbar(PyObject*, PyObject *args)
///////////////////////////////////////////////////////////////////////////////////////
static int convert_to_char(PyObject *o, char *dst, const char *name = "no_name")
{
if (PyString_Check(o) && PyString_Size(o) == 1) {
*dst = PyString_AsString(o)[0];
return 1;
} else {
(*dst) = 0;
return failmsg("Expected single character string for argument '%s'", name);
}
}
#define MKTYPE2(NAME) pyopencv_##NAME##_specials(); if (!to_ok(&pyopencv_##NAME##_Type)) return
#ifdef __GNUC__
......
modules/python/src2/gen2.py
浏览文件 @ f886651c
......@@ -213,7 +213,6 @@ gen_template_rw_prop_init = Template("""
simple_argtype_mapping = {
"bool": ("bool", "b", "0"),
"char": ("char", "b", "0"),
"int": ("int", "i", "0"),
"float": ("float", "f", "0.f"),
"double": ("double", "d", "0"),
......@@ -619,7 +618,10 @@ class FuncInfo(object):
if amapping[1] == "O":
code_decl += " PyObject* pyobj_%s = NULL;\n" % (a.name,)
parse_name = "pyobj_" + a.name
code_cvt_list.append("pyopencv_to(pyobj_%s, %s, %s)" % (a.name, a.name, a.crepr()))
if a.tp == 'char':
code_cvt_list.append("convert_to_char(pyobj_%s, &%s, %s)"% (a.name, a.name, a.crepr()))
else:
code_cvt_list.append("pyopencv_to(pyobj_%s, %s, %s)" % (a.name, a.name, a.crepr()))
all_cargs.append([amapping, parse_name])
......
modules/python/test/test.py 100755 → 100644
浏览文件 @ f886651c
此差异已折叠。
modules/python/test/test2.py 已删除 100644 → 0
浏览文件 @ b2ba8b99
#!/usr/bin/env python
import unittest
import random
import time
import math
import sys
import array
import urllib
import tarfile
import hashlib
import os
import getopt
import operator
import functools
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 = urllib.urlopen("https://raw.github.com/Itseez/opencv/master/" + filename).read()
self.image_cache[filename] = cv2.imdecode(np.fromstring(filedata, dtype=np.uint8), iscolor)
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()
if sys.version_info[:2] == (2, 6):
def assertLess(self, a, b, msg=None):
if not a < b:
self.fail('%s not less than %s' % (repr(a), repr(b)))
def assertLessEqual(self, a, b, msg=None):
if not a <= b:
self.fail('%s not less than or equal to %s' % (repr(a), repr(b)))
def assertGreater(self, a, b, msg=None):
if not a > b:
self.fail('%s not greater than %s' % (repr(a), repr(b)))
# Tests to run first; check the handful of basic operations that the later tests rely on
class Hackathon244Tests(NewOpenCVTests):
def test_int_array(self):
a = np.array([-1, 2, -3, 4, -5])
absa0 = np.abs(a)
self.assert_(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(30, True)
img = self.get_sample("samples/cpp/right02.jpg", 0)
img = cv2.medianBlur(img, 3)
imgc = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR)
keypoints = fd.detect(img)
self.assert_(600 <= len(keypoints) <= 700)
for kpt in keypoints:
self.assertNotEqual(kpt.response, 0)
def check_close_angles(self, a, b, angle_delta):
self.assert_(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
img = np.zeros((300, 300, 3), dtype='uint8')
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__':
print "testing", cv2.__version__
random.seed(0)
unittest.main()
samples/python/camera.py 已删除 100755 → 0
浏览文件 @ b2ba8b99
#!/usr/bin/python
import cv2.cv as cv
import time
cv.NamedWindow("camera", 1)
capture = cv.CaptureFromCAM(0)
while True:
img = cv.QueryFrame(capture)
cv.ShowImage("camera", img)
if cv.WaitKey(10) == 27:
break
cv.DestroyAllWindows()
samples/python/camshift.py 已删除 100755 → 0
浏览文件 @ b2ba8b99
#!/usr/bin/env python
import cv2.cv as cv
def is_rect_nonzero(r):
(_,_,w,h) = r
return (w > 0) and (h > 0)
class CamShiftDemo:
def __init__(self):
self.capture = cv.CaptureFromCAM(0)
cv.NamedWindow( "CamShiftDemo", 1 )
cv.NamedWindow( "Histogram", 1 )
cv.SetMouseCallback( "CamShiftDemo", self.on_mouse)
self.drag_start = None # Set to (x,y) when mouse starts drag
self.track_window = None # Set to rect when the mouse drag finishes
print( "Keys:\n"
" ESC - quit the program\n"
" b - switch to/from backprojection view\n"
"To initialize tracking, drag across the object with the mouse\n" )
def hue_histogram_as_image(self, hist):
""" Returns a nice representation of a hue histogram """
histimg_hsv = cv.CreateImage( (320,200), 8, 3)
mybins = cv.CloneMatND(hist.bins)
cv.Log(mybins, mybins)
(_, hi, _, _) = cv.MinMaxLoc(mybins)
cv.ConvertScale(mybins, mybins, 255. / hi)
w,h = cv.GetSize(histimg_hsv)
hdims = cv.GetDims(mybins)[0]
for x in range(w):
xh = (180 * x) / (w - 1) # hue sweeps from 0-180 across the image
val = int(mybins[int(hdims * x / w)] * h / 255)
cv.Rectangle( histimg_hsv, (x, 0), (x, h-val), (xh,255,64), -1)
cv.Rectangle( histimg_hsv, (x, h-val), (x, h), (xh,255,255), -1)
histimg = cv.CreateImage( (320,200), 8, 3)
cv.CvtColor(histimg_hsv, histimg, cv.CV_HSV2BGR)
return histimg
def on_mouse(self, event, x, y, flags, param):
if event == cv.CV_EVENT_LBUTTONDOWN:
self.drag_start = (x, y)
if event == cv.CV_EVENT_LBUTTONUP:
self.drag_start = None
self.track_window = self.selection
if self.drag_start:
xmin = min(x, self.drag_start[0])
ymin = min(y, self.drag_start[1])
xmax = max(x, self.drag_start[0])
ymax = max(y, self.drag_start[1])
self.selection = (xmin, ymin, xmax - xmin, ymax - ymin)
def run(self):
hist = cv.CreateHist([180], cv.CV_HIST_ARRAY, [(0,180)], 1 )
backproject_mode = False
while True:
frame = cv.QueryFrame( self.capture )
# Convert to HSV and keep the hue
hsv = cv.CreateImage(cv.GetSize(frame), 8, 3)
cv.CvtColor(frame, hsv, cv.CV_BGR2HSV)
self.hue = cv.CreateImage(cv.GetSize(frame), 8, 1)
cv.Split(hsv, self.hue, None, None, None)
# Compute back projection
backproject = cv.CreateImage(cv.GetSize(frame), 8, 1)
# Run the cam-shift
cv.CalcArrBackProject( [self.hue], backproject, hist )
if self.track_window and is_rect_nonzero(self.track_window):
crit = ( cv.CV_TERMCRIT_EPS | cv.CV_TERMCRIT_ITER, 10, 1)
(iters, (area, value, rect), track_box) = cv.CamShift(backproject, self.track_window, crit)
self.track_window = rect
# If mouse is pressed, highlight the current selected rectangle
# and recompute the histogram
if self.drag_start and is_rect_nonzero(self.selection):
sub = cv.GetSubRect(frame, self.selection)
save = cv.CloneMat(sub)
cv.ConvertScale(frame, frame, 0.5)
cv.Copy(save, sub)
x,y,w,h = self.selection
cv.Rectangle(frame, (x,y), (x+w,y+h), (255,255,255))
sel = cv.GetSubRect(self.hue, self.selection )
cv.CalcArrHist( [sel], hist, 0)
(_, max_val, _, _) = cv.GetMinMaxHistValue( hist)
if max_val != 0:
cv.ConvertScale(hist.bins, hist.bins, 255. / max_val)
elif self.track_window and is_rect_nonzero(self.track_window):
cv.EllipseBox( frame, track_box, cv.CV_RGB(255,0,0), 3, cv.CV_AA, 0 )
if not backproject_mode:
cv.ShowImage( "CamShiftDemo", frame )
else:
cv.ShowImage( "CamShiftDemo", backproject)
cv.ShowImage( "Histogram", self.hue_histogram_as_image(hist))
c = cv.WaitKey(7) % 0x100
if c == 27:
break
elif c == ord("b"):
backproject_mode = not backproject_mode
if __name__=="__main__":
demo = CamShiftDemo()
demo.run()
cv.DestroyAllWindows()
samples/python/chessboard.py 已删除 100755 → 0
浏览文件 @ b2ba8b99
#!/usr/bin/python
import cv2.cv as cv
import sys
import urllib2
if __name__ == "__main__":
cv.NamedWindow("win")
if len(sys.argv) > 1:
filename = sys.argv[1]
im = cv.LoadImage(filename, cv.CV_LOAD_IMAGE_GRAYSCALE)
im3 = cv.LoadImage(filename, cv.CV_LOAD_IMAGE_COLOR)
else:
try: # try opening local copy of image
fileName = '../cpp/left01.jpg'
im = cv.LoadImageM(fileName, False)
im3 = cv.LoadImageM(fileName, True)
except: # if local copy cannot be opened, try downloading it
url = 'http://code.opencv.org/projects/opencv/repository/revisions/master/raw/samples/cpp/left01.jpg'
filedata = urllib2.urlopen(url).read()
imagefiledata = cv.CreateMatHeader(1, len(filedata), cv.CV_8UC1)
cv.SetData(imagefiledata, filedata, len(filedata))
im = cv.DecodeImageM(imagefiledata, cv.CV_LOAD_IMAGE_GRAYSCALE)
im3 = cv.DecodeImageM(imagefiledata, cv.CV_LOAD_IMAGE_COLOR)
chessboard_dim = ( 9, 6 )
found_all, corners = cv.FindChessboardCorners( im, chessboard_dim )
print found_all, len(corners)
cv.DrawChessboardCorners( im3, chessboard_dim, corners, found_all )
cv.ShowImage("win", im3);
cv.WaitKey()
cv.DestroyAllWindows()
samples/python/contours.py 已删除 100755 → 0
浏览文件 @ b2ba8b99
#! /usr/bin/env python
print "OpenCV Python version of contours"
# import the necessary things for OpenCV
import cv2.cv as cv
# some default constants
_SIZE = 500
_DEFAULT_LEVEL = 3
# definition of some colors
_red = (0, 0, 255, 0);
_green = (0, 255, 0, 0);
_white = cv.RealScalar (255)
_black = cv.RealScalar (0)
# the callback on the trackbar, to set the level of contours we want
# to display
def on_trackbar (position):
# create the image for putting in it the founded contours
contours_image = cv.CreateImage ( (_SIZE, _SIZE), 8, 3)
# compute the real level of display, given the current position
levels = position - 3
# initialisation
_contours = contours
if levels <= 0:
# zero or negative value
# => get to the nearest face to make it look more funny
_contours = contours.h_next().h_next().h_next()
# first, clear the image where we will draw contours
cv.SetZero (contours_image)
# draw contours in red and green
cv.DrawContours (contours_image, _contours,
_red, _green,
levels, 3, cv.CV_AA,
(0, 0))
# finally, show the image
cv.ShowImage ("contours", contours_image)
if __name__ == '__main__':
# create the image where we want to display results
image = cv.CreateImage ( (_SIZE, _SIZE), 8, 1)
# start with an empty image
cv.SetZero (image)
# draw the original picture
for i in range (6):
dx = (i % 2) * 250 - 30
dy = (i / 2) * 150
cv.Ellipse (image,
(dx + 150, dy + 100),
(100, 70),
0, 0, 360, _white, -1, 8, 0)
cv.Ellipse (image,
(dx + 115, dy + 70),
(30, 20),
0, 0, 360, _black, -1, 8, 0)
cv.Ellipse (image,
(dx + 185, dy + 70),
(30, 20),
0, 0, 360, _black, -1, 8, 0)
cv.Ellipse (image,
(dx + 115, dy + 70),
(15, 15),
0, 0, 360, _white, -1, 8, 0)
cv.Ellipse (image,
(dx + 185, dy + 70),
(15, 15),
0, 0, 360, _white, -1, 8, 0)
cv.Ellipse (image,
(dx + 115, dy + 70),
(5, 5),
0, 0, 360, _black, -1, 8, 0)
cv.Ellipse (image,
(dx + 185, dy + 70),
(5, 5),
0, 0, 360, _black, -1, 8, 0)
cv.Ellipse (image,
(dx + 150, dy + 100),
(10, 5),
0, 0, 360, _black, -1, 8, 0)
cv.Ellipse (image,
(dx + 150, dy + 150),
(40, 10),
0, 0, 360, _black, -1, 8, 0)
cv.Ellipse (image,
(dx + 27, dy + 100),
(20, 35),
0, 0, 360, _white, -1, 8, 0)
cv.Ellipse (image,
(dx + 273, dy + 100),
(20, 35),
0, 0, 360, _white, -1, 8, 0)
# create window and display the original picture in it
cv.NamedWindow ("image", 1)
cv.ShowImage ("image", image)
# create the storage area
storage = cv.CreateMemStorage (0)
# find the contours
contours = cv.FindContours(image,
storage,
cv.CV_RETR_TREE,
cv.CV_CHAIN_APPROX_SIMPLE,
(0,0))
# comment this out if you do not want approximation
contours = cv.ApproxPoly (contours,
storage,
cv.CV_POLY_APPROX_DP, 3, 1)
# create the window for the contours
cv.NamedWindow ("contours", 1)
# create the trackbar, to enable the change of the displayed level
cv.CreateTrackbar ("levels+3", "contours", 3, 7, on_trackbar)
# call one time the callback, so we will have the 1st display done
on_trackbar (_DEFAULT_LEVEL)
# wait a key pressed to end
cv.WaitKey (0)
cv.DestroyAllWindows()
samples/python/convexhull.py 已删除 100755 → 0
浏览文件 @ b2ba8b99
#! /usr/bin/env python
print "OpenCV Python version of convexhull"
# import the necessary things for OpenCV
import cv2.cv as cv
# to generate random values
import random
# how many points we want at max
_MAX_POINTS = 100
if __name__ == '__main__':
# main object to get random values from
my_random = random.Random ()
# create the image where we want to display results
image = cv.CreateImage ( (500, 500), 8, 3)
# create the window to put the image in
cv.NamedWindow ('hull', cv.CV_WINDOW_AUTOSIZE)
while True:
# do forever
# get a random number of points
count = my_random.randrange (0, _MAX_POINTS) + 1
# initialisations
points = []
for i in range (count):
# generate a random point
points.append ( (
my_random.randrange (0, image.width / 2) + image.width / 4,
my_random.randrange (0, image.width / 2) + image.width / 4
))
# compute the convex hull
storage = cv.CreateMemStorage(0)
hull = cv.ConvexHull2 (points, storage, cv.CV_CLOCKWISE, 1)
# start with an empty image
cv.SetZero (image)
# draw all the points as circles in red
for i in range (count):
cv.Circle (image, points [i], 2,
(0, 0, 255, 0),
cv.CV_FILLED, cv.CV_AA, 0)
# Draw the convex hull as a closed polyline in green
cv.PolyLine(image, [hull], 1, cv.RGB(0,255,0), 1, cv.CV_AA)
# display the final image
cv.ShowImage ('hull', image)
# handle events, and wait a key pressed
k = cv.WaitKey (0) % 0x100
if k == 27:
# user has press the ESC key, so exit
break
cv.DestroyAllWindows()
samples/python/cv20squares.py 已删除 100755 → 0
浏览文件 @ b2ba8b99
#!/usr/bin/python
"""
Find Squares in image by finding countours and filtering
"""
#Results slightly different from C version on same images, but is
#otherwise ok
import math
import cv2.cv as cv
def angle(pt1, pt2, pt0):
"calculate angle contained by 3 points(x, y)"
dx1 = pt1[0] - pt0[0]
dy1 = pt1[1] - pt0[1]
dx2 = pt2[0] - pt0[0]
dy2 = pt2[1] - pt0[1]
nom = dx1*dx2 + dy1*dy2
denom = math.sqrt( (dx1*dx1 + dy1*dy1) * (dx2*dx2 + dy2*dy2) + 1e-10 )
ang = nom / denom
return ang
def is_square(contour):
"""
Squareness checker
Square contours should:
-have 4 vertices after approximation,
-have relatively large area (to filter out noisy contours)
-be convex.
-have angles between sides close to 90deg (cos(ang) ~0 )
Note: absolute value of an area is used because area may be
positive or negative - in accordance with the contour orientation
"""
area = math.fabs( cv.ContourArea(contour) )
isconvex = cv.CheckContourConvexity(contour)
s = 0
if len(contour) == 4 and area > 1000 and isconvex:
for i in range(1, 4):
# find minimum angle between joint edges (maximum of cosine)
pt1 = contour[i]
pt2 = contour[i-1]
pt0 = contour[i-2]
t = math.fabs(angle(pt0, pt1, pt2))
if s <= t:s = t
# if cosines of all angles are small (all angles are ~90 degree)
# then its a square
if s < 0.3:return True
return False
def find_squares_from_binary( gray ):
"""
use contour search to find squares in binary image
returns list of numpy arrays containing 4 points
"""
squares = []
storage = cv.CreateMemStorage(0)
contours = cv.FindContours(gray, storage, cv.CV_RETR_TREE, cv.CV_CHAIN_APPROX_SIMPLE, (0,0))
storage = cv.CreateMemStorage(0)
while contours:
#approximate contour with accuracy proportional to the contour perimeter
arclength = cv.ArcLength(contours)
polygon = cv.ApproxPoly( contours, storage, cv.CV_POLY_APPROX_DP, arclength * 0.02, 0)
if is_square(polygon):
squares.append(polygon[0:4])
contours = contours.h_next()
return squares
def find_squares4(color_img):
"""
Finds multiple squares in image
Steps:
-Use Canny edge to highlight contours, and dilation to connect
the edge segments.
-Threshold the result to binary edge tokens
-Use cv.FindContours: returns a cv.CvSequence of cv.CvContours
-Filter each candidate: use Approx poly, keep only contours with 4 vertices,
enough area, and ~90deg angles.
Return all squares contours in one flat list of arrays, 4 x,y points each.
"""
#select even sizes only
width, height = (color_img.width & -2, color_img.height & -2 )
timg = cv.CloneImage( color_img ) # make a copy of input image
gray = cv.CreateImage( (width,height), 8, 1 )
# select the maximum ROI in the image
cv.SetImageROI( timg, (0, 0, width, height) )
# down-scale and upscale the image to filter out the noise
pyr = cv.CreateImage( (width/2, height/2), 8, 3 )
cv.PyrDown( timg, pyr, 7 )
cv.PyrUp( pyr, timg, 7 )
tgray = cv.CreateImage( (width,height), 8, 1 )
squares = []
# Find squares in every color plane of the image
# Two methods, we use both:
# 1. Canny to catch squares with gradient shading. Use upper threshold
# from slider, set the lower to 0 (which forces edges merging). Then
# dilate canny output to remove potential holes between edge segments.
# 2. Binary thresholding at multiple levels
N = 11
for c in [0, 1, 2]:
#extract the c-th color plane
cv.SetImageCOI( timg, c+1 );
cv.Copy( timg, tgray, None );
cv.Canny( tgray, gray, 0, 50, 5 )
cv.Dilate( gray, gray)
squares = squares + find_squares_from_binary( gray )
# Look for more squares at several threshold levels
for l in range(1, N):
cv.Threshold( tgray, gray, (l+1)*255/N, 255, cv.CV_THRESH_BINARY )
squares = squares + find_squares_from_binary( gray )
return squares
RED = (0,0,255)
GREEN = (0,255,0)
def draw_squares( color_img, squares ):
"""
Squares is py list containing 4-pt numpy arrays. Step through the list
and draw a polygon for each 4-group
"""
color, othercolor = RED, GREEN
for square in squares:
cv.PolyLine(color_img, [square], True, color, 3, cv.CV_AA, 0)
color, othercolor = othercolor, color
cv.ShowImage(WNDNAME, color_img)
WNDNAME = "Squares Demo"
def main():
"""Open test color images, create display window, start the search"""
cv.NamedWindow(WNDNAME, 1)
for name in [ "../c/pic%d.png" % i for i in [1, 2, 3, 4, 5, 6] ]:
img0 = cv.LoadImage(name, 1)
try:
img0
except ValueError:
print "Couldn't load %s\n" % name
continue
# slider deleted from C version, same here and use fixed Canny param=50
img = cv.CloneImage(img0)
cv.ShowImage(WNDNAME, img)
# force the image processing
draw_squares( img, find_squares4( img ) )
# wait for key.
if cv.WaitKey(-1) % 0x100 == 27:
break
if __name__ == "__main__":
main()
cv.DestroyAllWindows()
samples/python/cvutils.py 已删除 100755 → 0
浏览文件 @ b2ba8b99
#!/usr/bin/python
import cv2.cv as cv
import urllib2
from sys import argv
def load_sample(name=None):
if len(argv) > 1:
img0 = cv.LoadImage(argv[1], cv.CV_LOAD_IMAGE_COLOR)
elif name is not None:
try:
img0 = cv.LoadImage(name, cv.CV_LOAD_IMAGE_COLOR)
except IOError:
urlbase = 'http://code.opencv.org/projects/opencv/repository/revisions/master/raw/samples/c/'
file = name.split('/')[-1]
filedata = urllib2.urlopen(urlbase+file).read()
imagefiledata = cv.CreateMatHeader(1, len(filedata), cv.CV_8UC1)
cv.SetData(imagefiledata, filedata, len(filedata))
img0 = cv.DecodeImage(imagefiledata, cv.CV_LOAD_IMAGE_COLOR)
return img0
samples/python/delaunay.py 已删除 100755 → 0
浏览文件 @ b2ba8b99
#!/usr/bin/python
"""
the script demostrates iterative construction of
delaunay triangulation and voronoi tesselation
Original Author (C version): ?
Converted to Python by: Roman Stanchak
"""
import cv2.cv as cv
import random
def draw_subdiv_point( img, fp, color ):
cv.Circle( img, (cv.Round(fp[0]), cv.Round(fp[1])), 3, color, cv.CV_FILLED, 8, 0 );
def draw_subdiv_edge( img, edge, color ):
org_pt = cv.Subdiv2DEdgeOrg(edge);
dst_pt = cv.Subdiv2DEdgeDst(edge);
if org_pt and dst_pt :
org = org_pt.pt;
dst = dst_pt.pt;
iorg = ( cv.Round( org[0] ), cv.Round( org[1] ));
idst = ( cv.Round( dst[0] ), cv.Round( dst[1] ));
cv.Line( img, iorg, idst, color, 1, cv.CV_AA, 0 );
def draw_subdiv( img, subdiv, delaunay_color, voronoi_color ):
for edge in subdiv.edges:
edge_rot = cv.Subdiv2DRotateEdge( edge, 1 )
draw_subdiv_edge( img, edge_rot, voronoi_color );
draw_subdiv_edge( img, edge, delaunay_color );
def locate_point( subdiv, fp, img, active_color ):
(res, e0) = cv.Subdiv2DLocate( subdiv, fp );
if res in [ cv.CV_PTLOC_INSIDE, cv.CV_PTLOC_ON_EDGE ]:
e = e0
while True:
draw_subdiv_edge( img, e, active_color );
e = cv.Subdiv2DGetEdge(e, cv.CV_NEXT_AROUND_LEFT);
if e == e0:
break
draw_subdiv_point( img, fp, active_color );
def draw_subdiv_facet( img, edge ):
t = edge;
count = 0;
# count number of edges in facet
while count == 0 or t != edge:
count+=1
t = cv.Subdiv2DGetEdge( t, cv.CV_NEXT_AROUND_LEFT );
buf = []
# gather points
t = edge;
for i in range(count):
assert t>4
pt = cv.Subdiv2DEdgeOrg( t );
if not pt:
break;
buf.append( ( cv.Round(pt.pt[0]), cv.Round(pt.pt[1]) ) );
t = cv.Subdiv2DGetEdge( t, cv.CV_NEXT_AROUND_LEFT );
if( len(buf)==count ):
pt = cv.Subdiv2DEdgeDst( cv.Subdiv2DRotateEdge( edge, 1 ));
cv.FillConvexPoly( img, buf, cv.RGB(random.randrange(256),random.randrange(256),random.randrange(256)), cv.CV_AA, 0 );
cv.PolyLine( img, [buf], 1, cv.RGB(0,0,0), 1, cv.CV_AA, 0);
draw_subdiv_point( img, pt.pt, cv.RGB(0,0,0));
def paint_voronoi( subdiv, img ):
cv.CalcSubdivVoronoi2D( subdiv );
for edge in subdiv.edges:
# left
draw_subdiv_facet( img, cv.Subdiv2DRotateEdge( edge, 1 ));
# right
draw_subdiv_facet( img, cv.Subdiv2DRotateEdge( edge, 3 ));
if __name__ == '__main__':
win = "source";
rect = ( 0, 0, 600, 600 );
active_facet_color = cv.RGB( 255, 0, 0 );
delaunay_color = cv.RGB( 0,0,0);
voronoi_color = cv.RGB(0, 180, 0);
bkgnd_color = cv.RGB(255,255,255);
img = cv.CreateImage( (rect[2],rect[3]), 8, 3 );
cv.Set( img, bkgnd_color );
cv.NamedWindow( win, 1 );
storage = cv.CreateMemStorage(0);
subdiv = cv.CreateSubdivDelaunay2D( rect, storage );
print "Delaunay triangulation will be build now interactively."
print "To stop the process, press any key\n";
for i in range(200):
fp = ( random.random()*(rect[2]-10)+5, random.random()*(rect[3]-10)+5 )
locate_point( subdiv, fp, img, active_facet_color );
cv.ShowImage( win, img );
if( cv.WaitKey( 100 ) >= 0 ):
break;
cv.SubdivDelaunay2DInsert( subdiv, fp );
cv.CalcSubdivVoronoi2D( subdiv );
cv.Set( img, bkgnd_color );
draw_subdiv( img, subdiv, delaunay_color, voronoi_color );
cv.ShowImage( win, img );
if( cv.WaitKey( 100 ) >= 0 ):
break;
cv.Set( img, bkgnd_color );
paint_voronoi( subdiv, img );
cv.ShowImage( win, img );
cv.WaitKey(0);
cv.DestroyWindow( win );
samples/python/demhist.py 已删除 100755 → 0
浏览文件 @ b2ba8b99
#!/usr/bin/python
import cv2.cv as cv
import sys
import urllib2
hist_size = 64
range_0 = [0, 256]
ranges = [ range_0 ]
class DemHist:
def __init__(self, src_image):
self.src_image = src_image
self.dst_image = cv.CloneMat(src_image)
self.hist_image = cv.CreateImage((320, 200), 8, 1)
self.hist = cv.CreateHist([hist_size], cv.CV_HIST_ARRAY, ranges, 1)
self.brightness = 0
self.contrast = 0
cv.NamedWindow("image", 0)
cv.NamedWindow("histogram", 0)
cv.CreateTrackbar("brightness", "image", 100, 200, self.update_brightness)
cv.CreateTrackbar("contrast", "image", 100, 200, self.update_contrast)
self.update_brightcont()
def update_brightness(self, val):
self.brightness = val - 100
self.update_brightcont()
def update_contrast(self, val):
self.contrast = val - 100
self.update_brightcont()
def update_brightcont(self):
# The algorithm is by Werner D. Streidt
# (http://visca.com/ffactory/archives/5-99/msg00021.html)
if self.contrast > 0:
delta = 127. * self.contrast / 100
a = 255. / (255. - delta * 2)
b = a * (self.brightness - delta)
else:
delta = -128. * self.contrast / 100
a = (256. - delta * 2) / 255.
b = a * self.brightness + delta
cv.ConvertScale(self.src_image, self.dst_image, a, b)
cv.ShowImage("image", self.dst_image)
cv.CalcArrHist([self.dst_image], self.hist)
(min_value, max_value, _, _) = cv.GetMinMaxHistValue(self.hist)
cv.Scale(self.hist.bins, self.hist.bins, float(self.hist_image.height) / max_value, 0)
cv.Set(self.hist_image, cv.ScalarAll(255))
bin_w = round(float(self.hist_image.width) / hist_size)
for i in range(hist_size):
cv.Rectangle(self.hist_image, (int(i * bin_w), self.hist_image.height),
(int((i + 1) * bin_w), self.hist_image.height - cv.Round(self.hist.bins[i])),
cv.ScalarAll(0), -1, 8, 0)
cv.ShowImage("histogram", self.hist_image)
if __name__ == "__main__":
# Load the source image.
if len(sys.argv) > 1:
src_image = cv.GetMat(cv.LoadImage(sys.argv[1], 0))
else:
url = 'http://code.opencv.org/projects/opencv/repository/revisions/master/raw/samples/c/baboon.jpg'
filedata = urllib2.urlopen(url).read()
imagefiledata = cv.CreateMatHeader(1, len(filedata), cv.CV_8UC1)
cv.SetData(imagefiledata, filedata, len(filedata))
src_image = cv.DecodeImageM(imagefiledata, 0)
dh = DemHist(src_image)
cv.WaitKey(0)
cv.DestroyAllWindows()
samples/python/dft.py 已删除 100755 → 0
浏览文件 @ b2ba8b99
#!/usr/bin/python
import cv2.cv as cv
import sys
import urllib2
# Rearrange the quadrants of Fourier image so that the origin is at
# the image center
# src & dst arrays of equal size & type
def cvShiftDFT(src_arr, dst_arr ):
size = cv.GetSize(src_arr)
dst_size = cv.GetSize(dst_arr)
if dst_size != size:
cv.Error( cv.CV_StsUnmatchedSizes, "cv.ShiftDFT", "Source and Destination arrays must have equal sizes", __FILE__, __LINE__ )
if(src_arr is dst_arr):
tmp = cv.CreateMat(size[1]/2, size[0]/2, cv.GetElemType(src_arr))
cx = size[0] / 2
cy = size[1] / 2 # image center
q1 = cv.GetSubRect( src_arr, (0,0,cx, cy) )
q2 = cv.GetSubRect( src_arr, (cx,0,cx,cy) )
q3 = cv.GetSubRect( src_arr, (cx,cy,cx,cy) )
q4 = cv.GetSubRect( src_arr, (0,cy,cx,cy) )
d1 = cv.GetSubRect( src_arr, (0,0,cx,cy) )
d2 = cv.GetSubRect( src_arr, (cx,0,cx,cy) )
d3 = cv.GetSubRect( src_arr, (cx,cy,cx,cy) )
d4 = cv.GetSubRect( src_arr, (0,cy,cx,cy) )
if(src_arr is not dst_arr):
if( not cv.CV_ARE_TYPES_EQ( q1, d1 )):
cv.Error( cv.CV_StsUnmatchedFormats, "cv.ShiftDFT", "Source and Destination arrays must have the same format", __FILE__, __LINE__ )
cv.Copy(q3, d1)
cv.Copy(q4, d2)
cv.Copy(q1, d3)
cv.Copy(q2, d4)
else:
cv.Copy(q3, tmp)
cv.Copy(q1, q3)
cv.Copy(tmp, q1)
cv.Copy(q4, tmp)
cv.Copy(q2, q4)
cv.Copy(tmp, q2)
if __name__ == "__main__":
if len(sys.argv) > 1:
im = cv.LoadImage( sys.argv[1], cv.CV_LOAD_IMAGE_GRAYSCALE)
else:
url = 'http://code.opencv.org/projects/opencv/repository/revisions/master/raw/samples/c/baboon.jpg'
filedata = urllib2.urlopen(url).read()
imagefiledata = cv.CreateMatHeader(1, len(filedata), cv.CV_8UC1)
cv.SetData(imagefiledata, filedata, len(filedata))
im = cv.DecodeImageM(imagefiledata, cv.CV_LOAD_IMAGE_GRAYSCALE)
realInput = cv.CreateImage( cv.GetSize(im), cv.IPL_DEPTH_64F, 1)
imaginaryInput = cv.CreateImage( cv.GetSize(im), cv.IPL_DEPTH_64F, 1)
complexInput = cv.CreateImage( cv.GetSize(im), cv.IPL_DEPTH_64F, 2)
cv.Scale(im, realInput, 1.0, 0.0)
cv.Zero(imaginaryInput)
cv.Merge(realInput, imaginaryInput, None, None, complexInput)
dft_M = cv.GetOptimalDFTSize( im.height - 1 )
dft_N = cv.GetOptimalDFTSize( im.width - 1 )
dft_A = cv.CreateMat( dft_M, dft_N, cv.CV_64FC2 )
image_Re = cv.CreateImage( (dft_N, dft_M), cv.IPL_DEPTH_64F, 1)
image_Im = cv.CreateImage( (dft_N, dft_M), cv.IPL_DEPTH_64F, 1)
# copy A to dft_A and pad dft_A with zeros
tmp = cv.GetSubRect( dft_A, (0,0, im.width, im.height))
cv.Copy( complexInput, tmp, None )
if(dft_A.width > im.width):
tmp = cv.GetSubRect( dft_A, (im.width,0, dft_N - im.width, im.height))
cv.Zero( tmp )
# no need to pad bottom part of dft_A with zeros because of
# use nonzero_rows parameter in cv.FT() call below
cv.DFT( dft_A, dft_A, cv.CV_DXT_FORWARD, complexInput.height )
cv.NamedWindow("win", 0)
cv.NamedWindow("magnitude", 0)
cv.ShowImage("win", im)
# Split Fourier in real and imaginary parts
cv.Split( dft_A, image_Re, image_Im, None, None )
# Compute the magnitude of the spectrum Mag = sqrt(Re^2 + Im^2)
cv.Pow( image_Re, image_Re, 2.0)
cv.Pow( image_Im, image_Im, 2.0)
cv.Add( image_Re, image_Im, image_Re, None)
cv.Pow( image_Re, image_Re, 0.5 )
# Compute log(1 + Mag)
cv.AddS( image_Re, cv.ScalarAll(1.0), image_Re, None ) # 1 + Mag
cv.Log( image_Re, image_Re ) # log(1 + Mag)
# Rearrange the quadrants of Fourier image so that the origin is at
# the image center
cvShiftDFT( image_Re, image_Re )
min, max, pt1, pt2 = cv.MinMaxLoc(image_Re)
cv.Scale(image_Re, image_Re, 1.0/(max-min), 1.0*(-min)/(max-min))
cv.ShowImage("magnitude", image_Re)
cv.WaitKey(0)
cv.DestroyAllWindows()
samples/python/distrans.py 已删除 100755 → 0
浏览文件 @ b2ba8b99
#!/usr/bin/python
import sys
import cv2.cv as cv
import urllib2
wndname = "Distance transform"
tbarname = "Threshold"
# The output images
dist = 0
dist8u1 = 0
dist8u2 = 0
dist8u = 0
dist32s = 0
gray = 0
edge = 0
# define a trackbar callback
def on_trackbar(edge_thresh):
cv.Threshold(gray, edge, float(edge_thresh), float(edge_thresh), cv.CV_THRESH_BINARY)
#Distance transform
cv.DistTransform(edge, dist, cv.CV_DIST_L2, cv.CV_DIST_MASK_5)
cv.ConvertScale(dist, dist, 5000.0, 0)
cv.Pow(dist, dist, 0.5)
cv.ConvertScale(dist, dist32s, 1.0, 0.5)
cv.AndS(dist32s, cv.ScalarAll(255), dist32s, None)
cv.ConvertScale(dist32s, dist8u1, 1, 0)
cv.ConvertScale(dist32s, dist32s, -1, 0)
cv.AddS(dist32s, cv.ScalarAll(255), dist32s, None)
cv.ConvertScale(dist32s, dist8u2, 1, 0)
cv.Merge(dist8u1, dist8u2, dist8u2, None, dist8u)
cv.ShowImage(wndname, dist8u)
if __name__ == "__main__":
edge_thresh = 100
if len(sys.argv) > 1:
gray = cv.LoadImage(sys.argv[1], cv.CV_LOAD_IMAGE_GRAYSCALE)
else:
url = 'http://code.opencv.org/projects/opencv/repository/revisions/master/raw/samples/c/stuff.jpg'
filedata = urllib2.urlopen(url).read()
imagefiledata = cv.CreateMatHeader(1, len(filedata), cv.CV_8UC1)
cv.SetData(imagefiledata, filedata, len(filedata))
gray = cv.DecodeImage(imagefiledata, cv.CV_LOAD_IMAGE_GRAYSCALE)
# Create the output image
dist = cv.CreateImage((gray.width, gray.height), cv.IPL_DEPTH_32F, 1)
dist8u1 = cv.CloneImage(gray)
dist8u2 = cv.CloneImage(gray)
dist8u = cv.CreateImage((gray.width, gray.height), cv.IPL_DEPTH_8U, 3)
dist32s = cv.CreateImage((gray.width, gray.height), cv.IPL_DEPTH_32S, 1)
# Convert to grayscale
edge = cv.CloneImage(gray)
# Create a window
cv.NamedWindow(wndname, 1)
# create a toolbar
cv.CreateTrackbar(tbarname, wndname, edge_thresh, 255, on_trackbar)
# Show the image
on_trackbar(edge_thresh)
# Wait for a key stroke; the same function arranges events processing
cv.WaitKey(0)
cv.DestroyAllWindows()
samples/python/dmtx.py 已删除 100755 → 0
浏览文件 @ b2ba8b99
#!/usr/bin/python
import cv2.cv as cv
import time
from pydmtx import DataMatrix
import numpy
import sys
import math
'''
Find 2 D barcode based on up to 3 channel datamatrix
'''
def absnorm8(im, im8):
""" im may be any single-channel image type. Return an 8-bit version, absolute value, normalized so that max is 255 """
(minVal, maxVal, _, _) = cv.MinMaxLoc(im)
cv.ConvertScaleAbs(im, im8, 255 / max(abs(minVal), abs(maxVal)), 0)
return im8
font = cv.InitFont(cv.CV_FONT_HERSHEY_SIMPLEX, 1.0, 1.0, thickness = 2, lineType = cv.CV_AA)
if 0:
started = time.time()
print dm_write.decode(bg.width, bg.height, buffer(bg.tostring()), max_count = 1, min_edge = 12, max_edge = 13, shape = DataMatrix.DmtxSymbol10x10) # , timeout = 10)
print "took", time.time() - started
class DmtxFinder:
def __init__(self):
self.cache = {}
self.dm = DataMatrix()
def Cached(self, name, rows, cols, type):
key = (name, rows, cols)
if not key in self.cache:
self.cache[key] = cv.CreateMat(rows, cols, type)
return self.cache[key]
def find0(self, img):
started = time.time()
self.dm.decode(img.width,
img.height,
buffer(img.tostring()),
max_count = 4,
#min_edge = 6,
#max_edge = 19 # Units of 2 pixels
)
print "brute", time.time() - started
found = {}
for i in range(self.dm.count()):
stats = dm_read.stats(i + 1)
print stats
found[stats[0]] = stats[1]
return found
def find(self, img):
started = time.time()
gray = self.Cached('gray', img.height, img.width, cv.CV_8UC1)
cv.CvtColor(img, gray, cv.CV_BGR2GRAY)
sobel = self.Cached('sobel', img.height, img.width, cv.CV_16SC1)
sobely = self.Cached('sobely', img.height, img.width, cv.CV_16SC1)
cv.Sobel(gray, sobel, 1, 0)
cv.Sobel(gray, sobely, 0, 1)
cv.Add(sobel, sobely, sobel)
sobel8 = self.Cached('sobel8', sobel.height, sobel.width, cv.CV_8UC1)
absnorm8(sobel, sobel8)
cv.Threshold(sobel8, sobel8, 128.0, 255.0, cv.CV_THRESH_BINARY)
sobel_integral = self.Cached('sobel_integral', img.height + 1, img.width + 1, cv.CV_32SC1)
cv.Integral(sobel8, sobel_integral)
d = 16
_x1y1 = cv.GetSubRect(sobel_integral, (0, 0, sobel_integral.cols - d, sobel_integral.rows - d))
_x1y2 = cv.GetSubRect(sobel_integral, (0, d, sobel_integral.cols - d, sobel_integral.rows - d))
_x2y1 = cv.GetSubRect(sobel_integral, (d, 0, sobel_integral.cols - d, sobel_integral.rows - d))
_x2y2 = cv.GetSubRect(sobel_integral, (d, d, sobel_integral.cols - d, sobel_integral.rows - d))
summation = cv.CloneMat(_x2y2)
cv.Sub(summation, _x1y2, summation)
cv.Sub(summation, _x2y1, summation)
cv.Add(summation, _x1y1, summation)
sum8 = self.Cached('sum8', summation.height, summation.width, cv.CV_8UC1)
absnorm8(summation, sum8)
cv.Threshold(sum8, sum8, 32.0, 255.0, cv.CV_THRESH_BINARY)
cv.ShowImage("sum8", sum8)
seq = cv.FindContours(sum8, cv.CreateMemStorage(), cv.CV_RETR_EXTERNAL)
subimg = cv.GetSubRect(img, (d / 2, d / 2, sum8.cols, sum8.rows))
t_cull = time.time() - started
seqs = []
while seq:
seqs.append(seq)
seq = seq.h_next()
started = time.time()
found = {}
print 'seqs', len(seqs)
for seq in seqs:
area = cv.ContourArea(seq)
if area > 1000:
rect = cv.BoundingRect(seq)
edge = int((14 / 14.) * math.sqrt(area) / 2 + 0.5)
candidate = cv.GetSubRect(subimg, rect)
sym = self.dm.decode(candidate.width,
candidate.height,
buffer(candidate.tostring()),
max_count = 1,
#min_edge = 6,
#max_edge = int(edge) # Units of 2 pixels
)
if sym:
onscreen = [(d / 2 + rect[0] + x, d / 2 + rect[1] + y) for (x, y) in self.dm.stats(1)[1]]
found[sym] = onscreen
else:
print "FAILED"
t_brute = time.time() - started
print "cull took", t_cull, "brute", t_brute
return found
bg = cv.CreateMat(1024, 1024, cv.CV_8UC3)
cv.Set(bg, cv.RGB(0, 0, 0))
df = DmtxFinder()
cv.NamedWindow("camera", 1)
def mkdmtx(msg):
dm_write = DataMatrix()
dm_write.encode(msg)
pi = dm_write.image # .resize((14, 14))
cv_im = cv.CreateImageHeader(pi.size, cv.IPL_DEPTH_8U, 3)
cv.SetData(cv_im, pi.tostring())
return cv_im
# test = [('WIL', (100,100))]: # , ('LOW', (250,100)), ('GAR', (300, 300)), ('AGE', (500, 300))]:
test = []
y = 10
for j in range(7):
r = 28 + j * 4
mr = r * math.sqrt(2)
y += mr * 1.8
test += [(str(deg) + "abcdefgh"[j], (50 + deg * 11, y), math.pi * deg / 180, r) for deg in range(0, 90, 10)]
for (msg, (x, y), angle, r) in test:
map = cv.CreateMat(2, 3, cv.CV_32FC1)
corners = [(x + r * math.cos(angle + th), y + r * math.sin(angle + th)) for th in [0, math.pi / 2, math.pi, 3 * math.pi / 4]]
src = mkdmtx(msg)
(sx, sy) = cv.GetSize(src)
cv.GetAffineTransform([(0,0), (sx, 0), (sx, sy)], corners[:3], map)
temp = cv.CreateMat(bg.rows, bg.cols, cv.CV_8UC3)
cv.Set(temp, cv.RGB(0, 0, 0))
cv.WarpAffine(src, temp, map)
cv.Or(temp, bg, bg)
cv.ShowImage("comp", bg)
scribble = cv.CloneMat(bg)
if 0:
for i in range(10):
df.find(bg)
for (sym, coords) in df.find(bg).items():
print sym
cv.PolyLine(scribble, [coords], 1, cv.CV_RGB(255, 0,0), 1, lineType = cv.CV_AA)
Xs = [x for (x, y) in coords]
Ys = [y for (x, y) in coords]
where = ((min(Xs) + max(Xs)) / 2, max(Ys) - 50)
cv.PutText(scribble, sym, where, font, cv.RGB(0,255, 0))
cv.ShowImage("results", scribble)
cv.WaitKey()
cv.DestroyAllWindows()
sys.exit(0)
capture = cv.CaptureFromCAM(0)
while True:
img = cv.QueryFrame(capture)
cv.ShowImage("capture", img)
print df.find(img)
cv.WaitKey(6)
samples/python/drawing.py 已删除 100755 → 0
浏览文件 @ b2ba8b99
#! /usr/bin/env python
from random import Random
import colorsys
print "OpenCV Python version of drawing"
import cv2.cv as cv
def random_color(random):
"""
Return a random color
"""
icolor = random.randint(0, 0xFFFFFF)
return cv.Scalar(icolor & 0xff, (icolor >> 8) & 0xff, (icolor >> 16) & 0xff)
if __name__ == '__main__':
# some "constants"
width = 1000
height = 700
window_name = "Drawing Demo"
number = 100
delay = 5
line_type = cv.CV_AA # change it to 8 to see non-antialiased graphics
# create the source image
image = cv.CreateImage( (width, height), 8, 3)
# create window and display the original picture in it
cv.NamedWindow(window_name, 1)
cv.SetZero(image)
cv.ShowImage(window_name, image)
# create the random number
random = Random()
# draw some lines
for i in range(number):
pt1 = (random.randrange(-width, 2 * width),
random.randrange(-height, 2 * height))
pt2 = (random.randrange(-width, 2 * width),
random.randrange(-height, 2 * height))
cv.Line(image, pt1, pt2,
random_color(random),
random.randrange(0, 10),
line_type, 0)
cv.ShowImage(window_name, image)
cv.WaitKey(delay)
# draw some rectangles
for i in range(number):
pt1 = (random.randrange(-width, 2 * width),
random.randrange(-height, 2 * height))
pt2 = (random.randrange(-width, 2 * width),
random.randrange(-height, 2 * height))
cv.Rectangle(image, pt1, pt2,
random_color(random),
random.randrange(-1, 9),
line_type, 0)
cv.ShowImage(window_name, image)
cv.WaitKey(delay)
# draw some ellipes
for i in range(number):
pt1 = (random.randrange(-width, 2 * width),
random.randrange(-height, 2 * height))
sz = (random.randrange(0, 200),
random.randrange(0, 200))
angle = random.randrange(0, 1000) * 0.180
cv.Ellipse(image, pt1, sz, angle, angle - 100, angle + 200,
random_color(random),
random.randrange(-1, 9),
line_type, 0)
cv.ShowImage(window_name, image)
cv.WaitKey(delay)
# init the list of polylines
nb_polylines = 2
polylines_size = 3
pt = [0,] * nb_polylines
for a in range(nb_polylines):
pt [a] = [0,] * polylines_size
# draw some polylines
for i in range(number):
for a in range(nb_polylines):
for b in range(polylines_size):
pt [a][b] = (random.randrange(-width, 2 * width),
random.randrange(-height, 2 * height))
cv.PolyLine(image, pt, 1,
random_color(random),
random.randrange(1, 9),
line_type, 0)
cv.ShowImage(window_name, image)
cv.WaitKey(delay)
# draw some filled polylines
for i in range(number):
for a in range(nb_polylines):
for b in range(polylines_size):
pt [a][b] = (random.randrange(-width, 2 * width),
random.randrange(-height, 2 * height))
cv.FillPoly(image, pt,
random_color(random),
line_type, 0)
cv.ShowImage(window_name, image)
cv.WaitKey(delay)
# draw some circles
for i in range(number):
pt1 = (random.randrange(-width, 2 * width),
random.randrange(-height, 2 * height))
cv.Circle(image, pt1, random.randrange(0, 300),
random_color(random),
random.randrange(-1, 9),
line_type, 0)
cv.ShowImage(window_name, image)
cv.WaitKey(delay)
# draw some text
for i in range(number):
pt1 = (random.randrange(-width, 2 * width),
random.randrange(-height, 2 * height))
font = cv.InitFont(random.randrange(0, 8),
random.randrange(0, 100) * 0.05 + 0.01,
random.randrange(0, 100) * 0.05 + 0.01,
random.randrange(0, 5) * 0.1,
random.randrange(0, 10),
line_type)
cv.PutText(image, "Testing text rendering!",
pt1, font,
random_color(random))
cv.ShowImage(window_name, image)
cv.WaitKey(delay)
# prepare a text, and get it's properties
font = cv.InitFont(cv.CV_FONT_HERSHEY_COMPLEX,
3, 3, 0.0, 5, line_type)
text_size, ymin = cv.GetTextSize("OpenCV forever!", font)
pt1 = ((width - text_size[0]) / 2, (height + text_size[1]) / 2)
image2 = cv.CloneImage(image)
# now, draw some OpenCV pub ;-)
for i in range(0, 512, 2):
cv.SubS(image2, cv.ScalarAll(i), image)
(r, g, b) = colorsys.hsv_to_rgb((i % 100) / 100., 1, 1)
cv.PutText(image, "OpenCV forever!",
pt1, font, cv.RGB(255 * r, 255 * g, 255 * b))
cv.ShowImage(window_name, image)
cv.WaitKey(delay)
# wait some key to end
cv.WaitKey(0)
cv.DestroyAllWindows()
samples/python/edge.py 已删除 100755 → 0
浏览文件 @ b2ba8b99
#! /usr/bin/env python
print "OpenCV Python version of edge"
import sys
import urllib2
import cv2.cv as cv
# some definitions
win_name = "Edge"
trackbar_name = "Threshold"
# the callback on the trackbar
def on_trackbar(position):
cv.Smooth(gray, edge, cv.CV_BLUR, 3, 3, 0)
cv.Not(gray, edge)
# run the edge dector on gray scale
cv.Canny(gray, edge, position, position * 3, 3)
# reset
cv.SetZero(col_edge)
# copy edge points
cv.Copy(im, col_edge, edge)
# show the im
cv.ShowImage(win_name, col_edge)
if __name__ == '__main__':
if len(sys.argv) > 1:
im = cv.LoadImage( sys.argv[1], cv.CV_LOAD_IMAGE_COLOR)
else:
url = 'http://code.opencv.org/projects/opencv/repository/revisions/master/raw/samples/c/fruits.jpg'
filedata = urllib2.urlopen(url).read()
imagefiledata = cv.CreateMatHeader(1, len(filedata), cv.CV_8UC1)
cv.SetData(imagefiledata, filedata, len(filedata))
im = cv.DecodeImage(imagefiledata, cv.CV_LOAD_IMAGE_COLOR)
# create the output im
col_edge = cv.CreateImage((im.width, im.height), 8, 3)
# convert to grayscale
gray = cv.CreateImage((im.width, im.height), 8, 1)
edge = cv.CreateImage((im.width, im.height), 8, 1)
cv.CvtColor(im, gray, cv.CV_BGR2GRAY)
# create the window
cv.NamedWindow(win_name, cv.CV_WINDOW_AUTOSIZE)
# create the trackbar
cv.CreateTrackbar(trackbar_name, win_name, 1, 100, on_trackbar)
# show the im
on_trackbar(0)
# wait a key pressed to end
cv.WaitKey(0)
cv.DestroyAllWindows()
samples/python/facedetect.py 已删除 100755 → 0
浏览文件 @ b2ba8b99
#!/usr/bin/python
"""
This program is demonstration for face and object detection using haar-like features.
The program finds faces in a camera image or video stream and displays a red box around them.
Original C implementation by: ?
Python implementation by: Roman Stanchak, James Bowman
"""
import sys
import cv2.cv as cv
from optparse import OptionParser
# Parameters for haar detection
# From the API:
# The default parameters (scale_factor=2, min_neighbors=3, flags=0) are tuned
# for accurate yet slow object detection. For a faster operation on real video
# images the settings are:
# scale_factor=1.2, min_neighbors=2, flags=CV_HAAR_DO_CANNY_PRUNING,
# min_size=<minimum possible face size
min_size = (20, 20)
image_scale = 2
haar_scale = 1.2
min_neighbors = 2
haar_flags = 0
def detect_and_draw(img, cascade):
# allocate temporary images
gray = cv.CreateImage((img.width,img.height), 8, 1)
small_img = cv.CreateImage((cv.Round(img.width / image_scale),
cv.Round (img.height / image_scale)), 8, 1)
# convert color input image to grayscale
cv.CvtColor(img, gray, cv.CV_BGR2GRAY)
# scale input image for faster processing
cv.Resize(gray, small_img, cv.CV_INTER_LINEAR)
cv.EqualizeHist(small_img, small_img)
if(cascade):
t = cv.GetTickCount()
faces = cv.HaarDetectObjects(small_img, cascade, cv.CreateMemStorage(0),
haar_scale, min_neighbors, haar_flags, min_size)
t = cv.GetTickCount() - t
print "detection time = %gms" % (t/(cv.GetTickFrequency()*1000.))
if faces:
for ((x, y, w, h), n) in faces:
# the input to cv.HaarDetectObjects was resized, so scale the
# bounding box of each face and convert it to two CvPoints
pt1 = (int(x * image_scale), int(y * image_scale))
pt2 = (int((x + w) * image_scale), int((y + h) * image_scale))
cv.Rectangle(img, pt1, pt2, cv.RGB(255, 0, 0), 3, 8, 0)
cv.ShowImage("result", img)
if __name__ == '__main__':
parser = OptionParser(usage = "usage: %prog [options] [filename|camera_index]")
parser.add_option("-c", "--cascade", action="store", dest="cascade", type="str", help="Haar cascade file, default %default", default = "../data/haarcascades/haarcascade_frontalface_alt.xml")
(options, args) = parser.parse_args()
cascade = cv.Load(options.cascade)
if len(args) != 1:
parser.print_help()
sys.exit(1)
input_name = args[0]
if input_name.isdigit():
capture = cv.CreateCameraCapture(int(input_name))
else:
capture = None
cv.NamedWindow("result", 1)
if capture:
frame_copy = None
while True:
frame = cv.QueryFrame(capture)
if not frame:
cv.WaitKey(0)
break
if not frame_copy:
frame_copy = cv.CreateImage((frame.width,frame.height),
cv.IPL_DEPTH_8U, frame.nChannels)
if frame.origin == cv.IPL_ORIGIN_TL:
cv.Copy(frame, frame_copy)
else:
cv.Flip(frame, frame_copy, 0)
detect_and_draw(frame_copy, cascade)
if cv.WaitKey(10) >= 0:
break
else:
image = cv.LoadImage(input_name, 1)
detect_and_draw(image, cascade)
cv.WaitKey(0)
cv.DestroyWindow("result")
samples/python/fback.py 已删除 100755 → 0
浏览文件 @ b2ba8b99
#!/usr/bin/env python
from cv import *
class FBackDemo:
def __init__(self):
self.capture = CaptureFromCAM(0)
self.mv_step = 16
self.mv_scale = 1.5
self.mv_color = (0, 255, 0)
self.cflow = None
self.flow = None
NamedWindow( "Optical Flow", 1 )
print( "Press ESC - quit the program\n" )
def draw_flow(self, flow, prevgray):
""" Returns a nice representation of a hue histogram """
CvtColor(prevgray, self.cflow, CV_GRAY2BGR)
for y in range(0, flow.height, self.mv_step):
for x in range(0, flow.width, self.mv_step):
fx, fy = flow[y, x]
Line(self.cflow, (x,y), (x+fx,y+fy), self.mv_color)
Circle(self.cflow, (x,y), 2, self.mv_color, -1)
ShowImage("Optical Flow", self.cflow)
def run(self):
first_frame = True
while True:
frame = QueryFrame( self.capture )
if first_frame:
gray = CreateImage(GetSize(frame), 8, 1)
prev_gray = CreateImage(GetSize(frame), 8, 1)
flow = CreateImage(GetSize(frame), 32, 2)
self.cflow = CreateImage(GetSize(frame), 8, 3)
CvtColor(frame, gray, CV_BGR2GRAY)
if not first_frame:
CalcOpticalFlowFarneback(prev_gray, gray, flow,
pyr_scale=0.5, levels=3, winsize=15,
iterations=3, poly_n=5, poly_sigma=1.2, flags=0)
self.draw_flow(flow, prev_gray)
c = WaitKey(7)
if c in [27, ord('q'), ord('Q')]:
break
prev_gray, gray = gray, prev_gray
first_frame = False
if __name__=="__main__":
demo = FBackDemo()
demo.run()
cv.DestroyAllWindows()
samples/python/ffilldemo.py 已删除 100755 → 0
浏览文件 @ b2ba8b99
#!/usr/bin/python
import sys
import random
import urllib2
import cv2.cv as cv
im=None;
mask=None;
color_img=None;
gray_img0 = None;
gray_img = None;
ffill_case = 1;
lo_diff = 20
up_diff = 20;
connectivity = 4;
is_color = 1;
is_mask = 0;
new_mask_val = 255;
def update_lo( pos ):
lo_diff = pos
def update_up( pos ):
up_diff = pos
def on_mouse( event, x, y, flags, param ):
if( not color_img ):
return;
if event == cv.CV_EVENT_LBUTTONDOWN:
my_mask = None
seed = (x,y);
if ffill_case==0:
lo = up = 0
flags = connectivity + (new_mask_val << 8)
else:
lo = lo_diff;
up = up_diff;
flags = connectivity + (new_mask_val << 8) + cv.CV_FLOODFILL_FIXED_RANGE
b = random.randint(0,255)
g = random.randint(0,255)
r = random.randint(0,255)
if( is_mask ):
my_mask = mask
cv.Threshold( mask, mask, 1, 128, cv.CV_THRESH_BINARY );
if( is_color ):
color = cv.CV_RGB( r, g, b );
comp = cv.FloodFill( color_img, seed, color, cv.CV_RGB( lo, lo, lo ),
cv.CV_RGB( up, up, up ), flags, my_mask );
cv.ShowImage( "image", color_img );
else:
brightness = cv.RealScalar((r*2 + g*7 + b + 5)/10);
comp = cv.FloodFill( gray_img, seed, brightness, cv.RealScalar(lo),
cv.RealScalar(up), flags, my_mask );
cv.ShowImage( "image", gray_img );
print "%g pixels were repainted" % comp[0]
if( is_mask ):
cv.ShowImage( "mask", mask );
if __name__ == "__main__":
if len(sys.argv) > 1:
im = cv.LoadImage( sys.argv[1], cv.CV_LOAD_IMAGE_COLOR)
else:
url = 'http://code.opencv.org/projects/opencv/repository/revisions/master/raw/samples/c/fruits.jpg'
filedata = urllib2.urlopen(url).read()
imagefiledata = cv.CreateMatHeader(1, len(filedata), cv.CV_8UC1)
cv.SetData(imagefiledata, filedata, len(filedata))
im = cv.DecodeImage(imagefiledata, cv.CV_LOAD_IMAGE_COLOR)
print "Hot keys:"
print "\tESC - quit the program"
print "\tc - switch color/grayscale mode"
print "\tm - switch mask mode"
print "\tr - restore the original image"
print "\ts - use null-range floodfill"
print "\tf - use gradient floodfill with fixed(absolute) range"
print "\tg - use gradient floodfill with floating(relative) range"
print "\t4 - use 4-connectivity mode"
print "\t8 - use 8-connectivity mode"
color_img = cv.CloneImage( im );
gray_img0 = cv.CreateImage( (color_img.width, color_img.height), 8, 1 );
cv.CvtColor( color_img, gray_img0, cv.CV_BGR2GRAY );
gray_img = cv.CloneImage( gray_img0 );
mask = cv.CreateImage( (color_img.width + 2, color_img.height + 2), 8, 1 );
cv.NamedWindow( "image", 1 );
cv.CreateTrackbar( "lo_diff", "image", lo_diff, 255, update_lo);
cv.CreateTrackbar( "up_diff", "image", up_diff, 255, update_up);
cv.SetMouseCallback( "image", on_mouse );
while True:
if( is_color ):
cv.ShowImage( "image", color_img );
else:
cv.ShowImage( "image", gray_img );
c = cv.WaitKey(0) % 0x100
if c == 27:
print("Exiting ...");
sys.exit(0)
elif c == ord('c'):
if( is_color ):
print("Grayscale mode is set");
cv.CvtColor( color_img, gray_img, cv.CV_BGR2GRAY );
is_color = 0;
else:
print("Color mode is set");
cv.Copy( im, color_img, None );
cv.Zero( mask );
is_color = 1;
elif c == ord('m'):
if( is_mask ):
cv.DestroyWindow( "mask" );
is_mask = 0;
else:
cv.NamedWindow( "mask", 0 );
cv.Zero( mask );
cv.ShowImage( "mask", mask );
is_mask = 1;
elif c == ord('r'):
print("Original image is restored");
cv.Copy( im, color_img, None );
cv.Copy( gray_img0, gray_img, None );
cv.Zero( mask );
elif c == ord('s'):
print("Simple floodfill mode is set");
ffill_case = 0;
elif c == ord('f'):
print("Fixed Range floodfill mode is set");
ffill_case = 1;
elif c == ord('g'):
print("Gradient (floating range) floodfill mode is set");
ffill_case = 2;
elif c == ord('4'):
print("4-connectivity mode is set");
connectivity = 4;
elif c == ord('8'):
print("8-connectivity mode is set");
connectivity = 8;
cv.DestroyAllWindows()
samples/python/fitellipse.py 已删除 100755 → 0
浏览文件 @ b2ba8b99
#!/usr/bin/python
"""
This program is a demonstration of ellipse fitting.
Trackbar controls threshold parameter.
Gray lines are contours. Colored lines are fit ellipses.
Original C implementation by: Denis Burenkov.
Python implementation by: Roman Stanchak, James Bowman
"""
import sys
import urllib2
import random
import cv2.cv as cv
def contour_iterator(contour):
while contour:
yield contour
contour = contour.h_next()
class FitEllipse:
def __init__(self, source_image, slider_pos):
self.source_image = source_image
cv.CreateTrackbar("Threshold", "Result", slider_pos, 255, self.process_image)
self.process_image(slider_pos)
def process_image(self, slider_pos):
"""
This function finds contours, draws them and their approximation by ellipses.
"""
stor = cv.CreateMemStorage()
# Create the destination images
image02 = cv.CloneImage(self.source_image)
cv.Zero(image02)
image04 = cv.CreateImage(cv.GetSize(self.source_image), cv.IPL_DEPTH_8U, 3)
cv.Zero(image04)
# Threshold the source image. This needful for cv.FindContours().
cv.Threshold(self.source_image, image02, slider_pos, 255, cv.CV_THRESH_BINARY)
# Find all contours.
cont = cv.FindContours(image02,
stor,
cv.CV_RETR_LIST,
cv.CV_CHAIN_APPROX_NONE,
(0, 0))
for c in contour_iterator(cont):
# Number of points must be more than or equal to 6 for cv.FitEllipse2
if len(c) >= 6:
# Copy the contour into an array of (x,y)s
PointArray2D32f = cv.CreateMat(1, len(c), cv.CV_32FC2)
for (i, (x, y)) in enumerate(c):
PointArray2D32f[0, i] = (x, y)
# Draw the current contour in gray
gray = cv.CV_RGB(100, 100, 100)
cv.DrawContours(image04, c, gray, gray,0,1,8,(0,0))
# Fits ellipse to current contour.
(center, size, angle) = cv.FitEllipse2(PointArray2D32f)
# Convert ellipse data from float to integer representation.
center = (cv.Round(center[0]), cv.Round(center[1]))
size = (cv.Round(size[0] * 0.5), cv.Round(size[1] * 0.5))
# Draw ellipse in random color
color = cv.CV_RGB(random.randrange(256),random.randrange(256),random.randrange(256))
cv.Ellipse(image04, center, size,
angle, 0, 360,
color, 2, cv.CV_AA, 0)
# Show image. HighGUI use.
cv.ShowImage( "Result", image04 )
if __name__ == '__main__':
if len(sys.argv) > 1:
source_image = cv.LoadImage(sys.argv[1], cv.CV_LOAD_IMAGE_GRAYSCALE)
else:
url = 'http://code.opencv.org/projects/opencv/repository/revisions/master/raw/samples/c/stuff.jpg'
filedata = urllib2.urlopen(url).read()
imagefiledata = cv.CreateMatHeader(1, len(filedata), cv.CV_8UC1)
cv.SetData(imagefiledata, filedata, len(filedata))
source_image = cv.DecodeImage(imagefiledata, cv.CV_LOAD_IMAGE_GRAYSCALE)
# Create windows.
cv.NamedWindow("Source", 1)
cv.NamedWindow("Result", 1)
# Show the image.
cv.ShowImage("Source", source_image)
fe = FitEllipse(source_image, 70)
print "Press any key to exit"
cv.WaitKey(0)
cv.DestroyWindow("Source")
cv.DestroyWindow("Result")
samples/python/houghlines.py 已删除 100755 → 0
浏览文件 @ b2ba8b99
#!/usr/bin/python
# This is a standalone program. Pass an image name as a first parameter of the program.
import sys
from math import sin, cos, sqrt, pi
import cv2.cv as cv
import urllib2
# toggle between CV_HOUGH_STANDARD and CV_HOUGH_PROBILISTIC
USE_STANDARD = True
if __name__ == "__main__":
if len(sys.argv) > 1:
filename = sys.argv[1]
src = cv.LoadImage(filename, cv.CV_LOAD_IMAGE_GRAYSCALE)
else:
url = 'http://code.opencv.org/projects/opencv/repository/revisions/master/raw/doc/pics/building.jpg'
filedata = urllib2.urlopen(url).read()
imagefiledata = cv.CreateMatHeader(1, len(filedata), cv.CV_8UC1)
cv.SetData(imagefiledata, filedata, len(filedata))
src = cv.DecodeImageM(imagefiledata, cv.CV_LOAD_IMAGE_GRAYSCALE)
cv.NamedWindow("Source", 1)
cv.NamedWindow("Hough", 1)
while True:
dst = cv.CreateImage(cv.GetSize(src), 8, 1)
color_dst = cv.CreateImage(cv.GetSize(src), 8, 3)
storage = cv.CreateMemStorage(0)
lines = 0
cv.Canny(src, dst, 50, 200, 3)
cv.CvtColor(dst, color_dst, cv.CV_GRAY2BGR)
if USE_STANDARD:
lines = cv.HoughLines2(dst, storage, cv.CV_HOUGH_STANDARD, 1, pi / 180, 100, 0, 0)
for (rho, theta) in lines[:100]:
a = cos(theta)
b = sin(theta)
x0 = a * rho
y0 = b * rho
pt1 = (cv.Round(x0 + 1000*(-b)), cv.Round(y0 + 1000*(a)))
pt2 = (cv.Round(x0 - 1000*(-b)), cv.Round(y0 - 1000*(a)))
cv.Line(color_dst, pt1, pt2, cv.RGB(255, 0, 0), 3, 8)
else:
lines = cv.HoughLines2(dst, storage, cv.CV_HOUGH_PROBABILISTIC, 1, pi / 180, 50, 50, 10)
for line in lines:
cv.Line(color_dst, line[0], line[1], cv.CV_RGB(255, 0, 0), 3, 8)
cv.ShowImage("Source", src)
cv.ShowImage("Hough", color_dst)
k = cv.WaitKey(0) % 0x100
if k == ord(' '):
USE_STANDARD = not USE_STANDARD
if k == 27:
break
cv.DestroyAllWindows()
samples/python/inpaint.py 已删除 100755 → 0
浏览文件 @ b2ba8b99
#!/usr/bin/python
import urllib2
import sys
import cv2.cv as cv
class Sketcher:
def __init__(self, windowname, dests):
self.prev_pt = None
self.windowname = windowname
self.dests = dests
cv.SetMouseCallback(self.windowname, self.on_mouse)
def on_mouse(self, event, x, y, flags, param):
pt = (x, y)
if event == cv.CV_EVENT_LBUTTONUP or not (flags & cv.CV_EVENT_FLAG_LBUTTON):
self.prev_pt = None
elif event == cv.CV_EVENT_LBUTTONDOWN:
self.prev_pt = pt
elif event == cv.CV_EVENT_MOUSEMOVE and (flags & cv.CV_EVENT_FLAG_LBUTTON) :
if self.prev_pt:
for dst in self.dests:
cv.Line(dst, self.prev_pt, pt, cv.ScalarAll(255), 5, 8, 0)
self.prev_pt = pt
cv.ShowImage(self.windowname, img)
if __name__=="__main__":
if len(sys.argv) > 1:
img0 = cv.LoadImage( sys.argv[1], cv.CV_LOAD_IMAGE_COLOR)
else:
url = 'http://code.opencv.org/projects/opencv/repository/revisions/master/raw/samples/c/fruits.jpg'
filedata = urllib2.urlopen(url).read()
imagefiledata = cv.CreateMatHeader(1, len(filedata), cv.CV_8UC1)
cv.SetData(imagefiledata, filedata, len(filedata))
img0 = cv.DecodeImage(imagefiledata, cv.CV_LOAD_IMAGE_COLOR)
print "Hot keys:"
print "\tESC - quit the program"
print "\tr - restore the original image"
print "\ti or ENTER - run inpainting algorithm"
print "\t\t(before running it, paint something on the image)"
cv.NamedWindow("image", 1)
cv.NamedWindow("inpainted image", 1)
img = cv.CloneImage(img0)
inpainted = cv.CloneImage(img0)
inpaint_mask = cv.CreateImage(cv.GetSize(img), 8, 1)
cv.Zero(inpaint_mask)
cv.Zero(inpainted)
cv.ShowImage("image", img)
cv.ShowImage("inpainted image", inpainted)
sk = Sketcher("image", [img, inpaint_mask])
while True:
c = cv.WaitKey(0) % 0x100
if c == 27 or c == ord('q'):
break
if c == ord('r'):
cv.Zero(inpaint_mask)
cv.Copy(img0, img)
cv.ShowImage("image", img)
if c == ord('i') or c == ord('\n'):
cv.Inpaint(img, inpaint_mask, inpainted, 3, cv.CV_INPAINT_TELEA)
cv.ShowImage("inpainted image", inpainted)
cv.DestroyAllWindows()
samples/python/kalman.py 已删除 100755 → 0
浏览文件 @ b2ba8b99
#!/usr/bin/python
"""
Tracking of rotating point.
Rotation speed is constant.
Both state and measurements vectors are 1D (a point angle),
Measurement is the real point angle + gaussian noise.
The real and the estimated points are connected with yellow line segment,
the real and the measured points are connected with red line segment.
(if Kalman filter works correctly,
the yellow segment should be shorter than the red one).
Pressing any key (except ESC) will reset the tracking with a different speed.
Pressing ESC will stop the program.
"""
import urllib2
import cv2.cv as cv
from math import cos, sin, sqrt
import sys
if __name__ == "__main__":
A = [ [1, 1], [0, 1] ]
img = cv.CreateImage((500, 500), 8, 3)
kalman = cv.CreateKalman(2, 1, 0)
state = cv.CreateMat(2, 1, cv.CV_32FC1) # (phi, delta_phi)
process_noise = cv.CreateMat(2, 1, cv.CV_32FC1)
measurement = cv.CreateMat(1, 1, cv.CV_32FC1)
rng = cv.RNG(-1)
code = -1L
cv.Zero(measurement)
cv.NamedWindow("Kalman", 1)
while True:
cv.RandArr(rng, state, cv.CV_RAND_NORMAL, cv.RealScalar(0), cv.RealScalar(0.1))
kalman.transition_matrix[0,0] = 1
kalman.transition_matrix[0,1] = 1
kalman.transition_matrix[1,0] = 0
kalman.transition_matrix[1,1] = 1
cv.SetIdentity(kalman.measurement_matrix, cv.RealScalar(1))
cv.SetIdentity(kalman.process_noise_cov, cv.RealScalar(1e-5))
cv.SetIdentity(kalman.measurement_noise_cov, cv.RealScalar(1e-1))
cv.SetIdentity(kalman.error_cov_post, cv.RealScalar(1))
cv.RandArr(rng, kalman.state_post, cv.CV_RAND_NORMAL, cv.RealScalar(0), cv.RealScalar(0.1))
while True:
def calc_point(angle):
return (cv.Round(img.width/2 + img.width/3*cos(angle)),
cv.Round(img.height/2 - img.width/3*sin(angle)))
state_angle = state[0,0]
state_pt = calc_point(state_angle)
prediction = cv.KalmanPredict(kalman)
predict_angle = prediction[0, 0]
predict_pt = calc_point(predict_angle)
cv.RandArr(rng, measurement, cv.CV_RAND_NORMAL, cv.RealScalar(0),
cv.RealScalar(sqrt(kalman.measurement_noise_cov[0, 0])))
# generate measurement
cv.MatMulAdd(kalman.measurement_matrix, state, measurement, measurement)
measurement_angle = measurement[0, 0]
measurement_pt = calc_point(measurement_angle)
# plot points
def draw_cross(center, color, d):
cv.Line(img, (center[0] - d, center[1] - d),
(center[0] + d, center[1] + d), color, 1, cv.CV_AA, 0)
cv.Line(img, (center[0] + d, center[1] - d),
(center[0] - d, center[1] + d), color, 1, cv.CV_AA, 0)
cv.Zero(img)
draw_cross(state_pt, cv.CV_RGB(255, 255, 255), 3)
draw_cross(measurement_pt, cv.CV_RGB(255, 0,0), 3)
draw_cross(predict_pt, cv.CV_RGB(0, 255, 0), 3)
cv.Line(img, state_pt, measurement_pt, cv.CV_RGB(255, 0,0), 3, cv. CV_AA, 0)
cv.Line(img, state_pt, predict_pt, cv.CV_RGB(255, 255, 0), 3, cv. CV_AA, 0)
cv.KalmanCorrect(kalman, measurement)
cv.RandArr(rng, process_noise, cv.CV_RAND_NORMAL, cv.RealScalar(0),
cv.RealScalar(sqrt(kalman.process_noise_cov[0, 0])))
cv.MatMulAdd(kalman.transition_matrix, state, process_noise, state)
cv.ShowImage("Kalman", img)
code = cv.WaitKey(100) % 0x100
if code != -1:
break
if code in [27, ord('q'), ord('Q')]:
break
cv.DestroyWindow("Kalman")
samples/python/kmeans.py 已删除 100755 → 0
浏览文件 @ b2ba8b99
#!/usr/bin/python
import urllib2
import cv2.cv as cv
from random import randint
MAX_CLUSTERS = 5
if __name__ == "__main__":
color_tab = [
cv.CV_RGB(255, 0,0),
cv.CV_RGB(0, 255, 0),
cv.CV_RGB(100, 100, 255),
cv.CV_RGB(255, 0,255),
cv.CV_RGB(255, 255, 0)]
img = cv.CreateImage((500, 500), 8, 3)
rng = cv.RNG(-1)
cv.NamedWindow("clusters", 1)
while True:
cluster_count = randint(2, MAX_CLUSTERS)
sample_count = randint(1, 1000)
points = cv.CreateMat(sample_count, 1, cv.CV_32FC2)
clusters = cv.CreateMat(sample_count, 1, cv.CV_32SC1)
# generate random sample from multigaussian distribution
for k in range(cluster_count):
center = (cv.RandInt(rng)%img.width, cv.RandInt(rng)%img.height)
first = k*sample_count/cluster_count
last = sample_count
if k != cluster_count:
last = (k+1)*sample_count/cluster_count
point_chunk = cv.GetRows(points, first, last)
cv.RandArr(rng, point_chunk, cv.CV_RAND_NORMAL,
cv.Scalar(center[0], center[1], 0, 0),
cv.Scalar(img.width*0.1, img.height*0.1, 0, 0))
# shuffle samples
cv.RandShuffle(points, rng)
cv.KMeans2(points, cluster_count, clusters,
(cv.CV_TERMCRIT_EPS + cv.CV_TERMCRIT_ITER, 10, 1.0))
cv.Zero(img)
for i in range(sample_count):
cluster_idx = int(clusters[i, 0])
pt = (cv.Round(points[i, 0][0]), cv.Round(points[i, 0][1]))
cv.Circle(img, pt, 2, color_tab[cluster_idx], cv.CV_FILLED, cv.CV_AA, 0)
cv.ShowImage("clusters", img)
key = cv.WaitKey(0) % 0x100
if key in [27, ord('q'), ord('Q')]:
break
cv.DestroyWindow("clusters")
samples/python/laplace.py 已删除 100755 → 0
浏览文件 @ b2ba8b99
#!/usr/bin/python
import urllib2
import cv2.cv as cv
import sys
if __name__ == "__main__":
laplace = None
colorlaplace = None
planes = [ None, None, None ]
capture = None
if len(sys.argv) == 1:
capture = cv.CreateCameraCapture(0)
elif len(sys.argv) == 2 and sys.argv[1].isdigit():
capture = cv.CreateCameraCapture(int(sys.argv[1]))
elif len(sys.argv) == 2:
capture = cv.CreateFileCapture(sys.argv[1])
if not capture:
print "Could not initialize capturing..."
sys.exit(-1)
cv.NamedWindow("Laplacian", 1)
while True:
frame = cv.QueryFrame(capture)
if frame:
if not laplace:
planes = [cv.CreateImage((frame.width, frame.height), 8, 1) for i in range(3)]
laplace = cv.CreateImage((frame.width, frame.height), cv.IPL_DEPTH_16S, 1)
colorlaplace = cv.CreateImage((frame.width, frame.height), 8, 3)
cv.Split(frame, planes[0], planes[1], planes[2], None)
for plane in planes:
cv.Laplace(plane, laplace, 3)
cv.ConvertScaleAbs(laplace, plane, 1, 0)
cv.Merge(planes[0], planes[1], planes[2], None, colorlaplace)
cv.ShowImage("Laplacian", colorlaplace)
if cv.WaitKey(10) != -1:
break
cv.DestroyWindow("Laplacian")
samples/python/lkdemo.py 已删除 100755 → 0
浏览文件 @ b2ba8b99
#! /usr/bin/env python
print "OpenCV Python version of lkdemo"
import sys
# import the necessary things for OpenCV
import cv2.cv as cv
#############################################################################
# some "constants"
win_size = 10
MAX_COUNT = 500
#############################################################################
# some "global" variables
image = None
pt = None
add_remove_pt = False
flags = 0
night_mode = False
need_to_init = False
#############################################################################
# the mouse callback
# the callback on the trackbar
def on_mouse (event, x, y, flags, param):
# we will use the global pt and add_remove_pt
global pt
global add_remove_pt
if image is None:
# not initialized, so skip
return
if image.origin != 0:
# different origin
y = image.height - y
if event == cv.CV_EVENT_LBUTTONDOWN:
# user has click, so memorize it
pt = (x, y)
add_remove_pt = True
#############################################################################
# so, here is the main part of the program
if __name__ == '__main__':
frames = sys.argv[1:]
if frames == []:
print "usage lkdemo.py <image files>"
sys.exit(1)
# display a small howto use it
print "Hot keys: \n" \
"\tESC - quit the program\n" \
"\tr - auto-initialize tracking\n" \
"\tc - delete all the points\n" \
"\tn - switch the \"night\" mode on/off\n" \
"\tSPACE - next frame\n" \
"To add/remove a feature point click it\n"
# first, create the necessary windows
cv.NamedWindow ('LkDemo', cv.CV_WINDOW_AUTOSIZE)
# register the mouse callback
cv.SetMouseCallback ('LkDemo', on_mouse, None)
fc = 0
while 1:
# do forever
frame = cv.LoadImage(frames[fc])
if image is None:
# create the images we need
image = cv.CreateImage (cv.GetSize (frame), 8, 3)
image.origin = frame.origin
grey = cv.CreateImage (cv.GetSize (frame), 8, 1)
prev_grey = cv.CreateImage (cv.GetSize (frame), 8, 1)
pyramid = cv.CreateImage (cv.GetSize (frame), 8, 1)
prev_pyramid = cv.CreateImage (cv.GetSize (frame), 8, 1)
features = []
# copy the frame, so we can draw on it
cv.Copy (frame, image)
# create a grey version of the image
cv.CvtColor (image, grey, cv.CV_BGR2GRAY)
if night_mode:
# night mode: only display the points
cv.SetZero (image)
if need_to_init:
# we want to search all the good points
# create the wanted images
eig = cv.CreateImage (cv.GetSize (grey), 32, 1)
temp = cv.CreateImage (cv.GetSize (grey), 32, 1)
# the default parameters
quality = 0.01
min_distance = 10
# search the good points
features = cv.GoodFeaturesToTrack (
grey, eig, temp,
MAX_COUNT,
quality, min_distance, None, 3, 0, 0.04)
# refine the corner locations
features = cv.FindCornerSubPix (
grey,
features,
(win_size, win_size), (-1, -1),
(cv.CV_TERMCRIT_ITER | cv.CV_TERMCRIT_EPS, 20, 0.03))
elif features != []:
# we have points, so display them
# calculate the optical flow
features, status, track_error = cv.CalcOpticalFlowPyrLK (
prev_grey, grey, prev_pyramid, pyramid,
features,
(win_size, win_size), 3,
(cv.CV_TERMCRIT_ITER|cv.CV_TERMCRIT_EPS, 20, 0.03),
flags)
# set back the points we keep
features = [ p for (st,p) in zip(status, features) if st]
if add_remove_pt:
# we have a point to add, so see if it is close to
# another one. If yes, don't use it
def ptptdist(p0, p1):
dx = p0[0] - p1[0]
dy = p0[1] - p1[1]
return dx**2 + dy**2
if min([ ptptdist(pt, p) for p in features ]) < 25:
# too close
add_remove_pt = 0
# draw the points as green circles
for the_point in features:
cv.Circle (image, (int(the_point[0]), int(the_point[1])), 3, (0, 255, 0, 0), -1, 8, 0)
if add_remove_pt:
# we want to add a point
# refine this corner location and append it to 'features'
features += cv.FindCornerSubPix (
grey,
[pt],
(win_size, win_size), (-1, -1),
(cv.CV_TERMCRIT_ITER | cv.CV_TERMCRIT_EPS,
20, 0.03))
# we are no longer in "add_remove_pt" mode
add_remove_pt = False
# swapping
prev_grey, grey = grey, prev_grey
prev_pyramid, pyramid = pyramid, prev_pyramid
need_to_init = False
# we can now display the image
cv.ShowImage ('LkDemo', image)
# handle events
c = cv.WaitKey(10) % 0x100
if c == 27:
# user has press the ESC key, so exit
break
# processing depending on the character
if 32 <= c and c < 128:
cc = chr(c).lower()
if cc == 'r':
need_to_init = True
elif cc == 'c':
features = []
elif cc == 'n':
night_mode = not night_mode
elif cc == ' ':
fc = (fc + 1) % len(frames)
cv.DestroyAllWindows()
samples/python/logpolar.py 已删除 100755 → 0
浏览文件 @ b2ba8b99
#!/usr/bin/python
import sys
import urllib2
import cv2.cv as cv
src=None
dst=None
src2=None
def on_mouse(event, x, y, flags, param):
if not src:
return
if event==cv.CV_EVENT_LBUTTONDOWN:
cv.LogPolar(src, dst, (x, y), 40, cv.CV_INTER_LINEAR + cv.CV_WARP_FILL_OUTLIERS)
cv.LogPolar(dst, src2, (x, y), 40, cv.CV_INTER_LINEAR + cv.CV_WARP_FILL_OUTLIERS + cv.CV_WARP_INVERSE_MAP)
cv.ShowImage("log-polar", dst)
cv.ShowImage("inverse log-polar", src2)
if __name__ == "__main__":
if len(sys.argv) > 1:
src = cv.LoadImage( sys.argv[1], cv.CV_LOAD_IMAGE_COLOR)
else:
url = 'http://code.opencv.org/projects/opencv/repository/revisions/master/raw/samples/c/fruits.jpg'
filedata = urllib2.urlopen(url).read()
imagefiledata = cv.CreateMatHeader(1, len(filedata), cv.CV_8UC1)
cv.SetData(imagefiledata, filedata, len(filedata))
src = cv.DecodeImage(imagefiledata, cv.CV_LOAD_IMAGE_COLOR)
cv.NamedWindow("original", 1)
cv.NamedWindow("log-polar", 1)
cv.NamedWindow("inverse log-polar", 1)
dst = cv.CreateImage((256, 256), 8, 3)
src2 = cv.CreateImage(cv.GetSize(src), 8, 3)
cv.SetMouseCallback("original", on_mouse)
on_mouse(cv.CV_EVENT_LBUTTONDOWN, src.width/2, src.height/2, None, None)
cv.ShowImage("original", src)
cv.WaitKey()
cv.DestroyAllWindows()
samples/python/minarea.py 已删除 100755 → 0
浏览文件 @ b2ba8b99
#!/usr/bin/python
import urllib2
import cv2.cv as cv
from random import randint
def roundxy(pt):
return (cv.Round(pt[0]), cv.Round(pt[1]))
def draw_common(points):
success, center, radius = cv.MinEnclosingCircle(points)
if success:
cv.Circle(img, roundxy(center), cv.Round(radius), cv.CV_RGB(255, 255, 0), 1, cv. CV_AA, 0)
box = cv.MinAreaRect2(points)
box_vtx = [roundxy(p) for p in cv.BoxPoints(box)]
cv.PolyLine(img, [box_vtx], 1, cv.CV_RGB(0, 255, 255), 1, cv. CV_AA)
def minarea_array(img, count):
pointMat = cv.CreateMat(count, 1, cv.CV_32SC2)
for i in range(count):
pointMat[i, 0] = (randint(img.width/4, img.width*3/4),
randint(img.height/4, img.height*3/4))
cv.Zero(img)
for i in range(count):
cv.Circle(img, roundxy(pointMat[i, 0]), 2, cv.CV_RGB(255, 0, 0), cv.CV_FILLED, cv. CV_AA, 0)
draw_common(pointMat)
def minarea_seq(img, count, storage):
points = [(randint(img.width/4, img.width*3/4), randint(img.height/4, img.height*3/4)) for i in range(count)]
cv.Zero(img)
for p in points:
cv.Circle(img, roundxy(p), 2, cv.CV_RGB(255, 0, 0), cv.CV_FILLED, cv. CV_AA, 0)
draw_common(points)
if __name__ == "__main__":
img = cv.CreateImage((500, 500), 8, 3)
storage = cv.CreateMemStorage()
cv.NamedWindow("rect & circle", 1)
use_seq = True
while True:
count = randint(1, 100)
if use_seq:
minarea_seq(img, count, storage)
else:
minarea_array(img, count)
cv.ShowImage("rect & circle", img)
key = cv.WaitKey() % 0x100
if key in [27, ord('q'), ord('Q')]:
break
use_seq = not use_seq
cv.DestroyAllWindows()
samples/python/minidemo.py 已删除 100755 → 0
浏览文件 @ b2ba8b99
#! /usr/bin/env python
import cv2.cv as cv
cap = cv.CreateFileCapture("../c/tree.avi")
img = cv.QueryFrame(cap)
print "Got frame of dimensions (", img.width, " x ", img.height, ")"
cv.NamedWindow("win", cv.CV_WINDOW_AUTOSIZE)
cv.ShowImage("win", img)
cv.MoveWindow("win", 200, 200)
cv.WaitKey(0)
cv.DestroyAllWindows()
samples/python/morphology.py 已删除 100755 → 0
浏览文件 @ b2ba8b99
#!/usr/bin/python
import sys
import urllib2
import cv2.cv as cv
src = 0
image = 0
dest = 0
element_shape = cv.CV_SHAPE_RECT
def Opening(pos):
element = cv.CreateStructuringElementEx(pos*2+1, pos*2+1, pos, pos, element_shape)
cv.Erode(src, image, element, 1)
cv.Dilate(image, dest, element, 1)
cv.ShowImage("Opening & Closing", dest)
def Closing(pos):
element = cv.CreateStructuringElementEx(pos*2+1, pos*2+1, pos, pos, element_shape)
cv.Dilate(src, image, element, 1)
cv.Erode(image, dest, element, 1)
cv.ShowImage("Opening & Closing", dest)
def Erosion(pos):
element = cv.CreateStructuringElementEx(pos*2+1, pos*2+1, pos, pos, element_shape)
cv.Erode(src, dest, element, 1)
cv.ShowImage("Erosion & Dilation", dest)
def Dilation(pos):
element = cv.CreateStructuringElementEx(pos*2+1, pos*2+1, pos, pos, element_shape)
cv.Dilate(src, dest, element, 1)
cv.ShowImage("Erosion & Dilation", dest)
if __name__ == "__main__":
if len(sys.argv) > 1:
src = cv.LoadImage(sys.argv[1], cv.CV_LOAD_IMAGE_COLOR)
else:
url = 'http://code.opencv.org/projects/opencv/repository/revisions/master/raw/samples/c/fruits.jpg'
filedata = urllib2.urlopen(url).read()
imagefiledata = cv.CreateMatHeader(1, len(filedata), cv.CV_8UC1)
cv.SetData(imagefiledata, filedata, len(filedata))
src = cv.DecodeImage(imagefiledata, cv.CV_LOAD_IMAGE_COLOR)
image = cv.CloneImage(src)
dest = cv.CloneImage(src)
cv.NamedWindow("Opening & Closing", 1)
cv.NamedWindow("Erosion & Dilation", 1)
cv.ShowImage("Opening & Closing", src)
cv.ShowImage("Erosion & Dilation", src)
cv.CreateTrackbar("Open", "Opening & Closing", 0, 10, Opening)
cv.CreateTrackbar("Close", "Opening & Closing", 0, 10, Closing)
cv.CreateTrackbar("Dilate", "Erosion & Dilation", 0, 10, Dilation)
cv.CreateTrackbar("Erode", "Erosion & Dilation", 0, 10, Erosion)
cv.WaitKey(0)
cv.DestroyWindow("Opening & Closing")
cv.DestroyWindow("Erosion & Dilation")
samples/python/motempl.py 已删除 100755 → 0
浏览文件 @ b2ba8b99
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samples/python/numpy_array.py 已删除 100755 → 0
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samples/python/numpy_warhol.py 已删除 100755 → 0
浏览文件 @ b2ba8b99
#!/usr/bin/python
import urllib2
import sys
import cv2.cv as cv
import numpy
if __name__ == "__main__":
cv.NamedWindow("camera", 1)
capture = cv.CaptureFromCAM(0)
paste = cv.CreateMat(960, 1280, cv.CV_8UC3)
topleft = numpy.asarray(cv.GetSubRect(paste, (0, 0, 640, 480)))
topright = numpy.asarray(cv.GetSubRect(paste, (640, 0, 640, 480)))
bottomleft = numpy.asarray(cv.GetSubRect(paste, (0, 480, 640, 480)))
bottomright = numpy.asarray(cv.GetSubRect(paste, (640, 480, 640, 480)))
while True:
img = cv.GetMat(cv.QueryFrame(capture))
n = (numpy.asarray(img)).astype(numpy.uint8)
red = n[:,:,0]
grn = n[:,:,1]
blu = n[:,:,2]
topleft[:,:,0] = 255 - grn
topleft[:,:,1] = red
topleft[:,:,2] = blu
topright[:,:,0] = blu
topright[:,:,1] = 255 - red
topright[:,:,2] = grn
bottomright[:,:,0] = red
bottomright[:,:,1] = grn
bottomright[:,:,2] = 255 - blu
fgrn = grn.astype(numpy.float32)
fred = red.astype(numpy.float32)
bottomleft[:,:,0] = blu
bottomleft[:,:,1] = (abs(fgrn - fred)).astype(numpy.uint8)
bottomleft[:,:,2] = red
cv.ShowImage("camera", paste)
if cv.WaitKey(6) == 27:
break
cv.DestroyAllWindows()
samples/python/peopledetect.py 已删除 100755 → 0
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samples/python/pyramid_segmentation.py 已删除 100755 → 0
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samples/python/squares.py 已删除 100755 → 0
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samples/python/watershed.py 已删除 100755 → 0
浏览文件 @ b2ba8b99
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samples/python2/_coverage.py
浏览文件 @ f886651c
......@@ -24,8 +24,3 @@ if __name__ == '__main__':
r = 1.0 * len(cv2_used) / len(cv2_callable)
print '\ncv2 api coverage: %d / %d (%.1f%%)' % ( len(cv2_used), len(cv2_callable), r*100 )
print '\nold (cv) symbols:'
for s in found:
if s.startswith('cv.'):
print s
samples/python2/browse.py
浏览文件 @ f886651c
此差异已折叠。
samples/python2/common.py
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samples/python2/contours.py
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samples/python2/deconvolution.py
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samples/python2/dft.py 100644 → 100755
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samples/python2/distrans.py
浏览文件 @ f886651c
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samples/python2/facedetect.py
浏览文件 @ f886651c
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samples/python2/fitline.py
浏览文件 @ f886651c
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samples/python2/gaussian_mix.py
浏览文件 @ f886651c
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samples/python2/houghcircles.py
浏览文件 @ f886651c
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samples/python2/houghlines.py
浏览文件 @ f886651c
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samples/python2/mouse_and_match.py
浏览文件 @ f886651c
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samples/python2/texture_flow.py
浏览文件 @ f886651c
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samples/python2/turing.py
浏览文件 @ f886651c
此差异已折叠。
samples/python2/video.py
浏览文件 @ f886651c
此差异已折叠。
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