# Read the list of test image files
source_dir = dir_prefix + image_directory + '/'
img_files = glob.glob(source_dir + '*.jpg')
filenumber = 1
nfiles = len(img_files)
for testfile in img_files:
print '%s (%d/%d)' % (testfile,filenumber,nfiles)
filenumber += 1
###################################################################
# Change the following line to use a different detection routine. #
###################################################################
im = cv.imread(testfile)#fla - added this
matchingcoords = cascadedetect.detect(im)#originally detect(testfile) which was str not im
boundingboxes = getboundingboxes(testfile)
'''if boundingboxes == []:
break'''
#im = cv.LoadImage(testfile)#fla - void in opencv 3.0. Above i used imread
if show_images:
for match in matchingcoords:
xcentre = match[0]
ycentre = match[1]
cv.circle( im, (xcentre,ycentre), 10, [0,0,255] )
for bb in boundingboxes:
cv.rectangle(im,(bb[0],bb[2]),(bb[1],bb[3]), [255, 255, 255], 1)
import os
import copy
import sys
import cascadedetect
import boosteddetect
if __name__=='__main__':
imagefilename = sys.argv[1]
xstep = int(sys.argv[2])
ystep = int(sys.argv[3])
size = int(sys.argv[4])
detectortype = sys.argv[5]
if detectortype=='cascade':
matchingcoords = cascadedetect.detect(imagefilename)
else:
patchscores = boosteddetect.detect(imagefilename,featuretype=detectortype,returnpatchscores=True,paramsdir='../../../data/params/')
im = cv.LoadImage(imagefilename)
# Scan through patch locations in the image
patchidx = 0
width = im.width
height = im.height
x = xstep
y = ystep
while y<height:
x = xstep;
while (x<width):
# Test whether a square at this point includes the center of a detected object
for image_directory in test_directories:
# Read the list of test image files
source_dir = dir_prefix + image_directory + '/'
img_files = glob.glob(source_dir + '*.jpg')
filenumber = 1
nfiles = len(img_files)
for testfile in img_files:
print '%s (%d/%d)' % (testfile, filenumber, nfiles)
filenumber += 1
###################################################################
# Change the following line to use a different detection routine. #
###################################################################
matchingcoords = cascadedetect.detect(testfile)
boundingboxes = getboundingboxes(testfile)
im = cv.LoadImage(testfile)
if show_images:
for match in matchingcoords:
xcentre = match[0]
ycentre = match[1]
cv.Circle(im, (xcentre, ycentre), 10, [0, 0, 255])
for bb in boundingboxes:
cv.Rectangle(im, (bb[0], bb[2]), (bb[1], bb[3]),
[255, 255, 255], 1)
TPim = FPim = FNim = 0
# Read the list of test image files
source_dir = dir_prefix + image_directory + '/'
img_files = glob.glob(source_dir + '*.jpg')
filenumber = 1
nfiles = len(img_files)
for testfile in img_files:
print '%s (%d/%d)' % (testfile, filenumber, nfiles)
filenumber += 1
###################################################################
# Change the following line to use a different detection routine. #
###################################################################
im = cv.imread(testfile) #fla - added this
matchingcoords = cascadedetect.detect(
im) #originally detect(testfile) which was str not im
boundingboxes = getboundingboxes(testfile)
'''if boundingboxes == []:
break'''
#im = cv.LoadImage(testfile)#fla - void in opencv 3.0. Above i used imread
if show_images:
for match in matchingcoords:
xcentre = match[0]
ycentre = match[1]
cv.circle(im, (xcentre, ycentre), 10, [0, 0, 255])
for bb in boundingboxes:
cv.rectangle(im, (bb[0], bb[2]), (bb[1], bb[3]),
[255, 255, 255], 1)
for image_directory in test_directories:
# Read the list of test image files
source_dir = dir_prefix + image_directory + '/'
img_files = glob.glob(source_dir + '*.jpg')
filenumber = 1
nfiles = len(img_files)
for testfile in img_files:
print '%s (%d/%d)' % (testfile,filenumber,nfiles)
filenumber += 1
###################################################################
# Change the following line to use a different detection routine. #
###################################################################
matchingcoords = cascadedetect.detect(testfile)
boundingboxes = getboundingboxes(testfile)
im = cv.LoadImage(testfile)
if show_images:
for match in matchingcoords:
xcentre = match[0]
ycentre = match[1]
cv.Circle( im, (xcentre,ycentre), 10, [0,0,255] )
for bb in boundingboxes:
cv.Rectangle(im,(bb[0],bb[2]),(bb[1],bb[3]), [255, 255, 255], 1)
TPim = FPim = FNim = 0
from lxml import etree
import cv
import os
import copy
import sys
import cascadedetect
if __name__=='__main__':
imagefilename = sys.argv[1]
xstep = int(sys.argv[2])
ystep = int(sys.argv[3])
size = int(sys.argv[4])
matchingcoords = cascadedetect.detect(imagefilename,cascadefile='../../data/cascade/cascade_HAAR2.xml',
trainpatchsize=14,smallestobjectsize=45.0,scalefactor=1.1,minneighbours=1)
im = cv.LoadImage(imagefilename)
# Scan through patch locations in the image
width = im.width
height = im.height
x = xstep
y = ystep
while y<height:
x = xstep;
while (x<width):
# Test whether a square at this point includes the center of a detected object
objecthere = 0
for c in matchingcoords:
if (x-size/2 < c[0]) and (x+size/2 > c[0]) and (y-size/2 < c[1]) and (y+size/2 > c[1]):
objecthere = 1