for i in range(3):
imp = img[:,:,i]
print ('\t'.join(map(str, [stats.min(imp), stats.max(imp), stats.median(imp), stats.mean(imp)]))), "\t",
print fft.energy(gray), "\t", fft.energy(ngray), "\t",
for i in range(15):
k=2*i+1
print lap.sum(ngray, k), "\t",
for i in range(25):
t2 = 10*i
print edge.sumCanny(ngray, 1, t2), "\t",
#edge.sumCanny(gray)
# Contour detection
ctr = Contours.contours(ngray)
for i in range(5):
threshold=50*i
ctr.withCanny(1, threshold)
if ctr.numberOfContours() == 0:
print "0\t0\t0\t0\t0\t0\t0\t0\t0\t0"
else:
try:
print "\t".join(map(str, [ctr.numberOfContours(), ctr.numberOfClosedContours(),
ctr.numberOfOpenContours(), ctr.totalContourArea(), cv2.contourArea(ctr.largestContourByArea()),
ctr.totalPerimeterLength()])), "\t",
ctr.linelengths()
print "\t".join(map(str, [ctr.maxLineLength(), ctr.meanLineLength(), ctr.medianLineLength(), ctr.modeLineLength()])), "\t",
except ValueError as e:
sys.stderr.write("There was an error calculating the contours for " + imgfile +": " + e.message + "\n")
break
def imageWriter(images,seen,args,fout,classification,stats,fft,lap,edge):
for imgfile in images:
if imgfile in seen: continue
if os.path.isdir(os.path.join(args.directory, imgfile)):
temp = os.listdir(os.path.join(args.directory, imgfile))
for f in temp:
images.append(os.path.join(imgfile, f))
continue
#rewrite of above if statement
#if os.path.isdir(os.path.join(args.directory,imgfile)):
# temp = os.listdir(os.path.join(args.directory,imgfile))
# pool = Pool()
# pool.map(images.append, os.path.join(imgfile, f))
# pool.close()
# pool.join()
# continue
if not args.all and imgfile not in classification:
continue
# silently skip the bin files that have the gps data
if imgfile.endswith('bin'):
continue
# alert to other files that were skipped
if not (imgfile.endswith('png') | imgfile.endswith('jpg')):
sys.stderr.write("Skipped file: " + imgfile + "\n")
continue
if args.verbose:
sys.stderr.write("Parsing " + imgfile + "\n")
fout.write( imgfile + "\t" )
if imgfile in classification:
fout.write( classification[imgfile] + "\t")
else:
fout.write( "unknown\t" )
img = ImageIO.cv2read(os.path.join(args.directory, imgfile))
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
fout.write( ('\t'.join(map(str, [stats.min(gray), stats.max(gray), stats.median(gray), stats.mean(gray)]))) + "\t" )
ngray = Normalization.equalizeHistograms(gray)
# apply a gaussian blur to remove edge effects
ngray = cv2.GaussianBlur(ngray, (3,3), 0)
fout.write( ('\t'.join(map(str, [stats.min(ngray), stats.max(ngray), stats.median(ngray), stats.mean(ngray)]))) + "\t")
for i in range(3):
imp = img[:,:,i]
fout.write( ('\t'.join(map(str, [stats.min(imp), stats.max(imp), stats.median(imp), stats.mean(imp)]))) + "\t" )
fout.write( str(fft.energy(gray)) + "\t" + str(fft.energy(ngray)) + "\t")
if args.features:
feats.detect_kp_ORB(ngray)
fout.write( str(feats.numberKeyPoints()) + "\t" + str(feats.medianKeyPointSize()) + "\t" + str(feats.meanKeyPointSize()) + "\t")
for i in range(15):
fout.write( str(feats.numKeyPoints(i*10)) + "\t")
else:
fout.write("0\t0\t0\t");
for i in range(15):
fout.write("0\t")
for i in range(15):
k=2*i+1
fout.write( str(lap.sum(ngray, k)) + "\t")
for i in range(25):
t2 = 10*i
fout.write( str(edge.sumCanny(ngray, 1, t2)) + "\t")
#edge.sumCanny(gray)
# Contour detection
ctr = Contours.contours(ngray)
for i in range(5):
threshold=50*i
ctr.withCanny(1, threshold)
if ctr.numberOfContours() == 0:
fout.write( "0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t" )
else:
try:
fout.write( "\t".join(map(str, [ctr.numberOfContours(), ctr.numberOfClosedContours(),
ctr.numberOfOpenContours(), ctr.totalContourArea(), cv2.contourArea(ctr.largestContourByArea()),
ctr.totalPerimeterLength()])) + "\t")
ctr.linelengths()
fout.write( "\t".join(map(str, [ctr.maxLineLength(), ctr.meanLineLength(), ctr.medianLineLength(), ctr.modeLineLength()])) + "\t")
except Exception as e:
sys.stderr.write("There was an error calculating the contours for " + imgfile +": " + e.message + "\n")
fout.write( "0\t0\t0\t0\t0\t0\t0\t0\t0\t0\t" )
fout.write("\n")
import sys
sys.path.append('../Modules/')
import Contours
import cv2
im = cv2.imread('test.jpg')
g = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)
c = Contours.contours(g)
print "Threshold\t# contours\tClosed\tOpen\tTotal area\tLargest\tPerimeter"
for i in range(5):
thresh = 50*i
c.withCanny(1, thresh)
# print "\t".join(map(str, [thresh, c.numberOfContours(), c.numberOfClosedContours(),
# c.numberOfOpenContours(), c.totalContourArea(), cv2.contourArea(c.largestContourByArea()),
# c.totalPerimeterLength()]))
print thresh, "\t",
print c.numberOfContours(), "\t",
print c.numberOfClosedContours(), "\t",
print c.numberOfOpenContours(), "\t",
print c.totalContourArea(), "\t",
print cv2.contourArea(c.largestContourByArea()), "\t",
print c.totalPerimeterLength()
