def processImage(dirname, filename):
(p, e) = os.path.splitext(filename)
p += ".txt"
annotationFile = os.path.join(dirname, "annotate", p)
builddirname = os.path.join(dirname, "build")
(l, t, w, h) = (-1, -1, -1, -1)
with file(annotationFile) as fp:
for l in fp:
l = l.strip()
if not l:
continue
m = r1.match(l)
m2 = r2.match(l)
p2 = l.split(", ")
if not m and m2:
(l, t, w, h) = (
int(m2.group("left")),
int(m2.group("top")),
int(m2.group("width")),
int(m2.group("height")),
)
break
pass
pass
if l >= 0 and t >= 0 and w >= 0 and h >= 0:
imagefilename = os.path.join(dirname, filename)
im2 = None
img = cv2.imread(imagefilename)
im2 = img[t : t + h, l : l + w]
# im = Image.open(imagefilename)
print filename, img.size, l, t, l + w, t + h
# im2 = im.crop((l,t,w+l,h+t))
im3 = cv2.resize(im2, (128, 64), interpolation=cv2.INTER_LANCZOS4)
im2 = None
(n, e) = os.path.splitext(filename)
n += "_canonical"
if not os.path.exists(builddirname):
os.mkdir(builddirname)
# im3 = im2.resize((128, 64), Image.ANTIALIAS)
# im3 = im2.resize((128, 64), Image.LINEAR)
# cvimg = cv.CreateImageHeader(im3.size, cv.IPL_DEPTH_8U, 3) # cimg2 is a OpenCV image
# cv.SetData(cvimg, im3.tostring())
numpyImg = nu.asarray(im3)
hogc.gammaCorrect(numpyImg, 2.2, True)
# print type(cvimg)
# normalizedImg = cv2.cvtColor(numpyImg, cv2.COLOR_RGB2BGR)
# normalizedImg = normalizeImage(numpyImg)
# im3.save(os.path.join(builddirname, n + e))
# im3 = None
cv2.imwrite((os.path.join(builddirname, n + e)), numpyImg)
cvimg = None
pass
def test_GammaCorrect(self):
height =2
width = 5
grayImg = np.zeros((height,width,3), np.uint8)
grayImg[:,:] = (128,128,128)
hogc.gammaCorrect(grayImg, 2, False )
self.assertEqual(list(grayImg[1,2]) , [64,64,64])
hogc.gammaCorrect(grayImg, 2, reverse=True )
self.assertEqual(list(grayImg[1,4]) , [128,128,128])
def processImage(dirname, filename):
if True:
imagefilename = os.path.join(dirname, filename)
builddirname = os.path.join(dirname, "build")
im2 = None
img = cv2.imread(imagefilename)
print filename, img.size
(n, e) = os.path.splitext(filename)
n += "_normalized"
if not os.path.exists(builddirname):
os.mkdir(builddirname)
numpyImg = nu.asarray(img)
hogc.gammaCorrect(numpyImg, 2.2, True)
normalizedImg = normalizeImage(numpyImg)
cv2.imwrite((os.path.join(builddirname, n + e)), normalizedImg)
cvimg = None
pass
def hog(img, hogScheme, aHistTemplate, smAngle, smMag, descriptor):
#print img.width, img.height
imgCopy = cv2.resize(img, (128, 64))
numpyImg = np.asarray(imgCopy)
hogc.gammaCorrect(numpyImg, 2.2, True)
#normalizedImg = normalizeImage(numpyImg)
convertedImg = cv2.cvtColor( numpyImg, cv2.COLOR_BGR2GRAY)
h = convertedImg.shape[0]
w = convertedImg.shape[1]
assert(descriptor.shape[0] == hogScheme.numBlocksVertical * hogScheme.numBlocksHorizontal * hogScheme.numCellsInUnitPerSide * hogScheme.numCellsInUnitPerSide * 9)
assert(descriptor.dtype == np.float32)
hog = hogc.Hog(hogScheme, hogc.Hog.BlockGaussianWeightingPolicy.YesGaussian, hogc.Hog.BlockNormalizationPolicy.L2Normalization)
for r in range(0, hogScheme.numBlocksVertical):
for c in range(0, hogScheme.numBlocksHorizontal):
histVec = hogc.FloatVec()
hog.computeBlock( convertedImg,aHistTemplate, r, c, smAngle, smMag, False, histVec)
hogc.copyToNpArray(histVec, (r*15 +c)*36, descriptor)
return
def processImage2(builddir, dirname, filename):
if True:
imagefilename = os.path.join(dirname, filename)
im2 = None
img = cv2.imread(imagefilename)
print filename, img.size
im2 = cv2.resize(img, (128, 64), interpolation=cv2.INTER_LANCZOS4)
img = None
(n, e) = os.path.splitext(filename)
n += "_canonical"
if not os.path.exists(builddir):
os.mkdir(builddir)
numpyImg = nu.asarray(im2)
hogc.gammaCorrect(numpyImg, 2.2, True)
# normalizedImg = normalizeImage(numpyImg)
cv2.imwrite((os.path.join(builddir, n + e)), numpyImg)
cvimg = None
pass
