def getDistanceTest():
from algorithm import getDistance
m,n=20,10
ma = np.zeros((m,n)).astype(int)
ma[:5,5:]=1
ma[5:,:5]=2
ma[5:,5:]=3
dis = getDistance(ma)
print ma
print dis[0][2]
print dis[0][1]
def getWeightSumTest():
from algorithm import getLbp ,getVectors,getWeightSum
labelMap = getSlic(img,200)
maxLabel = labelMap.max() + 1
im = sk.color.rgb2lab(img)
degreeVectors, Ws = getVectors(im, labelMap)
vectors = getWeightSum(labelMap, degreeVectors, Ws)
m,n = labelMap.shape
imgg = np.zeros((m,n))
imgg2 = np.zeros((m,n))
order = ['lab','l','a','b','lab-texture','l-texture','a-texture','b-texture']
labs = [im]+ [im[:,:,i] for i in range(3)]
lbps = map(lambda c: getLbp(c,labelMap,1)[1],labs)
labLbp = labs + lbps
for color in range(vectors.shape[1]):
for k in range(maxLabel):
imgg[labelMap==k]=vectors[k][color]
imgg2[labelMap==k]=degreeVectors[k][color]
print order[color],'raw | scatter | weight sum'
# show(sk.exposure.equalize_hist(imgg))
show([labLbp[color],imgg2,imgg],1)
loga(degreeVectors)
loga(vectors)
g()
def getEdgeImg(img, labelMap=None, width=0.0):
'''
width(float):how width of edge
return a list of label: edge of labelMap
'''
labelMap = getSlic(img, 300) if labelMap is None else labelMap
width = int(min(*labelMap.shape) * width)
u, d, l, r = (labelMap[0:width + 1].ravel(), labelMap[-1 - width:].ravel(),
labelMap[:,
0:width + 1].ravel(), labelMap[:,
-1 - width:].ravel())
edge = np.unique(np.c_[[u], [d], [l], [r]])
new = np.zeros(img.shape)
for i in edge:
new[labelMap == i] = 1
show(new)
return new
IMG_DIR = r'C:\D\dataset\saliency\ECSSD-small\images/'
COARSE_DIR =r'C:\D\dataset\saliency\ECSSD-small\ground_truth_mas/'
IMG_DIR = r'test/'
COARSE_DIR ='test/'
IMG_NAME_LIST = filter(lambda x:x[-3:]=='jpg',listdir(IMG_DIR))
setModuleConstant(alg)
imgName = IMG_NAME_LIST[0]
img,imgGt = readImg(imgName)
rgbImg = img
rgbImg = np.zeros((100,100,3))
rgbImg[25:75,25:75,1:]=1.
#show(rgbImg)
def integratImgsBy3wayTest():
from algorithm import getSlic,getCoarseDic,integratImgsBy3way,buildMethodDic
labelMap = getSlic(rgbImg,300)
img = rgbImg
m, n = labelMap.shape
coarseMethods = ['GT']
coarseDic = getCoarseDic(imgName,coarseMethods)
# show(coarseDic)
coarseImgs=coarseDic.values()
g()