def calcDistanceHist( queryImage , df_hist) :
featsVectors = df_hist.values.tolist()
distances = {}
print('--------------- calculate distances for Hist Feats --------------------')
for i in range(len(featsVectors)):
queryFeatures = histFeats(queryImage)
imgFeatures = featsVectors[i]
dist = euclidean(queryFeatures,imgFeatures)
print('dist (query image , image %d )'%(i+1)+'-----> %f'%dist)
distances[i] = dist
print('------------calculate distances for Hist Feats completed ---------')
distances = normalize(distances , 25)
return distances
def calcDistanceHaralickTexture(queryImage , df_haralick) :
featsVectors = df_haralick.values.tolist()
distances = {}
print('--------------- calculate distances for Haralick Feats -------------------')
for i in range(len(featsVectors)):
queryFeatures = haralickTextureFeats(queryImage)
imgFeatures = featsVectors[i]
#imgFeatures = cv2.normalize(imgFeatures, None, alpha=0, beta=1, norm_type=cv2.NORM_MINMAX)
dist = euclidean(queryFeatures,imgFeatures)
print('dist (query image , image %d )'%(i+1)+'-----> %f'%dist)
distances[i] = dist
print('------------calculate distances for HaralickTexture Feats completed ---------')
distances = normalize(distances , 25)
return distances
def calcDistanceColorDom(queryImage, nbreDominantColors, df_colorDom):
featsVectors = df_colorDom.values.tolist()
distances = {}
print(
'--------- calculate distances for color dominant feats -----------')
for i in range(len(featsVectors)):
queryFeatures = colorDominantFeats(queryImage, nbreDominantColors)
imgFeatures = featsVectors[i]
dist = euclidean(queryFeatures, imgFeatures)
print('dist (query image , image %d )' % (i + 1) + '-----> %f' % dist)
distances[i] = dist
print(
'------------calculate distances for colorDom Feats completed ---------'
)
distances = normalize(distances, 25)
return distances
def calcDistanceGabor( queryImage , df_gabor) :
featsVectors = df_gabor.values.tolist()
distances = {}
print('--------------- calculate distances for Gabor Feats -------------------')
for i in range(len(featsVectors)):
queryFeatures = filtreGaborFeats(queryImage)
imgFeatures = featsVectors[i]
dist = euclidean(queryFeatures,imgFeatures)
#dist = cv2.compareHist(queryFeatures, imgFeatures, cv2.HISTCMP_CHISQR)
print('dist (query image , image %d )'%(i+1)+'-----> %f'%dist)
distances[i] = dist
print('------------calculate distances for Gabor Feats completed ---------')
distances = normalize(distances , 25)
return distances
