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