#?-*-?coding:?utf-8?-*-
“““
#!/usr/local/bin/python2.7
#python?findFeatures.py?-t?dataset/train/
“““

import?argparse?as?ap
import?cv2
import?imutils
import?numpy?as?np
import?os
from?sklearn.externals?import?joblib
from?scipy.cluster.vq?import?*

from?sklearn?import?preprocessing
from?rootsift?import?RootSIFT
import?math

#?Get?the?path?of?the?training?set
parser?=?ap.ArgumentParser（）
parser.add_argument（“-t“?“--trainingSet“?help=“Path?to?Training?Set“?required=“True“）
args?=?vars（parser.parse_args（））

#?Get?the?training?classes?names?and?store?them?in?a?list
train_path?=?args[“trainingSet“]
#train_path?=?“dataset/train/“

training_names?=?os.listdir（train_path）

numWords?=?1000

#?Get?all?the?path?to?the?images?and?save?them?in?a?list
#?image_paths?and?the?corresponding?label?in?image_paths
image_paths?=?[]
for?training_name?in?training_names:
????image_path?=?os.path.join（train_path?training_name）
????image_paths?+=?[image_path]

#?Create?feature?extraction?and?keypoint?detector?objects
fea_det?=?cv2.FeatureDetector_create（“SIFT“）
des_ext?=?cv2.DescriptorExtractor_create（“SIFT“）

#?List?where?all?the?descriptors?are?stored
des_list?=?[]

for?i?image_path?in?enumerate（image_paths）:
????im?=?cv2.imread（image_path）
????print?“Extract?SIFT?of?%s?image?%d?of?%d?images“?%（training_names[i]?i?len（image_paths））
????kpts?=?fea_det.detect（im）
????kpts?des?=?des_ext.compute（im?kpts）
????#?rootsift
????#rs?=?RootSIFT（）
????#des?=?rs.compute（kpts?des）
????des_list.append（（image_path?des））

#?Stack?all?the?descriptors?vertically?in?a?numpy?array
#downsampling?=?1
#descriptors?=?des_list[0][1][::downsampling:]
#for?image_path?descriptor?in?des_list[1:]:
#????descriptors?=?np.vstack（（descriptors?descriptor[::downsampling:]））

#?Stack?all?the?descriptors?vertically?in?a?numpy?array
descriptors?=?des_list[0][1]
for?image_path?descriptor?in?des_list[1:]:
????descriptors?=?np.vstack（（descriptors?descriptor））

#?Perform?k-means?clustering
print?“Start?k-means:?%d?words?%d?key?points“?%（numWords?descriptors.shape[0]）
voc?variance?=?kmeans（descriptors?numWords?1）

#?Calculate?the?histogram?of?features
im_features?=?np.zeros（（len（image_paths）?numWords）?“float32“）
for?i?in?xrange（len（image_paths））:
????words?distance?=?vq（des_list[i][1]voc）
????for?w?in?words:
????????im_features[i][w]?+=?1

#?Perform?Tf-Idf?vectorization
nbr_occurences?=?np.sum（?（im_features?>?0）?*?1?axis?=?0）
idf?=?np.array（np.log（（1.0*len（image_paths）+1）?/?（1.0*nbr_occurences?+?1））?‘float32‘）

#?Perform?L2?normalization
im_features?=?im_features*idf
im_features?=?preprocessing.normalize（im_features?norm=‘l2‘）

joblib.dump（（im_features?image_paths?idf?numWords?voc）?“bof.pkl“?compress=3）

?屬性????????????大小?????日期????時間???名稱
-----------?---------??----------?-----??----

?????文件?????496225??2015-06-27?16:04??bow\bof.pkl

?????文件???????2804??2015-07-21?10:55??bow\findFeatures.py

?????文件????????707??2015-07-21?10:55??bow\rootsift.py

?????文件???????2200??2015-07-21?10:56??bow\search.py

?????文件??????13155??2015-07-21?10:53??bow\使用必讀.docx

?????目錄??????????0??2015-07-21?11:04??bow\dataset\train

?????目錄??????????0??2015-07-21?10:33??bow\dataset

?????目錄??????????0??2015-07-21?10:56??bow

-----------?---------??----------?-----??----

???????????????515091????????????????????8