def run(self):
# print "Starting " + self.name
while not exitFlag:
queueLock.acquire()
if not workQueue.empty() and not filesQueue.full():
path = self.q.get()
print "%d" % filesQueue.qsize()
queueLock.release()
# t1 = cv2.getTickCount()
des2 = np.asarray(
image.loadImageFromPath(path, cv2.IMREAD_GRAYSCALE, False),
np.float32)
name = image.fileName(path)
# t2 = cv2.getTickCount()
if len(des2) >= 2:
queueLock.acquire()
filesQueue.put({'n': name, 'd': des2})
if filesQueue.qsize() > WORK_THREAD_COUNT * 10:
e.set()
queueLock.release()
# t3 = cv2.getTickCount()
# time = (e2 - e1) / cv2.getTickFrequency()
# print "R: %s s P: %s s" % ((t2 - t1) / cv2.getTickFrequency(), (t3 - t2) / cv2.getTickFrequency())
else:
queueLock.release()
time.sleep(5)
print "Exiting " + self.name
def run(self):
# print "Starting " + self.name
while not self.event.is_set():
self.lock.acquire()
if not self.queue.empty():
path = self.queue.get()
self.lock.release()
# t1 = cv2.getTickCount()
des2 = np.asarray(
image.loadImageFromPath(path, cv2.IMREAD_GRAYSCALE, False),
np.float32)
name = image.fileName(path)
# t2 = cv2.getTickCount()
if len(des2) >= 2:
self.lock.acquire()
self.files.append({'n': name, 'd': des2})
self.lock.release()
# t3 = cv2.getTickCount()
# time = (e2 - e1) / cv2.getTickFrequency()
# print "R: %s s P: %s s" % ((t2 - t1) / cv2.getTickFrequency(), (t3 - t2) / cv2.getTickFrequency())
else:
self.lock.release()
def run(self):
i = 0
print("Starting " + self.name)
while not self.event.is_set():
self.lock.acquire()
if not self.workQueue.empty():
path = self.workQueue.get()
self.lock.release()
i += 1
des2 = image.loadImageFromPath(path, cv2.IMREAD_GRAYSCALE,
False)
des2 = np.asarray(des2, np.float32)
if len(des2) >= 2:
name = image.fileName(path)
m = image.match(self.des, des2)
if len(m) >= 50:
self.lock.acquire()
self.finds.append({'m': len(m), 'n': name})
self.lock.release()
print("Matched %s file %s" % (len(m), name))
# time.sleep(2)
else:
self.lock.release()
print("Exiting %s - %d" % (self.name, i))
def testFlan():
flann = cv2.FlannBasedMatcher(index_params, search_params)
load_descriptors(flann)
# img = im.loadImageFromUrl('http://comicstore.cf/uploads/diamonds/STK360887.jpg', resize=True, maxSize=200)
img = im.loadImageFromPath('../images/z13.jpg', resize=True, maxSize=500)
_kp, _des = sift.detectAndCompute(img, None)
kp, des = im.sortKp(_kp, _des, 1000)
t_start = cv2.getTickCount()
matches = flann.knnMatch(des, k=2)
t_end = cv2.getTickCount()
print "Time match: %s" % ((t_end - t_start) / cv2.getTickFrequency())
m = [(m.queryIdx, m.trainIdx, m.imgIdx) for m, n in matches
if m.distance < n.distance * 0.75]
duples = [
c for n, (a, b, c) in enumerate(m)
if c in [cc for aa, bb, cc in m[:n if n > 0 else n + 1]]
]
no_duples = [
c for n, (a, b, c) in enumerate(m)
if c not in duples and c not in [cc for aa, bb, cc in m[:n]]
]
print "Points: %d,\n no duples(%d): %s,\n duples(%d): %s" % (
len(m), len(no_duples), ' '.join([str(i) for i in no_duples]),
len(duples), ' '.join([str(i) for i in duples]))
def checkFromRAM(imgPath, threadsCount=200):
finds = []
img = image.loadImageFromPath(imgPath, cv2.IMREAD_GRAYSCALE, True, 200)
kp, des = image.getKpDes(img)
threadList = []
count = 0
while count < threadsCount:
threadList.append("Thread-%d" % count)
count += 1
if len(files) == 0:
print("Hash files count is empty")
else:
print("Files count: %d " % len(files))
event = threading.Event()
queueLock = threading.Lock()
workQueue = Queue.Queue(len(files) + 10)
threads = []
threadID = 1
# Create new threads
for tName in threadList:
thread = RamThread(threadID, tName, event, queueLock, workQueue,
kp, des, finds)
thread.daemon = True
thread.start()
threads.append(thread)
threadID += 1
# Fill the queue
queueLock.acquire()
for i in range(0, len(files) - 1):
workQueue.put(i)
queueLock.release()
# Wait for queue to empty
while not workQueue.empty():
pass
# Notify threads it's time to exit
event.set()
# Wait for all threads to complete
for t in threads:
t.join()
return finds
def run(self):
print "Starting " + self.name
queueLock.acquire()
des1 = des.copy()
queueLock.release()
while not exitFlag:
queueLock.acquire()
if not workQueue.empty():
path = self.q.get()
queueLock.release()
des2 = image.loadImageFromPath(path, cv2.IMREAD_GRAYSCALE,
False)
des2 = np.asarray(des2, np.float32)
name = image.fileName(path)
if isinstance(des2, list) and len(des2) >= 2:
m = image.match(des1, des2)
if len(m) >= 50:
print "Matched %s file %s" % (len(m), name)
else:
queueLock.release()
print "Exiting " + self.name
queueLock.release()
print("Exiting " + self.name)
ap = argparse.ArgumentParser()
ap.add_argument("-t",
"--threads",
required=True,
type=int,
help="Threads count")
ap.add_argument("-i", "--image", required=True, help="Path to the image")
ap.add_argument("-hs", "--hash", required=True, help="Path to the hash files")
args = vars(ap.parse_args())
img = image.loadImageFromPath(args['image'], cv2.IMREAD_GRAYSCALE, True, 200)
kp, des = image.getKpDes(img)
threadList = []
count = 0
while count < args['threads']:
threadList.append("Thread-%d" % count)
count += 1
nameList = []
for imagePath in glob.glob("%s*%s" % (args['hash'], KPC_EXT)):
nameList.append(imagePath)
if len(nameList) == 0:
exit(0)
else:
queueLock.acquire()
if not workQueue.empty():
url = q.get()
queueLock.release()
name2 = image.fileName(url)
img2 = image.loadImageFromUrl(url)
image.compare(name1, name2, img1.copy(), img2)
# print "%s processing %s" % (threadName, data)
else:
queueLock.release()
url1 = '../images/M7.jpg'
img1 = image.loadImageFromPath(url1)
# url1 = 'http://comicstore.cf/uploads/diamonds/STK309612.jpg'
# img1 = image.loadImageFromUrl(url1)
name1 = image.fileName(url1)
threadList = []
count = 0
while count < THREAD_COUNT:
threadList.append("Thread-%d" % count)
count += 1
nameList = sql.executeQuery()
if len(nameList) == 0:
data = self.q.get()
queueLock.release()
des2 = data['d']
name = data['n']
m = image.match(des1, des2)
if len(m) >= 50:
print "Matched %s file %s" % (len(m), name)
else:
queueLock.release()
time.sleep(1)
print "Exiting " + self.name
img = image.loadImageFromPath('../images/M6.jpg', cv2.IMREAD_GRAYSCALE, True,
200)
kp, des = image.getKpDes(img)
e = threading.Event()
workThreadList = []
count = 0
while count < WORK_THREAD_COUNT:
workThreadList.append("WorkThread-%d" % count)
count += 1
filesThreadList = []
count = 0
while count < FILES_THREAD_COUNT:
filesThreadList.append("FileThread-%d" % count)
count += 1
def check(imgPath,
hashPath=HASH_PATH,
withSubFolders=True,
threadsCount=200,
ext=DES_EXT):
finds = []
img = image.loadImageFromPath(imgPath, cv2.IMREAD_GRAYSCALE, True, 200)
kp, des = image.getKpDes(img)
threadList = []
count = 0
while count < threadsCount:
threadList.append("Thread-%d" % count)
count += 1
nameList = []
if withSubFolders:
folder = 1
path = "%s%s/" % (hashPath, folder)
print(path)
while os.path.exists(path):
for imagePath in glob.glob("%s*%s" % (path, ext)):
nameList.append(imagePath)
if len(nameList) == 50000:
break
folder += 1
path = "%s%s/" % (hashPath, folder)
else:
for imagePath in glob.glob("%s*%s" % (hashPath, ext)):
nameList.append(imagePath)
# if len(nameList) == 50000:
# break
if len(nameList) == 0:
print("Hash files count is empty")
else:
print("Files count: %d " % len(nameList))
event = threading.Event()
queueLock = threading.Lock()
workQueue = Queue.Queue(1000000)
threads = []
threadID = 1
# Create new threads
for tName in threadList:
thread = HashThread(threadID, tName, event, queueLock, workQueue,
kp, des, finds)
thread.daemon = True
thread.start()
threads.append(thread)
threadID += 1
# Fill the queue
queueLock.acquire()
for word in nameList:
workQueue.put(word)
queueLock.release()
# Wait for queue to empty
while not workQueue.empty():
pass
# Notify threads it's time to exit
event.set()
# Wait for all threads to complete
for t in threads:
t.join()
return finds
inpt = -1
while inpt != 0:
try:
inpt = int(raw_input(' 0 - exit \n 1 - check \n'))
except ValueError:
inpt = -1
continue
if inpt == 1:
try:
file_name = raw_input('Input filename: ')
except ValueError:
file_name = None
continue
img = im.loadImageFromPath('../images/%s' % file_name,
resize=True,
maxSize=800)
_kp, _des = sift.detectAndCompute(img, None)
kp, des = im.sortKp(_kp, _des, 200)
lock.acquire()
for t in tasks:
t.put(des)
lock.release()
pass
else:
pass
stopThreads(threads, event)
def loadFiles(filesInQueue=10000, hashPath=HASH_PATH, ext=DES_EXT):
def load_descriptors(bow, hashPath=HASH_PATH, withSubFolders=True, ext=DES_EXT):
des_list = []
kp_list = []
folder = 0
path = "%s%s/" % (hashPath, folder)
while os.path.exists(path):
for imagePath in glob.glob("%s*%s" % (path, '.des')):
des_list.append(imagePath)
kp_list.append('%s%s.kp' % (path, im.fileName(imagePath)))
if len(des_list) == FILES_CHECK:
folder = -2
break
folder += 1
path = "%s%s/" % (hashPath, folder)
if len(des_list) == 0:
print("Hash files count is empty")
return []
print("Files count: %d " % len(des_list))
for n in des_list:
bow.add(im.loadDesFromPath(n))
# bow.write(HASH_PATH + 'hash.bat')
print("Loaded")
images = []
for n in des_list:
images.append('http://comicstore.cf/uploads/diamonds/%s.jpg' % im.fileName(n))
return images, kp_list
flann = cv2.FlannBasedMatcher(index_params, search_params)
bow_train = cv2.BOWKMeansTrainer(50) # toy world, you want more.
bow_extract = cv2.BOWImgDescriptorExtractor(sift, flann)
images, kps = load_descriptors(bow_train)
print 'Getting cluster ...'
voc = bow_train.cluster()
print 'Set vocabulary ...'
bow_extract.setVocabulary(voc)
traindata, trainlabels = [], []
j = 0
for i in images:
img = im.loadImageFromUrl(i, resize=True, maxSize=800)
kp = im.loadKeypointFromPath(kps[j])
traindata.extend(bow_extract.compute(img, kp))
trainlabels.append(j)
j += 1
print 'Training SVM'
svm = cv2.ml.SVM_create()
svm.train(np.array(traindata), cv2.ml.ROW_SAMPLE, np.array(trainlabels))
img = im.loadImageFromPath('%s%s' % (IMG_PATH, 'M2.jpg'), resize=True, maxSize=800)
kp, des = im.keypointDesCalc(img, count=100)
fbow = bow_extract.compute(img, kp)
t_start = cv2.getTickCount()
p = svm.predict(fbow)
t_end = cv2.getTickCount()
print "Time match: %s" % ((t_end - t_start) / cv2.getTickFrequency())