def spoken_term_detection_truncated(keywords, utterances, left_encode_num,
right_encode_num, distance_type,
output_dir):
for i in range(len(keywords)):
keyword_sampling_feature = keywords[i].sampling_feature
keyword_phone_num = keyword_sampling_feature.shape[0]
(left_position,
right_position) = get_truncated_position(keyword_phone_num,
left_encode_num,
right_encode_num)
keyword_indexes_selected = get_real_indexes(range(keyword_phone_num),
left_encode_num,
right_encode_num)
keyword_sampling_feature_selected = keyword_sampling_feature[
keyword_indexes_selected, :]
output_file = output_dir + keywords[i].getFileId() + ".result"
fid = open(output_file, "w")
for j in range(len(utterances)):
utterance_sampling_feature = utterances[j].sampling_feature
utterance_phone_num = utterance_sampling_feature.shape[0]
utterance_indexes_selected = get_real_indexes(
range(utterance_phone_num), left_encode_num, right_encode_num)
utterance_sampling_feature_selected = utterance_sampling_feature[
utterance_indexes_selected, :]
distance = Distance.distance(
keyword_sampling_feature_selected[:, left_position:
right_position],
utterance_sampling_feature_selected[:, left_position:
right_position],
distance_type,
sub_num=PHONE_LEN)
fid.writelines(str(-distance.min()) + "\n")
fid.close()
log.Log("finished the std for keyword " + str(keywords[i].getFileId()))\
def has_distance(text):
if Distance.isOpen:
Distance.isOpen = False
return "你距离我 %s" % Distance.distance("上海市长宁区凯利大厦", text)
elif text in ['你在哪', '离我多远', '距离']:
Distance.isOpen = True
return Distance.HELP_MSG
else:
return has_weather(text)
def search(img_path):
cf = CaculateColorVector.get_color_feature(img_path)
cfs = File_Operation.read_list_from_file('/Users/ligang/Documents/cfs.txt')
distances = []
for cf_tuple in cfs:
d = Distance.distance(cf, cf_tuple[1])
distances.append((cf_tuple[0], d))
top_distances = heapq.nsmallest(10, distances, key=lambda x: x[1])
print top_distances
def search(img_path):
ulbp_f = ulbp.ulbp(img_path)
ulbps = File_Operation.read_list_from_file('/Users/ligang/Documents/ulbp.txt')
distances = []
for ulbp_tuple in ulbps:
d = Distance.distance(ulbp_f, ulbp_tuple[1])
distances.append((ulbp_tuple[0], d))
top_distances = heapq.nsmallest(20, distances, key=lambda x: x[1])
dstDir = '/Users/ligang/Documents/Emilie/lbp_search_result'
img_set_dir = '/Users/ligang/Documents/Emilie/dress'
for top in top_distances:
shutil.copy2(os.path.join(img_set_dir, top[0]), os.path.join(dstDir, top[0]))
print top_distances
def search(img_path):
cf = CaculateColorVector.get_color_feature(img_path)
unlbp_feature = Uniform_LBP.ulbp(img_path)
cfs = File_Operation.read_list_from_file('/Users/ligang/Documents/cfs.txt')
ulbps = File_Operation.read_list_from_file('/Users/ligang/Documents/ulbp.txt')
distances = []
for cf_tuple, ulbp_tuple in zip(cfs, ulbps):
assert cf_tuple[0] == ulbp_tuple[0]
d_color = Distance.distance(cf, cf_tuple[1])
d_ulbp = Distance.distance(unlbp_feature, ulbp_tuple[1])
d = d_color + d_ulbp
distances.append((cf_tuple[0], d))
top_distances = heapq.nsmallest(20, distances, key=lambda x: x[1])
dstDir = '/Users/ligang/Documents/Emilie/colorlbp_search_result'
img_set_dir = '/Users/ligang/Documents/Emilie/dress'
for top in top_distances:
shutil.copy2(os.path.join(img_set_dir, top[0]), os.path.join(dstDir, top[0]))
print top_distances
def __init__(self):
self.__img = Image.image()
self.__greenFinder = GreenFinder.greenFinder()
self.__dist = Distance.distance()
self.__targetAngle = TargetAngle.targetAngle()
def detect_QR_code(camera, PBR):
print "QR code reading"
# PBR.SetMotor1(0.2)
# PBR.SetMotor2(-0.2)
time.sleep(0.1)
done = False
count = 0
while count < 8 and not done:
print "not done"
rawCapture = PiRGBArray(camera)
# grab an image from the camera
camera.capture(rawCapture, format="bgr")
image = rawCapture.array
try:
dist = Distance.distance(image)
except:
return False
print "dist" + str(dist)
if dist > 24:
return False
if dist > 12:
PBR.SetMotor1(0.2)
PBR.SetMotor2(-0.2)
time.sleep(0.01 * (dist - 6))
continue
elif dist < 6:
PBR.SetMotor1(-0.2)
PBR.SetMotor2(0.2)
time.sleep(0.01 * (6 - dist))
continue
count += 1
# cv2.imshow("rect",image)
img = image
#show the image
#wait until some key is pressed to procced
image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
edges = cv2.Canny(image, 100, 200)
# cv2.imshow("edges", edges)
# key = cv2.waitKey(1) & 0xFF
contours, hierarchy = cv2.findContours(edges, cv2.RETR_TREE,
cv2.CHAIN_APPROX_SIMPLE)
cv2.drawContours(image, contours, -1, (0, 255, 0), 3)
mu = []
mc = []
mark = 0
for x in range(0, len(contours)):
mu.append(cv2.moments(contours[x]))
for m in mu:
if m['m00'] != 0:
mc.append((m['m10'] / m['m00'], m['m01'] / m['m00']))
else:
mc.append((0, 0))
# print hierarchy[0]
# print(len(contours))
for x in range(0, len(contours)):
# print "x"+str(int(mc[x][0]))+" "+str(int(mc[x][1]))
k = x
c = 0
while (hierarchy[0][k][2] != -1):
k = hierarchy[0][k][2]
c = c + 1
if hierarchy[0][k][2] != -1:
c = c + 1
# print str(c )
if c >= 5:
if mark == 0:
A = x
elif mark == 1:
B = x
elif mark == 2:
C = x
mark = mark + 1
# break
# print "mark"+str(mark)
# print str(mc[A])
# if mark == 1:
# cv2.circle(image,( int(mc[A][0]),int(mc[A][1])), 5, ( 110, 220, 0 ), -1)
# elif mark == 2:
# cv2.circle(image,( int(mc[A][0]),int(mc[A][1])), 5, ( 110, 220, 0 ), -1)
# cv2.circle(image,( int(mc[B][0]),int(mc[B][1])), 5, ( 110, 220, 0 ), -1)
# elif mark == 3:
# cv2.circle(image,( int(mc[A][0]),int(mc[A][1])), 5, ( 110, 220, 0 ), -1)
# cv2.circle(image,( int(mc[B][0]),int(mc[B][1])), 5, ( 110, 220, 0 ), -1)
# cv2.circle(image,( int(mc[C][0]),int(mc[C][1])), 5, ( 110, 220, 0 ), -1)
# cv2.imshow("BW_image", image)
if mark > 2:
AB = distance(mc[A], mc[B])
BC = distance(mc[B], mc[C])
AC = distance(mc[A], mc[C])
if (AB > BC and AB > AC):
outlier = C
median1 = A
median2 = B
elif (AC > AB and AC > BC):
outlier = B
median1 = A
median2 = C
elif (BC > AB and BC > AC):
outlier = A
median1 = B
median2 = C
top = outlier
dist = lineEquation(mc[median1], mc[median2], mc[outlier])
slope, align = lineSlope(mc[median1], mc[median2])
if align == 0:
bottom = median1
right = median2
elif (slope < 0 and dist < 0):
bottom = median1
right = median2
orientation = 0
elif (slope > 0 and dist < 0):
right = median1
bottom = median2
orientation = 1
elif (slope < 0 and dist > 0):
right = median1
bottom = median2
orientation = 2
elif (slope > 0 and dist > 0):
bottom = median1
right = median2
orientation = 3
areatop = 0.0
arearight = 0.0
areabottom = 0.0
# print "top"+str(top)
# print "right"+str(right)
# print "bottom"+str(bottom)
# print "cv2.contourArea(contours[top]) "+str(cv2.contourArea(contours[top]) )
# print "cv2.contourArea(contours[right]) "+str(cv2.contourArea(contours[right]) )
# print "cv2.contourArea(contours[bottom]) "+str(cv2.contourArea(contours[bottom]) )
if (top < len(contours) and right < len(contours)
and bottom < len(contours)
and cv2.contourArea(contours[top]) > 10
and cv2.contourArea(contours[right]) > 10
and cv2.contourArea(contours[bottom]) > 10):
tempL = []
tempM = []
tempO = []
src = []
dst = []
N = (0, 0)
tempL = getVertices(contours, top, slope, tempL)
tempM = getVertices(contours, right, slope, tempM)
tempO = getVertices(contours, bottom, slope, tempO)
L = updateCornerOr(orientation, tempL)
M = updateCornerOr(orientation, tempM)
O = updateCornerOr(orientation, tempO)
qr = np.zeros((100, 100))
iflag, N = getIntersection(M[1], M[2], O[3], O[2], N)
src.append(L[0])
src.append(M[1])
src.append(N)
src.append(O[3])
src = np.asarray(src, np.float32)
dst.append((0, 0))
dst.append((100, 0))
dst.append((100, 100))
dst.append((0, 100))
dst = np.asarray(dst, np.float32)
warp_matrix = cv2.getPerspectiveTransform(src, dst)
warped = cv2.warpPerspective(img, warp_matrix, (100, 100))
# cv2.imshow("warped",warped)
cv2.circle(img, N, 1, (0, 0, 255), 2)
cv2.drawContours(img, contours, top, (255, 0, 0), 2)
cv2.drawContours(img, contours, right, (0, 255, 0), 2)
cv2.drawContours(img, contours, bottom, (0, 0, 255), 2)
warped = cv2.cvtColor(warped, cv2.COLOR_BGR2GRAY)
scanner = zbar.ImageScanner()
scanner.parse_config('enable')
imagez = zbar.Image(warped.shape[0], warped.shape[1], 'Y800',
warped.tostring())
scanner.scan(imagez)
for symbol in imagez:
x = symbol.data
print "------------------------------" + x + "------------------------------"
message = x
if message == "Stop 5 min":
Move.bypass(PBR)
elif message == "Spin 1 circle": #right
Move.turn_right(45, PBR)
return True
