def detect():
recognize()
#cv2.imshow("Face",img)
#if(cv2.waitKey(1) == ord('q')):
# break
#elif(userId != 0):
# cv2.waitKey(1000)
# cam.release()
# cv2.destroyAllWindows()
# return redirect('records/details/'+str(userId))
return redirect(url_for('index'))
def getVoiceKeyWord():
match = False
while match != True:
key = recognize('keyword')
t2s('you are want to find: {}'.format(key))
cf = recognize('YES or OK to confirm and NO to try again')
if cf in ['yes', 'ok', 'oke', 'đúng', 'phải', 'đồng ý']:
t2s('ok')
match = True
else:
t2s('oh sorry! please speech keyword again')
return key
def excCommand(self):
self.Pause()
command = listen_command()
if command == 0:
self.PlayPause()
elif command == 1:
self.Next()
elif command == 2:
self.Stop()
t2s("Phát lại")
elif command == 3:
self.VoiceSearch()
elif command == 4:
self.volUp()
t2s("đã tăng")
self.PlayPause()
elif command == 6:
self.volDown()
t2s("đã giảm")
self.PlayPause()
elif command == 5:
t2s('Bạn chắc chắn muốn thoát không')
t2s('Xác nhận bằng cách nói ok')
cf_exit = recognize('')
if cf_exit == 'yes' or cf_exit == 'ok' or cf_exit == 'oke':
t2s("Chào bạn hẹn gặp lại bạn hihi")
exit()
else:
print('no exit')
def t_recognize(img, c=0.3): # function to ocr images
save_ll = False
#print ('splitting...')
chars = dumb_split_plate(img)
if save_ll: # save pic
for char in chars:
cv2.imwrite('./ll/' + str(random.randint(0, 1000000)) + ".png",
char)
if not chars:
#print ('[main]:no chars')
return False, 0, 0
#print('[main]: returned chars:', len(chars))
if len(chars) > 1:
#print('processing...')
nums = process_number(chars)
else:
#print ('less than one char')
return False, 0, 0
if len(nums) > 1:
#print('recognizing...')
try:
t, conf = recognize(nums, c)
except:
#print('something went wrong')
return False, 0, 0
return t, conf, chars
return False, 0
def webcam():
models = load_models()
iteration = 0
cam = cv2.VideoCapture(0)
cv2.namedWindow('HackDrone', cv2.WND_PROP_FULLSCREEN)
cv2.setWindowProperty('HackDrone', cv2.WND_PROP_FULLSCREEN,
cv2.WINDOW_FULLSCREEN)
while True:
ret_val, image = cam.read()
if iteration > 5:
# RECOGNITION
print('Recognition')
result = recognize(image, models)
if result is not None:
letter, prob = result
text = 'Letter %s, confidence: %.2f' % (letter, prob)
cv2.putText(image, text, bottomLeftCornerOfText, font,
fontScale, fontColor, lineType)
cv2.imshow('HackDrone', image)
sleep(1)
iteration += 1
if cv2.waitKey(1) == 27:
break # esc to quit
cv2.destroyAllWindows()
def listen_command():
t2i_en = {
'play': 0,
'next': 1,
'stop': 2,
'search': 3,
'select song': 4,
'exit': 5
}
t2i_vn = {
'phát': 0,
'tiếp tục': 0,
'tiếp theo': 1,
'kế tiếp': 1,
'dừng lại': 2,
'tìm kiếm': 3,
'chọn bài hát': 4,
'chọn bài': 4,
'thoát': 5,
'thoát chương trình': 5
}
match = False
while match != True:
t2s('speech command')
text = recognize()
if text in t2i_en.keys() or text in t2i_vn.keys():
if text in t2i_en.keys():
command = t2i_en[text]
match = True
elif text in t2i_vn.keys():
command = t2i_vn[text]
match = True
return int(command)
def process_inputframes(frames_path, nth=1, duration=10):
frame_files = sorted(glob.glob(frames_path + '/*'))
num_frames = len(frame_files)
print(
'Detecting and recognizing text from {} frames for every {}th frame: {}'
.format(num_frames, nth, str(datetime.now())))
entries = []
for f_index, filename in tqdm(enumerate(frame_files), total=num_frames):
if (f_index % nth == 0):
boxes, scores = detection.detect(filename)
if scores.shape[0] != 0:
texts = recognition.recognize(filename, boxes)
for index, box in enumerate(boxes):
entry = {}
entry['f_index'] = f_index
entry['time_stamp'] = '{:2.2f}'.format(
f_index / num_frames * duration)
entry['text'] = texts[index]
entry['bbox'] = [
box[0], box[1], box[2] - box[0], box[3] - box[1]
]
entry['score'] = scores[index].item()
entries.append(entry)
return entries
def wav_to_text():
if request.method == 'POST':
wav_file = request.files['file']
wav_file.save('temp')
#Check if we have already translated, based on file hash
#Use a temp file and then destroy it
temp_file_obj = open('temp', 'rb')
file_hash = md5(temp_file_obj)
#If we dont find it, created
if not os.path.exists('./en_text_dir/' + file_hash):
#Turn the file to text
output_file = open(file_hash, 'w')
rec.recognize(open('temp', 'rb'), output_file)
#Move a saved copy to appropriate folder
os.rename(('./' + file_hash), ('./en_text_dir/' + file_hash))
#Delete the temp file
os.remove('temp')
return "Created"
else:
#Delete the temp file
os.remove('temp')
return "Already there"
elif request.method == 'GET':
wav_file = request.files['file']
#Check if we have already translated, based on file hash
file_hash = md5(wav_file)
if os.path.exists('./en_text_dir/' + file_hash):
return send_from_directory('./en_text_dir/',
file_hash,
as_attachment=True)
else:
return 'Not found', 404
def listen():
time.sleep(2)
while (True):
text = recognition.recognize().lower()
#text = input().lower()
print(text)
if (text is not ""):
parse_command(text)
def read_square():
while(not programEnd):
if(len(tasks)>0):
print("do new tasks, still have {} tasks left".format(len(tasks)))
current_task = tasks.pop()
print("task info:{}".format(current_task))
results.append(Results(current_task,recognition.recognize(current_task.frame,current_task.box, not usingPiCamera)))
time.sleep(.1)
def getVoiceKeyWord():
match = False
while True:
#sleep(1)
key = recognize('keyword')
#t2s('you are want to find: {}'.format(key))
if key != "error":
t2s("Có phải bạn muốn tìm kiếm {}".format(key))
cf = recognize('Nói OK hoặc Đồng ý để xác nhận')
else:
continue
if cf in ['yes', 'ok', 'oke', 'đúng', 'phải', 'đồng ý']:
t2s('Ok tìm kiếm cho {}'.format(key))
#match = True
break
#else:
#t2s('oh sorry! please speech keyword again')
return key
def on_message(client, userdata, msg):
# print("Data: " + str(msg.payload))
# print("Topic: " + msg.topic + "\n" +
# "Message: " + msg.payload.decode("utf-8"))
Save_power_Data(msg.payload) # save raw data samples
global data_accumulation, data_list
data_accumulation = data_accumulation + 1
if data_accumulation >= frame:
recognize(data_list) # run recognition function
data_accumulation = 0
data_list = []
else:
# 有時候下面這行 json_data = json.loads(msg.payload) 會出錯, 錯誤訊息如下
# raise JSONDecodeError("Expecting value", s, err.value) from None
# json.decoder.JSONDecodeError: Expecting value: line 1 column 54 (char 53)
try:
json_data = json.loads(msg.payload)
data_list.append([json_data['V'], json_data['A'], json_data['PF'],
json_data['W'], json_data['VA'], json_data['VAR']])
except Exception as e:
pass
def file_upload():
# convert request body to valid base64 string
encoded_image = request\
.data\
.decode()\
.replace('data:image/png;base64,', '')\
.replace(' ', '+')
# decode image content
content = base64.b64decode(encoded_image)
# create file buffer
tmp_file = io.BytesIO(content)
# send image to recognition
recognition_results = recognize(tmp_file)
# return JSON response
return jsonify(recognition_results)
def listen_command():
t2s('Bạn muốn tôi làm gì hãy ra lệnh cho tôi')
#t2s('Ví dụ tìm kiếm, kế tiếp, tiếp tục')
t2i_en = {
'play': 0,
'next': 1,
'replay': 2,
'search': 3,
'volume up': 4,
'volume down': 6,
'exit': 5
}
t2i_vn = {
'phát': 0,
'tiếp tục': 0,
'tiếp theo': 1,
'kế tiếp': 1,
'phát lại từ đầu': 2,
'phát lại': 2,
'nghe lại': 2,
'bắt đầu lại': 2,
'tìm kiếm': 3,
'tăng âm lượng': 4,
'tăng âm': 4,
"giảm âm lượng": 6,
"giảm âm": 6,
'thoát': 5,
'thoát chương trình': 5
}
match = False
while match != True:
t2s('Đọc lệnh bạn muốn')
text = recognize()
if text in t2i_en.keys() or text in t2i_vn.keys():
if text in t2i_en.keys():
command = t2i_en[text]
match = True
elif text in t2i_vn.keys():
command = t2i_vn[text]
match = True
return int(command)
def drop(event):
if event.data:
print('Dropped data:\n', event.data)
#print_event_info(event)
if event.widget == listbox:
files = listbox.tk.splitlist(event.data)
for f in files:
if os.path.exists(f):
print('Dropped file: "%s"' % f)
listbox.insert('end', f)
split_characters.Spliting(f)
result = recognition.recognize('./temp')
for item in result:
text.insert('end', item)
del_file('./temp/')
else:
print('Not dropping file "%s": file does not exist.' % f)
else:
print('Error: reported event.widget not known')
return event.data
def dronesign():
drone = tellopy.Tello()
try:
drone.connect()
drone.wait_for_connection(60.0)
drone.takeoff()
sleep(5)
drone.down(50)
sleep(5)
drone.start_video()
container = av.open(drone.get_video_stream())
for frame in container.decode(video=0):
image = cv2.cvtColor(numpy.array(frame.to_image()),
cv2.COLOR_RGB2BGR)
# RECOGNITION
print('Recognition')
result = recognize(image)
if result is not None:
letter, prob = result
text = 'Letter %s, confidence: %.2f' % (letter, prob)
print(text)
sleep(5)
stop = raw_input('Stop? [y]')
if stop.lower() == 'y':
break
sleep(5)
drone.land()
sleep(5)
except Exception as ex:
# exc_type, exc_value, exc_traceback = sys.exc_info()
# traceback.print_exception(exc_type, exc_value, exc_traceback)
print(ex)
finally:
drone.quit()
cv2.destroyAllWindows()
def excCommand(self):
self.Pause()
t2s('OK. Im here')
t2s('Please speech a command')
command = listen_command()
if command == 0:
self.PlayPause()
elif command == 1:
self.voiceNext()
elif command == 2:
self.Stop()
elif command == 3:
self.VoiceSearch()
elif command == 4:
self.voiceSelect()
elif command == 5:
t2s('You are sure to exit!')
t2s('Speech Yes or OK to comfirm!')
cf_exit = recognize('')
if cf_exit == 'yes' or cf_exit == 'ok' or cf_exit == 'oke':
exit()
else:
print('no exit')
def worker():
is_normal = True
while True:
item = q.get()
time.sleep(1)
text = recognize(item["file_path"], language="ja-JP")
add_log(item["file_name"], text)
if any(x in text for x in start_words):
i2c_motor_driver.start()
is_normal = True
elif any(x in text for x in stop_words):
i2c_motor_driver.stop()
elif any(x in text for x in reverse_words):
if is_normal:
i2c_motor_driver.reverse()
else:
i2c_motor_driver.start()
is_normal = not is_normal
elif any(x in text for x in accelerate_words):
i2c_motor_driver.accelerate()
elif any(x in text for x in decelerate_words):
i2c_motor_driver.decelerate()
q.task_done()
def infer_save_frames(input_frames_path, out_frames_path, every_nth=1):
frame_files = sorted(glob.glob(input_frames_path + '/*'))
num_frames = len(frame_files)
detect_time = 0
recognize_time = 0
print('Detecting and recognizing text from {} frames: {}'.format(
num_frames, str(datetime.now())))
wordBB = None
score = None
text = None
for index, filename in tqdm(enumerate(frame_files), total=num_frames):
out_name = out_frames_path + '/out_{0:04d}.png'.format(index)
if (index % every_nth == 0):
wordBB, score = detection.detect(filename)
if score.shape[0] == 0:
wordBB = None
score = None
else:
text = recognition.recognize(filename, wordBB)
utilities.save(filename, wordBB, text, out_name)
def select_by_speech():
t2i_en = {
'one': 1,
'two': 2,
'three': 3,
'four': 4,
'five': 5,
'six': 6,
'seven': 7,
'eight': 8,
'nine': 9,
'ten': 10
}
t2i_en2 = {
'number one': 1,
'number two': 2,
'number three': 3,
'number four': 4,
'number five': 5,
'number six': 6,
'number seven': 7,
'number eight': 8,
'number nine': 9,
'number ten': 10
}
t2i_vn = {
'một': 1,
'hai': 2,
'ba': 3,
'bốn': 4,
'năm': 5,
'sáu': 6,
'bẩy': 7,
'tám': 8,
'chín': 9,
'mười': 10
}
t2i_vn2 = {
'số 1': 1,
'số 2': 2,
'số 3': 3,
'số 4': 4,
'số 5': 5,
'số 6': 6,
'số 7': 7,
'số 8': 8,
'số 9': 9,
'số 10': 10
}
t2i = {
'1': 1,
'2': 2,
'3': 3,
'4': 4,
'5': 5,
'6': 6,
'7': 7,
'8': 8,
'9': 9,
'10': 10
}
match = False
while match != True:
t2s('select song')
text = recognize()
if text in t2i_en.keys() or text in t2i_en2.keys(
) or text in t2i_vn.keys() or t2i_vn2.keys() or text in t2i.keys():
if text in t2i_en.keys():
number = t2i_en[text]
match = True
elif text in t2i_en2.keys():
number = t2i_en2[text]
match = True
elif text in t2i_vn.keys():
number = t2i_vn[text]
match = True
elif text in t2i_vn2.keys():
number = t2i_vn2[text]
match = True
elif text in t2i.keys():
number = t2i[text]
match = True
return int(number) - 1
def worker():
while True:
item = q.get()
text = recognize(item["file_path"], language="ja-JP")
add_log(item["file_name"], text)
q.task_done()
def recognize(self):
if self.img_path is None:
pass
r_char = recognize(self.config, self.img_path)
self.tbRecognitionResult.setText(r_char)
voice = browser.find_elements_by_tag_name("iframe")[2]
browser.switch_to.frame(voice)
time.sleep(2)
download = browser.find_element_by_css_selector('.rc-audiochallenge-tdownload-link')
download.send_keys(Keys.ENTER)
time.sleep(15)
convert()
recognize()
result = browser.find_element_by_css_selector('#audio-response')
result.send_keys(recognize.text , Keys.ENTER)
time.sleep(15)
while "iframe" in browser.page_source:
download = browser.find_element_by_css_selector('.rc-audiochallenge-tdownload-link')
download.send_keys(Keys.ENTER)
time.sleep(15)
convert()
recognize()
def segFun(heighty, widthx, img):
import numpy as np
import image as img1
import cv2 as cv
import recognition as rg
c = []
i = 0
flag_dot = 0
flag_dots = 0
i_low = 0
i_high = 0
j_left = 0
j_right = 0
i_nhigh = 0
i_nlow = 0
iscount = 0
while (i <= heighty - 1):
count_dot = 0
for j in range(0, widthx - 1):
avalue = np.mean(img[i, j])
if (avalue == 0):
count_dot = count_dot + 1
if count_dot >= 4:
if flag_dot == 0:
flag_dot = 1
i_high = i - 1
else:
if flag_dot == 1:
flag_dot = 0
i_low = i
else:
flag_dot = 0
if ((i_low != 0) & (i_high != 0)):
flag_dots = 0
for line_j in range(0, widthx - 1):
lj = line_j
count_cr = 0
for line_i in range(i_high, i_low):
avalue1 = np.mean(img[line_i, line_j])
if (avalue1 == 0):
count_cr = count_cr + 1
if count_cr >= 1:
if flag_dots == 0:
flag_dots = 1
j_left = line_j - 1
else:
if flag_dots == 1:
flag_dots = 0
j_right = line_j
else:
flag_dots = 0
if ((j_left != 0) & (j_right != 0)):
flag_dotd = 0
for v_i in range(i_high, i_low + 1):
count_cv = 0
for h_j in range(j_left, j_right + 1):
avalue2 = np.mean(img[v_i, h_j])
if (avalue2 == 0):
count_cv = count_cv + 1
if count_cv >= 1:
if flag_dotd == 0:
flag_dotd = 1
i_nhigh = v_i
for drawn_j in range(j_left, j_right + 1):
img[v_i - 1, drawn_j, 2] = 255
img[v_i - 1, drawn_j, 1] = 0
img[v_i - 1, drawn_j, 0] = 0
else:
img[v_i - 1, j_left, 2] = 255
img[v_i - 1, j_left, 1] = 0
img[v_i - 1, j_left, 0] = 0
img[v_i - 1, j_right, 2] = 255
img[v_i - 1, j_right, 1] = 0
img[v_i - 1, j_right, 0] = 0
else:
if flag_dotd == 1:
flag_dotd = 0
i_nlow = v_i
for drawn_j in range(j_left, j_right + 1):
img[v_i, drawn_j, 2] = 255
img[v_i, drawn_j, 1] = 0
img[v_i, drawn_j, 0] = 0
img[v_i - 1, j_left, 2] = 255
img[v_i - 1, j_left, 1] = 0
img[v_i - 1, j_left, 0] = 0
img[v_i - 1, j_right, 2] = 255
img[v_i - 1, j_right, 1] = 0
img[v_i - 1, j_right, 0] = 0
#newly added
hs = i_nlow - i_nhigh
ws = j_right - j_left
img1 = np.zeros((hs, ws, 3), np.uint8)
img1[:] = (255, 255, 255)
for i_s in range(1, hs):
for j_s in range(1, ws):
img1[i_s, j_s] = img[i_nhigh + i_s, j_left + j_s]
#cv.imshow("demos(%d)"%iscount,img1)
# print(img1.shape)
img2 = cv.resize(img1, (32, 32),
interpolation=cv.INTER_CUBIC)
c.append(rg.recognize(img2))
#********
j_right = 0
j_left = 0
i_high = 0
i_low = 0
i = i + 1
return (c)
def check_party_affiliation():
json_obj = request.get_json(force=True)
result = recognition.recognize(json_obj['query'].lower().split())
obj = { 'response': result }
return make_my_response(obj)
digits_dir = argv[1]
gt_filename = argv[2]
digit_templates = []
for i in range(0, 10):
digit_templates.append(generate_template(digits_dir + '/' + str(i)))
gt = []
filenames = []
for line in open(gt_filename).readlines():
(filename, label) = line.rstrip().split(' ')
filenames.append(filename)
gt.append((int(label[0]), int(label[1]), int(label[2])))
testing_path = dirname(gt_filename)
accuracy = 0
for i, filename in enumerate(filenames):
img = imread(testing_path + '/' + filename)
digits = recognize(img, digit_templates)
if digits == gt[i]:
accuracy += 1
accuracy /= float(len(filenames))
stdout.write('%1.2f\n' % accuracy)
captchaFailed = True
loggedIn = False
while captchaFailed:
print('getting CAPTCHA...')
f = explorer.open(
urllib.request.Request(url=baseURL + '/INC/VerifyCode.aspx',
headers=generalHeaders))
captchabin = f.read()
myfile = open('./tmp.jpg', 'wb')
myfile.write(captchabin)
myfile.flush()
myfile.close()
print('recognizing CAPTCHA...')
captcha = r.recognize('./tmp.jpg')
print('CAPTCHA was recognized: ' + captcha)
print('trying to login...')
logindata = {'title': 'login', 'yzm': captcha}
logindata.update(loginInfo)
f = explorer.open(
urllib.request.Request(url=baseURL + '/ashx/ajaxHandler.ashx',
headers=generalHeaders,
data=bytes(urllib.parse.urlencode(logindata),
encoding='utf-8')))
rtn = json.loads(str(f.read(), encoding='utf-8'))
if (rtn['status'] == 'failed'):
if (rtn['des'] == '验证码输入错误！'):
print('CAPTCHA is wrong, try again!')
# Associação da aplicacao com a porta especificada
s.bind((TCP_IP, TCP_PORT))
print("Associacao feita com sucesso")
# Escuta iniciada para novas conexoes
s.listen(1)
print("Escutando na porta ", TCP_PORT)
# Aprovacao da conexao
conn, addr = s.accept()
print('Endereço da conexão:', addr)
# A unica conexao fica aberta por tempo indefinido (ou ate o aparelho ser desligado)
while 1:
# Recebe o dado do arduino
data = conn.recv(BUFFER_SIZE)
if not data: break
print("Dado recebido:", data)
# Executa identificacao de conteudo
ans = recognition.recognize(data)
# Responde se o aparelho deve ou nao desligar
if ans:
conn.send(False)
else:
conn.send(True)
# Fecha conexao
conn.close()
import recognition as r import sys filename = sys.argv[1] print(r.recognize(filename))
import cv2
import numpy as np
from os import system
parser = argparse.ArgumentParser()
parser.add_argument("echo")
args = parser.parse_args()
img = cv2.imread(args.echo)
net, sess = detection.detectorload()
model, converter = recognition.crnnloader()
cropedimage = detection.ctpn(sess, net, img, 1)
print("\n" * 50)
text = []
print(len(cropedimage))
for image in cropedimage:
buf = cv2.resize(image.copy(),
(int(image.shape[1] * 2), int(image.shape[0] * 2)))
image = cv2.cvtColor(image, cv2.COLOR_RGB2GRAY)
text_sim, cost = recognition.recognize(model, converter, image)
print('Text: ' + text_sim)
print(' Recognition Time: ' + str(np.round(cost, 4)))
print("\n")
text.append(text_sim)
cv2.imshow('My window', buf)
cv2.waitKey(50)
system('say ' + text_sim)
cv2.waitKey(2500)
def select_by_speech():
t2i_en = {
'one': 1,
'two': 2,
'three': 3,
'four': 4,
'five': 5,
'six': 6,
'seven': 7,
'eight': 8,
'nine': 9,
'ten': 10
}
t2i_en2 = {
'number one': 1,
'number two': 2,
'number three': 3,
'number four': 4,
'number five': 5,
'number six': 6,
'number seven': 7,
'number eight': 8,
'number nine': 9,
'number ten': 10
}
t2i_vn = {
'một': 1,
'hai': 2,
'ba': 3,
'bốn': 4,
'năm': 5,
'sáu': 6,
'bẩy': 7,
'tám': 8,
'chín': 9,
'mười': 10
}
t2i_vn2 = {
'số 1': 1,
'số 2': 2,
'số 3': 3,
'số 4': 4,
'số 5': 5,
'số 6': 6,
'số 7': 7,
'số 8': 8,
'số 9': 9,
'số 10': 10
}
t2i = {
'1': 1,
'2': 2,
'3': 3,
'4': 4,
'5': 5,
'6': 6,
'7': 7,
'8': 8,
'9': 9,
'10': 10
}
match = False
firttime = True
while match != True:
if firttime:
t2s('Mời bạn chọn bài hát bằng cách nói số thứ tự bài')
firttime = False
else:
t2s("Tôi chưa hiểu hãy thử lại")
text = recognize()
if text in t2i_en.keys() or text in t2i_en2.keys(
) or text in t2i_vn.keys() or t2i_vn2.keys() or text in t2i.keys():
if text in t2i_en.keys():
number = t2i_en[text]
match = True
break
elif text in t2i_en2.keys():
number = t2i_en2[text]
match = True
break
elif text in t2i_vn.keys():
number = t2i_vn[text]
match = True
break
elif text in t2i_vn2.keys():
number = t2i_vn2[text]
match = True
break
elif text in t2i.keys():
number = t2i[text]
match = True
break
# mặc định trả về 0 nếu không nhận dạng được, nếu không mặc định
# thì hỏi đến lúc nhận dạng đúng
#else:
#match = True
#number = 1
#break
return int(number) - 1