def ILEloop(R, A, structure, is_print=True):
cnt = 1
total_strong_connected_ls = []
altR, structure, StrProgress, strong_connected_ls = identify_level_elements(
R, A, structure, is_print)
S = len(altR)
strS = str(S)
if strong_connected_ls:
total_strong_connected_ls.append(strong_connected_ls)
while StrProgress < S:
if cnt > 50:
p('error cnt over', is_print=is_print)
return structure.append('ERR')
else:
p('continue... progress >> ',
StrProgress,
'/',
strS,
' cnt',
cnt,
is_print=is_print)
cnt += 1
altR, structure, StrProgress, strong_connected_ls = identify_level_elements(
altR, A, structure, is_print)
if strong_connected_ls:
total_strong_connected_ls.append(strong_connected_ls)
else:
p('Finished !! ', StrProgress, '/', strS, is_print=is_print)
p('strong-connect-pair: ', total_strong_connected_ls)
p(structure)
return structure
def extract_face(faces, i):
#(四角の左上のx座標, 四角の左上のy座標, 四角の横の長さ, 四角の縦の長さ)
pos = faces[i]
bottom = pos[1]+pos[3]
right = pos[0]+pos[2]
if not (pos[1] < 0 or right > height or pos[0] < 0 or bottom > width):
cvimg = original_cvimg
result_dic['extracted'] = {}
result_dic['extracted'][i] = {}
pos_dic = {}
pos_dic['left'] = int(pos[0])
pos_dic['top'] = int(pos[1])
pos_dic['bottom'] = int(bottom)
pos_dic['right'] = int(right)
pos_dic['height'] = int(pos[2])
pos_dic['width'] = int(pos[3])
result_dic['extracted'][i]['pos'] = pos_dic
face_icon = cvimg[pos_dic['top']: pos_dic['bottom'], pos_dic['left']: pos_dic['right']]
if not frame_setting is None:
framed_cvimg = frame_image(cvimg, pos = result_dic['extracted'][i]['pos'],frame_setting = frame_setting)
show_image(framed_cvimg, filename = '')
json = {}
json['pos'] = result_dic['extracted'][i]['pos']
p(json)
result_dic['extracted'][i]['icon_cvimg'] = face_icon
result_dic['extracted'][i]['icon_id'] = save_image_sql(cvimg = face_icon, filename = ''.join([str(_id), '_icon', str(i)]), url = _id, owner = None, json = json, compression_quality = 70, compression_format = 'jpg')
is_show = False
if is_show:
show_image(face_icon, filename = result_dic[i]['icon_id'])
def get_googlemap(url = 'https://notendur.hi.is/~sfg6/google_maps_example/'):
USER_AGENT = {'User-Agent': 'Mozilla/5.0'} #Needed to prevent 403 error
phantomjs_path = '/usr/local/bin/phantomjs'
driver = webdriver.PhantomJS(executable_path=phantomjs_path, service_log_path=os.path.devnull, desired_capabilities={'phantomjs.page.settings.userAgent':USER_AGENT})
# get a HTML response
driver.set_window_size(1280, 800)
driver.get(url)
html = driver.page_source.encode('utf-8') # more sophisticated methods may be available
soup = bs4.BeautifulSoup(html, 'lxml')
p(soup)
time.sleep(5)
driver.save_screenshot('test_google_maps_api_screenshot.png')
def get_dl_links(url = "https://www.jstage.jst.go.jp/browse/jspa1962/-char/ja/", extention = 'pdf', except_str = 'pub', DIR = DATADIR, sleep_time = 1):
abs_filename_ls = []
try:
soup = get_bs4soup(url)
links = soup.findAll('a')
download_urls = [href for href in [link.get('href') for link in links] if href and extention in href and not except_str in href]
BASE_URL = '/'.join(url.split('/')[:3])
downloads_cnt = len(download_urls)
error_cnt = 0
p(''.join([str(downloads_cnt), '件のファイルをダウンロードします。']))
for i in range(downloads_cnt):
time.sleep(sleep_time)
try:
target_url = ''.join([BASE_URL, download_urls[i]])
p(target_url)
filename = '.'.join([target_url.split('/')[-2], extention])
abs_filename_ls.append(_.download_file(url = target_url, DIR = DIR, filename = filename))
except:
error_cnt += 1
pass
p(''.join(['COMPLETE:', str(i-error_cnt+1), '/', str(downloads_cnt), '\tERR:', str(error_cnt)]))
return abs_filename_ls
except Exception as e:
p(e)
return abs_filename_ls
def get_listmembers_all(self, username, listname):
try:
return [
UserObject.screen_name for UserObject in tweepy.Cursor(
self.twtr_api.list_members, username, listname).items()
]
except tweepy.error.TweepError as e:
if e.api_code == '34':
if username == self.bot_id:
p(listname, 'MAKE the LIST!!')
# self.is_create_list_success(name = listname)
return []
except:
return []
def extract_ss(url = 'http://www.lovelive-ss.com/?p={}'):
soup = get_bs4soup(url)
title = soup.find('h1', class_="entry-title")
if title is None:
return None
else:
p(title.get_text(), url)
try:
ss_contents = soup.find("div", class_ = "entry-content").find_all("dd", class_ ="t_b")
except:
return None
def op_soup(content):
a_conts = content.find_all('a')
[a_cont.extract() for a_cont in a_conts if not a_cont is None]
return content.get_text()
s_ls = [op_soup(ss_content) for ss_content in ss_contents]
return s_ls
def user_stream(self, srf, q, lock, events):
# _.reconnect_wifi()
p('start user_stream')
auth = self.twtr_auth
stream = tweepy.Stream(auth=auth,
listener=StreamListener(srf, q, lock, events),
async=False,
timeout=180)
stream.userstream(stall_warnings=True,
_with=None,
replies=None,
track=None,
locations=None,
encoding='utf8',
async=True)
p('waiting stop event')
events.stop.wait()
p('stopping user_stream')
stream.running = False
def on_limit(self, track):
p(self.bot_id, 'track', track)
return True
def keep_alive(self):
p(self.bot_id, 'keep_alive...')
self.events.ping.set()
return True
def __del__(self):
p(self.bot_id, 'stopping streaming...')
def on_timeout(self):
p('timeout...')
return False
def simplifyC(
text='S1→S5\nS2→S1\nS2→S3\nS2→S4\nS3→S5\nS3→S4\nS4→S3\nS6→S2\nS6→S5',
arrow='→',
is_print=True):
chunk = text.split('\n')
pairs = [arg.split(arrow) for arg in chunk]
words = list(chain.from_iterable(pairs))
# print(words)
factors = f7(words)
factors_cnt = len(factors)
p('抽出された要素は以下の通りです。', is_print=is_print)
p(factors, is_print=is_print)
z = np.zeros((factors_cnt, factors_cnt))
I = np.identity(factors_cnt)
causels = [pair[0] for pair in pairs]
effectls = [pair[1] for pair in pairs]
causeN = [factors.index(cause) for cause in causels]
effectN = [factors.index(effect) for effect in effectls]
z[causeN, effectN] = 1
adjacency_matrix = z
reach_ability_matrix = adjacency_matrix + I
# Identifying process of the 1st level lements
R = []
A = []
p('boolean演算を実行します。', is_print=is_print)
RAM = prd_boolen_matrix(reach_ability_matrix)
p('boolにおいて(A+I)^r = (A+I)^(r+1) /= A+I \nとなる可到達行列は以下のとおりです。',
is_print=is_print)
p(RAM, is_print=is_print)
for Si in range(factors_cnt):
Ai = RAM[:, Si]
Ri = RAM[Si]
A.append(npwhere(Ai))
R.append(npwhere(Ri))
p('行列から抽出した集合は以下のとおりです。', is_print=is_print)
p('A', is_print=is_print)
p(A, is_print=is_print)
p('R', is_print=is_print)
p(R, is_print=is_print)
structure = []
Level = []
structure = ILEloop(R, A, structure, is_print=is_print)
p(structure, is_print=is_print)
structureName = []
p('++++result structure is as following !!++++', is_print=is_print)
ans_ls = []
ans_ls.append('######EFFECT######')
for level in structure:
level_name = []
for num in level:
level_name.append(factors[num])
ans_ls.append('↑↑↑↑↑↑↑')
[ans_ls.append(name) for name in level_name]
structureName.append(level_name)
ans_ls.append('######CAUSE######')
ans = '\n'.join(ans_ls)
p(ans)
return structureName, structure
def on_error(self, status_code):
p(status_code, 'cannot get')
return False
def on_warning(self, notice):
p(notice, 'warning')
return True
def identify_level_elements(R, A, structure, is_print):
# dirtyCode... リスト内包表記で要修正
p('~~~~~~~~~~~~~~~~~~~~~~~~~~~', is_print=is_print)
S = len(R)
strS = str(S)
Level = []
structureN = []
RcapA = calcRcapA(R, A, S)
p('RcapA', is_print=is_print)
p(RcapA, is_print=is_print)
for i in range(S):
Ri = R[i]
RiAi = RcapA[i]
if RiAi == Ri:
Level.append(Ri)
if Ri:
structureN.append(i)
# try:
altR = []
p('Level', is_print=is_print)
Level = [level for level in Level if level]
p(Level, is_print=is_print)
p('structureN', is_print=is_print)
p(structureN, is_print=is_print)
avoidLevel = flatten(Level)
strong_connected_ls = []
# check discrete or not
if len(Level) != 1:
p('parallel cause-effect... ', is_print=is_print)
for level in Level:
if len(level) > 1:
p(level,
' Not Discrete, Strongly connected...',
is_print=is_print)
strong_connected_ls.append(level)
Level.remove(level)
for i in range(S):
Ri = R[i]
altRi = [r for r in Ri if r not in avoidLevel]
altR.append(altRi)
p('altR', is_print=is_print)
p(altR, is_print=is_print)
structure.append(structureN)
structure = [structure for structure in structure if structure != []]
p('whole_structure', is_print=is_print)
p(structure, is_print=is_print)
StrProgress = len(flatten(structure))
return altR, structure, StrProgress, strong_connected_ls
# import urllib.parse # urlencode
# import http
# import http.cookiejar
# opener = urllib.request.build_opener(urllib.request.HTTPCookieProcessor(http.cookiejar.CookieJar()))
USER_AGENT = {'User-Agent': 'Mozilla/5.0'} #Needed to prevent 403 error
phantomjs_path = '/usr/local/bin/phantomjs'
login_url = 'https://mobile.twitter.com/session/new'
# img_url = 'https://twitter.com/messages/media/772747782637563907'
img_url = 'https://ton.twitter.com/1.1/ton/data/dm/772785678509760515/772785678547423232/iEUEceDa.jpg'
driver = webdriver.PhantomJS(executable_path=phantomjs_path, service_log_path=os.path.devnull, desired_capabilities={'phantomjs.page.settings.userAgent':USER_AGENT})
driver.get(img_url)
try:
loginid = driver.find_element_by_id('session[username_or_email]')
except:
p('log-in')
tw_id, tw_pw = 'LiveAI_Rin','705216130'
driver.get(login_url) # ログインページを開く
html = driver.page_source.encode('utf-8')
loginid = driver.find_element_by_id('session[username_or_email]')
password = driver.find_element_by_id('session[password]')
loginid.send_keys(tw_id)
password.send_keys(tw_pw)
driver.find_element_by_name('commit').click()
driver.get(img_url)
time.sleep(1)
driver.save_screenshot('DMimg.png')
driver.quit()
# p(search_weblioEJJE(word = 'some'))
# range(4538, 8000):
# reg = natural_language_processing.RegexTools()
Bannerfilename=user.abs_banner_filename)
return True
except Exception as e:
_.log_err()
return False
if __name__ == '__main__':
twf = TwtrTools('LiveAI_Hanamaru')
# twf.send(ans = '書込凍結のbotを捜索中(表示が出てれば無事です)', screen_name = 'LiveAI_Alpaca', mode = 'tweet')
# twf.update_profile(name = '実験垢@', description='', location='', url = '', filename = '', BGfilename = '', Bannerfilename = '')
# twf.imitate('LiveAI_Umi')
# p()
set_time = datetime.now(JST).strftime('%Y%m%d%H%M%S')
p(set_time.strftime('%Y%m%d%H%M%S'))
# st = twf.send(ans = 'test23', screen_name = 'kaihatsu_paka', mode = 'tweet')
# if st:
# p(st.id_str)
# user = twf.get_userinfo(screen_name = 'kaihatsu_paka')
# p(user)
# user.name
# user_id = user.id_str
#'id': 768871329332203522,
# a = twf.twtr_api.me()
# a = twf.twtr_api.get_user(screen_name = 'LiveAI_Umi')
# a = operate_sql.BotProfile()
# p(a.location)
# p(a.__dict__)
# p(hasattr( a, 'name'))
# objs = twf.get_followers_all('LiveAI_Maki')
def srtr(self):
s = self.s
status = ''
ans = ''
last = ''
answord = ''
wordsList = []
kanasList = []
wordsList = self.srtrdb.word_stream.split('<JOIN>')
kanasList = self.srtrdb.kana_stream.split('<JOIN>')
self.game_mode = self.srtrdb.mode
self.time = self.srtrdb.tmp_time
self.len_rule = self.srtrdb.len_rule
if any(
[rev_srtr in s for rev_srtr in ['逆しりとり', '頭取り', 'あたまとり', 'あたま取']]):
self.game_mode = 'reverse'
self.event = 'restart'
elif 'しりとり' in s:
self.game_mode = 'normal'
self.event = 'restart'
else:
pass
turncnt = len(wordsList)
# TODO]アポストロフィに無理やり対応(すごい例外)
s = s.replace('海未', '園田海未')
if "μ's" in s:
rawnoun = "μ's"
kana = 'ミューズ'
else:
rawNouns = natural_language_processing.MA.get_mecab(
s,
form=['名詞'],
exception={'数', '接尾', '非自立', '接続助詞', '格助詞', '代名詞'})
kanaNouns = natural_language_processing.MA.get_mecab(
s,
mode=8,
form=['名詞'],
exception={'数', '接尾', '非自立', '接続助詞', '格助詞', '代名詞'})
if not rawNouns:
status = 'alert_nonoun'
else:
rawnoun = rawNouns[0]
kana = kanaNouns[0]
if kana == '*':
status = 'alert_nonoun'
if not status:
try:
cleaned_noun = re.sub(re.compile('[!-@[-`{-~]'), '', kana)
gobi = cleaned_noun[-1:]
if gobi == 'ー':
gobi = cleaned_noun.replace('ー', '')[-1:]
gotou = cleaned_noun[:1]
gobi = gobi.replace('ャ', 'ヤ').replace('ュ', 'ユ').replace(
'ョ', 'ヨ').replace('ッ', 'ツ').replace('ィ', 'イ').replace(
'ァ', 'ア').replace('ェ', 'エ').replace('ゥ', 'ウ').replace(
'ォ',
'オ').replace('ヵ',
'カ').replace('ヶ',
'ケ').replace('ヮ', 'ワ')
if self.game_mode == 'reverse':
gotou, gobi = gobi, gotou
word = {}
lenword = len(kana)
last = ''
try:
if self.game_mode != 'reverse':
last = kanasList[-1][-1]
if last == 'ー':
last = kanasList[-1].replace('ー', '')[-1]
else:
last = kanasList[-1][0]
last = last.replace('ャ', 'ヤ').replace('ュ', 'ユ').replace(
'ョ', 'ヨ').replace('ッ', 'ツ').replace('ィ', 'イ').replace(
'ァ',
'ア').replace('ェ', 'エ').replace('ゥ', 'ウ').replace(
'ォ', 'オ').replace('ヵ', 'カ').replace(
'ヶ', 'ケ').replace('ヮ', 'ワ')
except Exception as e:
d(e, 'srtr')
if not last:
wordsList.append(rawnoun)
kanasList.append(kana)
if self.event == 'showlist':
return wordsList
elif self.event == 'restart':
wordsList = []
kanasList = []
try:
num = re.match("\d*", s)
extracted = num.group()
self.len_rulelen_rule = int(extracted)
is_changed = True
s = s.replace('文字', '').replace('字',
'').replace('以上', '')
except Exception as e:
len_rule = 1
if gobi == 'ン':
rawnoun = 'しりとり'
kana = 'シリトリ'
gobi = 'リ'
wordsList.append(rawnoun)
kanasList.append(kana)
if self.game_mode != 'reverse':
status = 'start_normal'
else:
status = 'start_reverse'
elif lenword < self.len_rule and rawnoun != 'しりとり':
status = 'alert_short'
else:
if last != gotou:
if self.game_mode != 'reverse':
status = 'alert_miss'
else:
status = 'alert_miss_reverse'
elif rawnoun in wordsList:
status = 'win_double'
elif gobi == 'ン':
status = 'win_N'
else:
wordsList.append(rawnoun)
kanasList.append(kana)
LoseFlag = False
# LoseFLAG
if turncnt > 25:
LoseFlag = True
with db.atomic():
if LoseFlag:
answords = TFIDFModel.select().where(
TFIDFModel.yomi.startswith(gobi),
TFIDFModel.yomi.endswith('ン'),
TFIDFModel.hinshi << ['名詞', '固有名詞'],
~TFIDFModel.hinshi << ['数']).order_by(
TFIDFModel.df.desc()).limit(50)
answord = self.choose_answord(answords)
else:
if self.game_mode != 'reverse':
select_words = TFIDFModel.select().where(
TFIDFModel.yomi.startswith(gobi),
~TFIDFModel.yomi.contains('*'),
~TFIDFModel.yomi.endswith('ン'),
TFIDFModel.hinshi << ['名詞', '固有名詞'],
~TFIDFModel.hinshi2 << ['数', ' 接尾'])
else:
select_words = TFIDFModel.select().where(
TFIDFModel.yomi.endswith(gobi),
~TFIDFModel.yomi.contains('*'),
TFIDFModel.hinshi << ['名詞', '固有名詞'],
~TFIDFModel.hinshi2 << ['数', '接尾'])
answords = select_words.order_by(
TFIDFModel.df.desc()).limit(300)
answord = self.choose_answord(answords)
if answord.word in wordsList:
status = 'lose_double'
elif answord.yomi[-1] == 'ン':
status = 'lose_N'
else:
if self.game_mode != 'reverse':
status = 'return_normal'
next_char = answord.yomi[-1]
else:
status = 'return_reverse'
next_char = answord.yomi[0]
anskana = answord.yomi
if next_char == 'ー':
next_char = answord.yomi[-2]
anskana = answord.yomi[:-1]
wordsList.append(answord.word)
kanasList.append(anskana)
except Exception as e:
d(e, 'srtr')
wordsList = []
kanasList = []
with db.atomic():
self.srtrdb.name = self.user
self.srtrdb.mode = self.game_mode
self.srtrdb.word_stream = '<JOIN>'.join(wordsList)
self.srtrdb.kana_stream = '<JOIN>'.join(kanasList)
self.srtrdb.len_rule = self.len_rule
self.srtrdb.tmp_time = datetime.utcnow()
self.srtrdb.save()
p(status)
if last:
last = last.replace('ャ', 'ヤ').replace('ュ', 'ユ').replace(
'ョ', 'ヨ').replace('ッ', 'ツ').replace('ィ', 'イ').replace(
'ァ', 'ア').replace('ェ', 'エ').replace('ゥ', 'ウ').replace(
'ォ', 'オ').replace('ヵ',
'カ').replace('ヶ',
'ケ').replace('ヮ', 'ワ')
if not status:
ans = '思いつきませんでした。悔しいですけど、私の負けです。\END'
elif status == 'start_normal':
ans = 'いいですね。' + str(
self.len_rule
) + '字以上でしりとりをしましょう。\nそれでは、「' + rawnoun + '」から開始です。'
elif status == 'start_reverse':
ans = 'いいですね。' + str(
self.len_rule
) + '字以上で逆しりとりしましょう。\nそれでは、「' + rawnoun + '」から開始です。'
elif status == 'alert_nonoun':
ans = '名詞の単語が見あたりません。他の単語はありませんか？\MISS'
elif status == 'alert_short':
ans = '「' + rawnoun + '」ですね。' + str(
self.len_rule) + '字縛りなので、字数が短いです。\n「しりとりおわり」で降参しても構いません。\MISS'
elif status == 'alert_miss':
ans = 'その言葉ではだめです。\n「' + last + '」ではじめる別の単語でお願いします。「しりとりおわり」で終了してもOKです。\MISS'
elif status == 'alert_miss_reverse':
ans = 'その言葉ではだめです。\n「' + last + '」でおわる別の単語でお願いします。「しりとりおわり」で終了してもOKです。\MISS'
elif status == 'lose_double':
ans = '「' + rawnoun + '」ですね。' + gobi + '...\n' + answord.word + ' ですッ!! あ、既に出ていた単語でした...。くっ、私の負けです。\END'
elif status == 'lose_N':
ans = '「' + rawnoun + '」ですね。' + gobi + '...\n' + answord.word + ' ですッ!! あ、「ン」がついてしまいました...。くっ、私の負けです。\END'
elif status == 'win_double':
ans = '「' + rawnoun + '」ですね。' + gobi + '...\n' + 'その言葉は既に使われましたよ。私の勝利ですっ!! \END'
elif status == 'win_N':
ans = '「' + rawnoun + '」ですね。' + gobi + '...\n' + '「ン」で終わりましたね。私の勝利です。 \END'
elif status == 'return_normal':
ans = '「' + rawnoun + '」ですね。' + gobi + '...\n' + answord.word + '(' + answord.yomi + ')' + ' ですっ!! 次の頭文字は「' + next_char + '」ですよ。'
elif status == 'return_reverse':
ans = '「' + rawnoun + '」ですね。' + gobi + '...\n' + answord.word + '(' + answord.yomi + ')' + ' ですっ!! 次の末尾の文字は「' + next_char + '」ですよ。'
else:
ans = 'エラーが発生しました。管理者にお問い合わせください。[{status}] \END'.format(
status=status)
return ans
def on_exception(self, exception):
p(exception, self.bot_id, 'exception')
return False
cvimg = overlay_on_part(src_image = cvimg, overlay_image = overlay_image_resized, posX = pos['left'], posY = pos['top'])
# framed_id = save_image_sql(cvimg = cvimg, filename = ''.join([_id, '_framed', str(LTRB)]), url = _id, owner = None, compression_quality = 70, compression_format = 'jpg')`
return cvimg
if __name__ == '__main__':
sys.stdout = io.TextIOWrapper(sys.stdout.buffer, encoding='utf-8')
filename = "/XXXXXX"
# filename2 = /XXXXXX'
# make_qrcode(data = 'hello')
_id = '832b32bb-3e2d-4bbf-9217-ff358fa8a317'
# cvimg = read_image_sql(_id = _id)
# p(passzbar(cvimg))
# _ID = save_image_sql(cvimg, filename = None, url = 'MjAxNjA5MDUwMzE5MzYvNDUyNDA=', owner = None, compression_quality = 70, compression_format = 'jpg')
result = recognize_faceimage(_id = '7aa33bfe-e6c0-4156-a4d0-7e53e88b1dd1', is_show = True,cascade_lib = cascade_lib_anime)
p(result)
# p(uuid.uuid4())
# p(uuid.uuid4().hex)
# make_qrcode(data = 'hello', owner = None)
# height, width = img.shape[:2]
# p(height * width)
# compression_params = [cv2.IMWRITE_JPEG_QUALITY, 70]
# retval, buf = cv2.imencode('jpg', img, compression_params)
# if not retval:
# raise ValueError('The Given image could not be converted to BMP binary data')
# height, width = buf.shape[:2]
# p(height * width)
# # convert buf from numpy.ndarray to bytes
# binary = buf.tobytes()
# BinaryBank.create_or_get(filename = 'test',data = binary)
# p(type(img))
json['detection'] = 'anime'
json['prediction'] = result_dic['anime']['extracted'][i]['label']
result_dic['anime']['extracted'][i]['framed_id'] = opencv_functions.save_image_sql(cvimg = framed_cvimg, filename = ''.join([str(_id), '_SVMdetect', result_dic['anime']['extracted'][i]['label'], '_framed', str(i)]), url = str(_id), owner = None, json = json, compression_quality = 70, compression_format = 'jpg')
elif 'cat' in result_dic:
result_dic['cat']['extracted'][0]['label'] = 'cat'
json['detection'] = 'cat'
frame_setting = {'thickness': 1, 'color':(204,153,153), 'scale':1.1, 'overlay_id' :'fabdb2c9-50c7-459e-9a29-94bbcdd77381'}
json['frame_setting'] = frame_setting
framed_cvimg = opencv_functions.frame_image(cvimg = result_dic['cat']['original_cvimg'], pos = result_dic['cat']['extracted'][0]['pos'], frame_setting = frame_setting)
result_dic['cat']['extracted'][0]['framed_id'] = opencv_functions.save_image_sql(cvimg = framed_cvimg, filename = ''.join([str(_id), '_cat', '_framed', str(0)]), url = str(_id), owner = None, json = json, compression_quality = 70, compression_format = 'jpg')
return result_dic
if __name__ == '__main__':
import sys, os, io
sys.stdout = io.TextIOWrapper(sys.stdout.buffer, encoding='utf-8')
# 6海未 7真姫
filename = /XXXXXX'
DIR = /XXXXXX'
ans = predict_svm(_id = '7aa33bfe-e6c0-4156-a4d0-7e53e88b1dd1', is_show = 1, model = modelSVM, label = ['others', 'ことり', 'にこ', '真姫', '凛', '希', '海未', '真姫', '穂乃果', '絵里', '花陽', '雪穂'])
print(ans)
if 'anime' in ans:
p('a')
# label, img_kind, IMGfile = machine_learning_img.predictSVM(filename = filename, isShow = False, model = modelSVM, work_dir = '')
# train_svm(DIR = "/XXXXXX", save_dir = DATADIR + '/lib/SVM_us3/SVMmodel3.pkl')
# adrs = [DIR+clsdir for clsdir in os.listdir(DIR) if not clsdir in set(['.DS_Store'])]
# print([predictSVM(filename =adr, isShow = 0, model = modelSVM)[0] for adr in adrs[:1]])
#
ans_ls.append('↑↑↑↑↑↑↑')
[ans_ls.append(name) for name in level_name]
structureName.append(level_name)
ans_ls.append('######CAUSE######')
ans = '\n'.join(ans_ls)
p(ans)
return structureName, structure
if __name__ == '__main__':
import sys
import io
import os
sys.stdout = io.TextIOWrapper(sys.stdout.buffer, encoding='utf-8')
try:
argvs = sys.argv
text = argvs[1]
p2 = argvs[2]
mode = 'simple'
except:
text = 'S1→S5\nS2→S1\nS2→S3\nS2→S4\nS3→S5\nS3→S4\nS4→S3\nS6→S2\nS6→S5'
p2 = 'ISM.detail()'
mode = 'simple'
# if text == 'demo':
text = 'S1→S5\nS2→S1\nS2→S3\nS2→S4\nS3→S5\nS3→S4\nS4→S3\nS6→S2\nS6→S5'
# if p2 == 'ISM.detail()':
# mode = 'detail'
arrow = '→'
structure_name, structure = simplifyC(text, arrow, is_print=True)
p(structure_name)
