def handle(bot, update):
# import ipdb; ipdb.set_trace()
f = bot.getFile(update.message.photo[-1].file_id)
fn = "files/{}.jpg".format(time.time())
f.download(fn)
guess = run_inference_on_image(fn)
bot.sendMessage(chat_id=update.message.chat_id,
text="I think it is a {}".format(guess))
def PIC_classify_pic_func(self):
if self.imported:
classification = run_inference_on_image(self.my_directory_path +
'/images/import_dream')
self.pic_classification = classification
self.PIC_description.setText(classification)
else:
self.PIC_LC.setText("Import a picture first")
def NF_classify_pic_func(self):
if self.first_dream:
classification = run_inference_on_image(self.my_directory_path +
'/images/default')
self.nf_classification = classification
self.NF_description.setText(classification)
else:
self.NF_LC.setText("Dream a picture first")
def post(self):
fileinfo = self.request.files['file'][0]
# print "fileinfo is", fileinfo
fname = fileinfo['filename']
extn = os.path.splitext(fname)[1]
cname = str(uuid.uuid4()) + extn
filePath = __UPLOADS__ + cname
fh = open(filePath, 'w')
fh.write(fileinfo['body'])
fh.close()
keywords = classify.run_inference_on_image(filePath)
self.write(json_encode(keywords))
def image_rec(bot, update):
# import ipdb; ipdb.set_trace()
f = bot.getFile(update.message.photo[-1].file_id)
fn = "files/{}.jpg".format(time.time())
f.download(fn)
resp = run_inference_on_image(fn)
obj_info = search_info_by_id(mapping(resp))
print(obj_info)
if obj_info[2] == '1':
obj_inf = "принимаем"
else:
obj_inf = "не принимаем"
bot.sendMessage(chat_id=update.message.chat_id,
text='Это {} и это мы {}'.format(obj_info[0], obj_inf))
bot.sendMessage(chat_id=update.message.chat_id, text=resp)
def put(self):
try:
# Parse the arguments
parser = reqparse.RequestParser()
parser.add_argument('user_id', type=str, help='user_id')
parser.add_argument('filename',
type=str,
help='Class of shared waste')
parser.add_argument('file',
type=werkzeug.FileStorage,
location='files',
help='Class of shared waste')
args = parser.parse_args()
print(args)
_userid = args['user_id']
_filename = args['filename']
_file = args['file'].stream
if not os.path.exists(_FOLDER_4_RCGN_):
os.makedirs(_FOLDER_4_RCGN_)
request_id = uuid.uuid1().__str__()
fn = "[{}]-[{}]-[{}]-{}".format(request_id, _userid, time.time(),
translit(_filename, reversed=True))
full_fn = _FOLDER_4_RCGN_ + "/" + fn
with open(full_fn, 'wb') as fout:
fout.write(_file.getvalue())
resultFlag = True
#
#
#resp = "сеть скорей всего не работает. печаль!!!"
print(full_fn)
try:
resp = run_inference_on_image(full_fn)
print(resp)
except Exception as e:
resultFlag = False
print(e)
#
#
#
result = ''
try:
with codecs.open("recycle_db.csv",
encoding='utf-8') as csvfile:
reader = csv.reader(csvfile, delimiter=',', quotechar='"')
for rec in reader:
if rec[2] in resp or resp in rec[2]:
result = rec[1]
if result == '':
result = "не удалось определить класс отходов"
pass
except Exception as e:
print(e)
if 'disposable paper cups resize' in resp:
result = "бумажный стакан"
if 'lame foil' in resp:
result = "фольга"
if 'glass bottle' in resp:
result = "стеклянная бутылка"
if 'plastic bottle' in resp:
result = "пластиковая бутылка"
if 'stupid' in resp:
result = "неудалось определить класс отходов"
if 'receipt' in resp:
result = "чек"
pass
return {
'StatusCode': '200',
'Message': result,
'callback_id': request_id
}
except Exception as e:
return {'error': str(e)}
def test_inference(image_name, animal_name):
# Ignore score in case it varies slightly on different platforms.
# Just check the name.
human_readable_name, _ = run_inference_on_image(image_name)
assert human_readable_name == animal_name