class TradeWorker(object):
def __init__(self):
# This block initializes the lists, that you need to trade.
self.all_item_classes = set()
self.in_buy_item_classes = set()
self.in_sell_item_classes = set()
self.in_freeze_item_classes = set()
self.in_check_item_classes = set()
self.controller = TradeWorkerController(self)
self.executor = Executor()
self.searcher = Searcher()
# Initializes controller, executor and checker_items_prices threads.
self.checker_price_thread = threading.Thread(target=self.searcher.start,
name='SearcherThread',
kwargs={'output_queue': self.controller.get_input_queue()})
self.executor_thread = threading.Thread(target=self.executor.start,
name='ExecutorThread',
kwargs={'output_queue': self.controller.get_input_queue()})
self.trade_worker_controller_thread = threading.Thread(target=self.controller.start_routing,
name='TradeWorkerControllerThread')
self.__start()
def __start(self):
self.__load_start_data()
self.__start_threads()
self.__start_main_event_loop()
def __load_start_data(self):
# This is temporary block. It's necessary before checker and executor was finale finished.
self.all_item_classes = set(ItemClass.get_default_itemclass_list()[:200])
self.in_buy_item_classes = set(list(self.all_item_classes)[5:50])
self.in_sell_item_classes = set(list(self.all_item_classes)[51:100])
self.refresh_in_check_item_classes()
self.controller.set_output_queue_searcher(self.searcher.get_input_queue())
self.controller.set_output_queue_executor(self.executor.get_input_queue())
def __start_threads(self):
# Start threads.
self.trade_worker_controller_thread.start()
# self.checker_price_thread.start()
self.executor_thread.start()
def __start_main_event_loop(self):
while True:
print 'Generate new loop!'
# self.search_trade_value_item_classes()
self.controller.output_queue_executor.put(1)
time.sleep(10)
def search_trade_value_item_classes(self):
for item_class in self.in_check_item_classes:
task = CheckProfitTradeTask(item_class)
self.controller.get_output_queue_searcher().put(task)
def refresh_in_check_item_classes(self):
self.in_check_item_classes = self.all_item_classes - self.in_buy_item_classes - self.in_sell_item_classes
def search():
if request.method == "POST":
results_arr = []
img_path = request.form.get("img")
try:
import cv2
d = Descriptor((8, 12, 3))
query = cv2.imread("static/images/" + img_path)
features = d.describe(query)
searcher = Searcher("index.csv")
results = searcher.search(features)
for (score, id) in results:
results_arr.append({"image": str(id), "score": str(score)})
return jsonify(results=(results_arr[::-1][:5]))
except:
return jsonify({"sorry": "Sorry, something went wrong! Please try again."})
def search():
if request.method == 'POST':
results_arr = []
img_path = request.form.get('img')
try:
import cv2
d = Descriptor((8, 12, 3))
query = cv2.imread('static/images/' + img_path)
features = d.describe(query)
searcher = Searcher('index.csv')
results = searcher.search(features)
for (score, id) in results:
results_arr.append({'image': str(id), 'score': str(score)})
return jsonify(results=(results_arr[::-1][:5]))
except:
return jsonify(
{'sorry': 'Sorry, something went wrong! Please try again.'})
def __init__(self):
# This block initializes the lists, that you need to trade.
self.all_item_classes = set()
self.in_buy_item_classes = set()
self.in_sell_item_classes = set()
self.in_freeze_item_classes = set()
self.in_check_item_classes = set()
self.controller = TradeWorkerController(self)
self.executor = Executor()
self.searcher = Searcher()
# Initializes controller, executor and checker_items_prices threads.
self.checker_price_thread = threading.Thread(target=self.searcher.start,
name='SearcherThread',
kwargs={'output_queue': self.controller.get_input_queue()})
self.executor_thread = threading.Thread(target=self.executor.start,
name='ExecutorThread',
kwargs={'output_queue': self.controller.get_input_queue()})
self.trade_worker_controller_thread = threading.Thread(target=self.controller.start_routing,
name='TradeWorkerControllerThread')
self.__start()
help="Engine to use for searching."
" Defaults to google ", default="google")
searcher.add_argument("-l", "--num-links", dest="number_of_links",
help="Number of links to return. "
"Defaults to 20", default=20, type=int)
# analizer related options
analizer = parser.add_argument_group('analizer')
analizer.add_argument("-k", "--keyword", dest="keyword", required=True,
help="Sentence to search on the web")
analizer.add_argument("-e", "--engine", dest="engine", type=str,
help="Engine to use for searching."
" Defaults to google ", default="google")
analizer.add_argument("-l", "--num-links", dest="number_of_links",
help="Number of links to return. "
"Defaults to 20", default=20, type=int)
args = parser.parse_args()
g = Searcher(args.keyword, engine=args.engine,
number_of_links=args.number_of_links)
print args
links = g.get_links()
default=20,
type=int)
# analizer related options
analizer = parser.add_argument_group('analizer')
analizer.add_argument("-k",
"--keyword",
dest="keyword",
required=True,
help="Sentence to search on the web")
analizer.add_argument("-e",
"--engine",
dest="engine",
type=str,
help="Engine to use for searching."
" Defaults to google ",
default="google")
analizer.add_argument("-l",
"--num-links",
dest="number_of_links",
help="Number of links to return. "
"Defaults to 20",
default=20,
type=int)
args = parser.parse_args()
g = Searcher(args.keyword,
engine=args.engine,
number_of_links=args.number_of_links)
print args
links = g.get_links()
from descriptor.descriptor import Descriptor
from searcher.searcher import Searcher
import argparse
import cv2
ap = argparse.ArgumentParser()
ap.add_argument('-i', '--index', required = True, help = 'Path to computed computed index')
ap.add_argument('-q', '--query', required = True, help = 'Path to query image')
ap.add_argument('-r', '--result', required = True, help = 'Path to picture database')
args = vars(ap.parse_args())
d = Descriptor((8, 12, 3))
query = cv2.imread(args['query'])
query = cv2.resize(query, (540, 360), cv2.INTER_AREA)
features = d.describe(query)
searcher = Searcher(args['index'])
results = searcher.search(features)
cv2.imshow('Query', query)
for (score, id) in results:
result = cv2.imread(args['result'] + '/' + str(id))
result = cv2.resize(result, (540, 360), cv2.INTER_AREA)
cv2.imshow('Result', result)
cv2.waitKey(0)