def test_query(self):
s = Searcher('search_engine_nyk.sql')
#self.assertEqual(s.query('AOAPAPA'), [])
#print(s.query('love')[:1])
#print(s.query('Mad Men'))
#self.assertEqual(s.query('Mad Men'), [])
pass
from tracker_engine.tracker import TrackerMulti
from worker import handle_missing_object, save_image_product
from model import *
from sqlalchemy import func
from flask_jwt_extended import create_access_token, verify_jwt_in_request, current_user, get_jwt, jwt_required
from functools import wraps
import base64
import io
import numpy as np
import re
# Global param
detector = Detector()
extractor = Extractor()
searcher = Searcher()
# extractor = None
# searcher = None
# detector = None
tracker = TrackerMulti()
######################## User API ########################
# Utilities
@jwt.user_identity_loader
def user_identity_lookup(user):
# Convert object to JSON serializable format for token
return user.username
def test_normalize_scores(self):
s = Searcher('abc.db')
self.assertEqual(s.normalize_scores({}, 1), {})
self.assertEqual(s.normalize_scores({}, 0), {})
def test_inbound_scores(self):
s = Searcher('nyw.sql')
s.calculate_page_rank()
self.assertNotEqual(s.inbound_link_scores({}), {})
def test_distance_scores(self):
s = Searcher('abc.db')
self.assertEqual(s.distance_scores({}), {})
def test_normalize_scores(self):
s = Searcher('abc.db')
self.assertEqual(s.normalize_scores({}, 1), {})
self.assertEqual(s.normalize_scores({}, 0), {})
def test_inbound_scores(self):
s = Searcher('nyw.sql')
s.calculate_page_rank()
self.assertNotEqual(s.inbound_link_scores({}), {})
def test_distance_scores(self):
s = Searcher('abc.db')
self.assertEqual(s.distance_scores({}), {})
ap.add_argument("-i",
"--index",
required=True,
help="Path to where the computed index will be stored")
ap.add_argument("-q", "--query", required=True, help="Path to the query image")
ap.add_argument("-r",
"--result-path",
required=True,
help="Path to the result path")
args = vars(ap.parse_args())
# initialize the image descriptor
cd = ColorDescriptor((8, 12, 3))
# load the query image and describe it
query = cv2.imread(args["query"])
features = cd.describe(query)
# perform the search
searcher = Searcher(args["index"])
results = searcher.search(features)
# display the query
cv2.imshow("Query", query)
# loop over the results
for (score, resultID) in results:
# load the result image and display it
result = cv2.imread(args["result_path"] + "/" + resultID)
cv2.imshow("Result", result)
cv2.waitKey(0)
