def build(self, lex_file, dict_dir):
"""
读入规则文件， 词典文件
构建自动机和匹配引擎
"""
ori_in = read_lex(lex_file)
script = char_stream(ori_in)
tokens = token_list(script).tokens
ast_obj = ast.AST(stream(tokens))
# 逗号分开的词典文件目录列表， 会加载目录中所有txt文件
all_slot_entity_files = []
if dict_dir:
dict_dirs = dict_dir.split(",")
for dir_path in dict_dirs:
all_slot_entity_files.extend(glob.glob(dir_path + "/*.txt"))
print("词典文件:", all_slot_entity_files)
# 规则中的关键词
keywords = ast.extract_all_atoms(ast_obj)
ac_machine = ac.AC()
ac_machine.make(keywords, all_slot_entity_files)
rule_graph = parse.RuleStructure(ast_obj)
rule_trie, rule_info = rule_graph.build()
self.searcher = search.Searcher(rule_trie, rule_info, ac_machine)
self.rule_info = rule_info
def test_searching(self):
f = os.path.join(os.getcwd(), "testing_to_prepare.txt")
srchr = search.Searcher(f)
adr = "липово, набережная улица, 30"
exp = [(54.8199454, 18.3544725), (54.8216088, 18.351938),
(54.8223243, 18.3508078), (54.8231284, 18.349651),
(54.8256473, 18.3478349), (54.8239951, 18.3491378)]
self.assertEqual(list(filter(None, srchr.search_nodes(adr))), exp)
def proceedSearch(inputText, maxNotes):
searcher = search.Searcher()
searchRes = searcher.Search(inputText, getTitleList(), getTagsList())
maxIndex = maxNotes if len(searchRes) > maxNotes else len(searchRes)
indexes = []
for i in range(0, maxIndex):
indexes.append(searchRes[i][0])
fillSearchFrame(indexes)
def post(self, request):
form = forms.ImageUploadForm(request.POST, request.FILES)
if form.is_valid():
image = form.save()
searcher = search.Searcher(image)
searcher.run()
return make_response(request, self.RESULT_TEMPLATE, {
'queryImage': image,
'searcher': searcher,
'form': form,
})
else:
# response the error form to client
return make_response(request, self.SEARCH_TEMPLATE, {'form': form})
def do_GET(self):
parts = self.path.split('?', 1)
if len(parts) < 2:
self.send_error(400, "Missing query")
return
q = urlparse.parse_qs(parts[1])
q = q.get("q")
if q is None:
self.send_error(400, "Missing q parameter")
return
self.send_response(200)
self.send_header("Content-Type", "text/xml")
self.end_headers()
writer = codecs.getwriter('utf-8')(self.wfile)
searcher = search.Searcher(index_path)
searcher.query(q[0].decode('utf-8'), writer)
writer.flush()
def __init__(self, db_path='rocks.db'):
self.db = rocksdb.DB(db_path, rocksdb.Options(), read_only=True)
self.trace = True
self.searcher = search.Searcher(exact=True)
#important configs
self.skip_artists_with_no_tracks = True
self.simple_edges = False
self.max_edges_per_artist = 4
self.pop_weight = 100.00
self.min_popularity = 30
self.artist_blacklist = set()
self.edge_blacklist = collections.defaultdict(set)
self.load_blacklist()
self.load_graph()
def smartUpdate(self, id, onlineNumber):
"""
Compare online stored number of descendants with calculated number of descendants
given by the advised-table.
If numbers are equal, no mathematician has been added and no update is needed.
"""
self.cursor.execute("SELECT author FROM advised, dissertation WHERE student=dID AND advisor=?", (id,))
localStudents = self.cursor.fetchall()
print(u"Online descendants = {}".format(onlineNumber).encode('utf-8'))
if len(localStudents) > 0:
storedStudents = set()
for row in localStudents:
storedStudents.add(row["author"])
searcher = search.Searcher(self.connector, False, False)
calculatedNumber = searcher.numberOfDescendants(storedStudents)
if calculatedNumber == onlineNumber:
print(u"In local database = {}".format(calculatedNumber).encode('utf-8'))
print(u"Skip branch!".encode('utf-8'))
return True
else:
print(u"In local database >= {}".format(calculatedNumber).encode('utf-8'))
if calculatedNumber > onlineNumber:
print(u"Student(s) online deleted! Delete them in local database and grab this branch again.".encode('utf-8'))
for delStudent in storedStudents:
self.cursor.execute("DELETE FROM dissertation WHERE author=?", (delStudent,))
# TRIGGER and CASCADE statements will delete the entries in the other tables
self.connection.commit()
elif len(localStudents) == 0 and onlineNumber < 2:
print(u"In local database = 0".encode('utf-8'))
else:
print(u"In local database: N/A".encode('utf-8'))
return False
from flask import Blueprint, jsonify, g
import search
import os
api = Blueprint("api", __name__, url_prefix="/api")
searcher = search.Searcher(api_key=os.environ["NITRO_YOUTUBE_KEY"])
@api.route("/queue", methods=["GET"])
def get_queue():
queue = g.queue.get_queue()
return jsonify(queue)
@api.route("/queue/add/<id>", methods=["GET"])
def add_to_queue(id):
g.queue.add_song(id)
return "OK"
@api.route("/search/<query>", methods=["GET"])
def get_search_results(query):
query = query.strip().lower()
return jsonify(searcher.query(query))
output_clip.write_videofile(output_fname, audio=False)
if __name__ == '__main__':
import os
folder = 'output_video'
if not os.path.isdir(folder):
os.makedirs(folder)
# model = 'trained_models/HSV-ss(16, 16)-hb16-o9-p8-c2-hcALL-sf1-hist1-hog1-acc99.49.p'
# model = 'trained_models/HLS-ss(16, 16)-hb16-o9-p10-c2-hcALL-sf1-hist1-hog1-acc99.32.p'
# model = 'trained_models/YCrCb-ss(16, 16)-hb16-o9-p8-c2-hcALL-sf1-hist1-hog1-acc99.21.p'
model = 'trained_models/YCrCb-ss(16, 16)-hb16-o9-p8-c2-hcALL-sf1-hist1-hog1-acc99.72.p'
(fp, clf, X_scaler) = tr.load_classifier(model)
searcher = sr.Searcher(fp, clf, X_scaler)
sp = sr.SearchParams.get_defaults()
for heatmap_window_size in [10]:
for threshold in [1.7]:
for vehicle_window_size in [7]:
tracker = Tracker(searcher,
sp,
heatmap_window_size,
heatmap_threshold_per_frame=threshold,
vehicle_window_size=vehicle_window_size)
process_video(
'test_video.mp4',
'output_video/test_video_boost_heat_th{}_hw{}_vw{}.mp4'.
format(threshold, heatmap_window_size,
def test_initializing(self):
p = os.path.join(os.path.dirname(os.path.realpath(__file__)),
'filth.txt.bz2')
s = search.Searcher(p)
self.assertEqual(s.file_db, p)
self.assertDictEqual(s.address_coordinates, {})
tagsOk = False
if len(tags) == 0:
tagsOk = True
for t in tags:
if t in place["types"]:
tagsOk = True
if not tagsOk:
return False
if 'rating' not in place:
exit(1)
r = float(place["rating"])
return r >= rating
try:
searcher = search.Searcher()
location = sys.argv[1]
pages = 1
tags = []
rating = 0.0
i = 2
while i < len(sys.argv) - 2:
tags.append(sys.argv[i])
i += 1
if sys.argv[i] != 'none':
rating = float(sys.argv[i])
i += 1
results = int(sys.argv[i])
text = searcher.get_places_query(location.replace("_", " "), pages)
data = json.loads(text)
if len(tags) == 0 and rating == 0.0: