arnrs/main.py

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import os
import threading
import csv
import time
import itertools
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from detector import Detector
from paddleocr import PaddleOCR
import cv2
import easyocr
import requests
class number(object):
def __init__(self, gpu=False, times=1, filter=0.8, ua="ARNRS", debug=False):
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assert type(gpu) is bool
assert type(times) is int and times >= 1
self.gpu = gpu
self.times = times
self.similar = {"8": "B", "O": "0", "-": "", "1": "/", "l": "I", "2": "Z", "4": "A"}
self.ua = ua
self.filter = filter
self.debug = debug
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# Init detector and OCR
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self.__detector = Detector(device="cuda" if gpu else "cpu")
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self.__eocr = easyocr.Reader(['ch_sim', 'en'], gpu=self.gpu)
self.__pocr = PaddleOCR(use_angle_cls=True, use_gpu=self.gpu, show_log=debug)
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# Init database
self.__database = {}
i = 0
with open('aircraftDatabase.csv', "r", encoding='utf-8') as fb:
for row in csv.reader(fb, skipinitialspace=True):
if not i:
keys = row
else:
self.__database[row[1]] = dict(zip(keys, row))
self.__database[row[1].replace("-", "")] = dict(zip(keys, row))
i += 1
# Try to update database
'''
update_database_daemon_thread = threading.Thread(target=self.__update_database_daemon, name="Update Database Daemon Thread")
update_database_daemon_thread.daemon = True
update_database_daemon_thread.start()
'''
def __update_database_daemon(self):
while True:
update_database_thread = threading.Thread(target=self.__update_database, name="Update Database Thread")
update_database_thread.daemon = True
update_database_thread.start()
time.sleep(60 * 60 * 1)
def __update_database(self):
f = 0
while True:
try:
database = requests.get("https://opensky-network.org/datasets/metadata/aircraftDatabase.csv", headers={"user-agent": self.ua}).text
except Exception as e:
print("Failed to update local registration number database,", e, ", retrying... Times: ", f+1)
f += 1
if f >= 10:
break
else:
with open('aircraftDatabase.csv', "w+", encoding='utf-8') as fb:
fb.write(database)
self.__database = []
i = 0
with open('aircraftDatabase.csv', "r", encoding='utf-8') as fb:
for row in csv.reader(fb, skipinitialspace=True):
if not i:
keys = row
else:
self.__database.append(dict(zip(keys, row)))
i += 1
break
def __distance(self, p1, p2):
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return ((p1[0] - p2[0]) ** 2 + (p1[1] - p2[1]) ** 2) ** 0.5
def __closest_pair(self, X, Y):
if len(X) <= 3:
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return min([self.__distance(X[i], X[j]) for i in range(len(X)) for j in range(i + 1, len(X))])
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mid = len(X) // 2
XL, XR = X[:mid], X[mid:]
YL, YR = [p for p in Y if p in XL], [p for p in Y if p in XR]
d = min(self.__closest_pair(XL, YL), self.__closest_pair(XR, YR))
line = (X[mid][0] + X[mid-1][0]) / 2
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YS = [p for p in Y if abs(p[0] - line) < d]
return min(d, self.__closest_split_pair(YS, d))
def __closest_split_pair(self, Y, d):
n = len(Y)
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for i in range(n - 1):
for j in range(i + 1, min(i + 8, n)):
if self.__distance(Y[i], Y[j]) < d:
d = self.__distance(Y[i], Y[j])
return d
def __dis(self, p1, p2):
X = p1 + p2
Y = sorted(X, key=lambda p: (p[0], p[1]))
return self.__closest_pair(X, Y)
def search(self, keyword):
'''
Search a plane by it registration number
:keyword Registration number
'''
if keyword.upper() in self.__database.keys() and not keyword.isdigit():
return self.__database[keyword.upper()]
# Similar characters replace
self.similar = {**self.similar, **dict(zip(self.similar.values(), self.similar.keys()))}
condition = []
for i in range(1, len(self.similar.items()) + 1):
condition.extend(list(itertools.combinations(self.similar.items(), i)))
for c in condition:
for c_i in c:
keyword_temp = keyword.replace(c_i[0], c_i[1])
if keyword_temp.upper() in self.__database.keys():
return self.__database[keyword_temp.upper()]
if keyword.upper() in self.__database.keys() and keyword.isdigit():
return self.__database[keyword.upper()]
return None
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def recognize(self, image):
'''
Recognize aircraft registration number with detection
and ocr powered by pytorch and paddlepaddle engine.
:image Accept numpy array or image file path
'''
if type(image) is str:
path = os.path.abspath(image)
image = cv2.imread(path)
result = self.__detector.image(image)
# Subjective judgment
area_max = 0
area_index = 0
for i in range(len(result[1])):
d = result[1][i]
this_area = ((d["box"][1] - d["box"][0]) ** 2 + (d["box"][3] - d["box"][2]) ** 2) ** 0.5
if this_area > area_max and result[1][i]["class"] == "airplane":
area_max = this_area
area_index = i
i = result[1][area_index]
img = image[int(i["box"][1]):int(i["box"][3]), int(i["box"][0]):int(i["box"][2])]
ocr_result = []
ocr_filter = []
for _ in range(self.times):
# OCR recognize
pocr_result = self.__pocr.ocr(img, cls=True)
if self.debug:
print(pocr_result)
print("------------------------------B-")
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eocr_result = self.__eocr.readtext(img, detail=1)
if self.debug:
print(eocr_result)
print("------------------------------A-")
# OCR results tidy up
for i in range(len(pocr_result[0])):
for j in range(len(pocr_result[0])):
if self.debug:
print("------------------------------D-")
print(pocr_result[0][i][0], pocr_result[0][j][0])
if i != j and len(pocr_result[0][i][0]) == 4 and len(pocr_result[0][j][0]) == 4 and self.__dis(pocr_result[0][i][0], pocr_result[0][j][0]) < 5:
if self.debug:
print("D Appended")
pocr_result.append(((pocr_result[0][i][0], pocr_result[0][j][0]), pocr_result[0][i][1][1] + pocr_result[0][j][1][1], (pocr_result[0][i][1][2] + pocr_result[0][j][1][2]) / 2))
pocr_result.append(((pocr_result[0][j][0], pocr_result[0][i][0]), pocr_result[0][j][1][1] + pocr_result[0][i][1][1], (pocr_result[0][j][1][2] + pocr_result[0][i][1][2]) / 2))
else:
if self.debug:
disout = 0
if len(eocr_result[i][0]) == 4 and len(eocr_result[j][0]) == 4:
disout = self.__dis(pocr_result[0][i][0], pocr_result[0][j][0])
print(i != j, len(pocr_result[0][i][0]) == 4, len(pocr_result[0][j][0]) == 4, disout)
print("------------------------------D-")
for i in range(len(eocr_result)):
for j in range(len(eocr_result)):
if self.debug:
print("------------------------------C-")
print(eocr_result[i][0], eocr_result[j][0])
if i != j and len(eocr_result[i][0]) == 4 and len(eocr_result[j][0]) == 4 and self.__dis(eocr_result[i][0], eocr_result[j][0]) < 5:
if self.debug:
print("C Appended")
eocr_result.append(((eocr_result[i][0], eocr_result[j][0]), eocr_result[i][1] + eocr_result[j][1], (eocr_result[i][2] + eocr_result[j][2]) / 2))
eocr_result.append(((eocr_result[j][0], eocr_result[i][0]), eocr_result[j][1] + eocr_result[i][1], (eocr_result[j][2] + eocr_result[i][2]) / 2))
else:
if self.debug:
disout = 0
if len(eocr_result[i][0]) == 4 and len(eocr_result[j][0]) == 4:
disout = self.__dis(eocr_result[i][0], eocr_result[j][0])
print(i != j, len(eocr_result[i][0]) == 4, len(eocr_result[j][0]) == 4, disout)
print("------------------------------C-")
if self.debug:
print(pocr_result)
print(eocr_result)
# OCR results sum up
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for p in pocr_result[0]:
if p[1][1] > self.filter and p[1][0] not in ocr_filter:
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ocr_result.append(
(tuple([tuple(i) for i in p[0]]), p[1][0], p[1][1])
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)
ocr_filter.append(p[1][0])
for e in eocr_result:
if e[2] > self.filter and e[1] not in ocr_filter:
ocr_result.append(
(tuple([tuple(i) for i in e[0]]), e[1], e[2])
)
ocr_filter.append(e[1])
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ocr_result = sorted(ocr_result, key=lambda x:len(x[1]), reverse=True)
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# Read database
for i in ocr_result:
r = self.search(i[1])
if r:
return r
if self.debug:
print(ocr_result)
return None
if __name__ == "__main__":
import json
num = number()
os.makedirs("out", exist_ok=True)
for pic in os.listdir("test"):
with open(os.path.join("out", f"{pic}.json"), "w+") as fb:
fb.write(json.dumps(num.recognize(os.path.join("test", pic))))