def car_number(frame):
layerOutputs, start, end = yolo.YOLO_Detect(frame) #yolo detection
idxs, boxes, classIDs, confidences = yolo.YOLO_BOX_INFO(
frame, layerOutputs) #detected object info
Vehicle_x = []
Vehicle_y = []
Vehicle_w = []
Vehicle_h = []
Vehicle_x, Vehicle_y, Vehicle_w, Vehicle_h = yolo.Position(
idxs, classIDs, boxes, Vehicle_x, Vehicle_y, Vehicle_w, Vehicle_h)
yolo.Draw_Points(frame, Vehicle_x, Vehicle_y, Vehicle_w, Vehicle_h)
"""
cv2.imshow('piece', frame)
cv2.waitKey(0)
cv2.destroyAllWindows()
"""
number = len(idxs)
return number
def main():
fps = FPS().start()
cap = cv2.VideoCapture(Input_Video)
(grabbed, frame) = cap.read()
#make background frame
first_frame = frame.copy()
first_gray = cv2.cvtColor(first_frame, cv2.COLOR_BGR2GRAY)
first_gray = cv2.GaussianBlur(first_gray, (5, 5), 0)
f_num = 0
#parking area variable
RED_cnt_1 = 0
BLUE_cnt_1 = 0
initBB_1 = None
tracker_1 = None
RED_cnt_2 = 0
BLUE_cnt_2 = 0
initBB_2 = None
tracker_2 = None
RED_cnt_3 = 0
BLUE_cnt_3 = 0
initBB_3 = None
tracker_3 = None
RED_cnt_4 = 0
BLUE_cnt_4 = 0
initBB_4 = None
tracker_4 = None
vertices = []
vertices, pos = parkinglot(vertices)
area = []
area = parkinglot_piece(frame, area)
l_up = 0
l_down = 0
r_up = 0
r_down = 0
#parking area counting variable
l_up, l_down, r_up, r_down = preprocess(
frame, area) #already parking car counting
yolo.YOLOTINYINIT() #tiny yolo initialization
while (cap.isOpened()):
csv_file = open_csv() #csv file open
wr = csv.writer(csv_file, delimiter=' ')
f_num = f_num + 1
(grabbed, frame) = cap.read()
#counting variable
temp_r_1 = RED_cnt_1
temp_b_1 = BLUE_cnt_1
temp_r_2 = RED_cnt_2
temp_b_2 = BLUE_cnt_2
temp_r_3 = RED_cnt_3
temp_b_3 = BLUE_cnt_3
temp_r_4 = RED_cnt_4
temp_b_4 = BLUE_cnt_4
#error exception
if (l_up < 0 or l_up > 3 or l_down < 0 or l_down > 3 or r_up < 0
or r_up > 3 or r_down < 0 or r_down > 3):
area = parkinglot_piece(frame, area)
l_up, l_down, r_up, r_down = error_detection(
area, l_up, l_down, r_up, r_down)
yolo.YOLOTINYINIT()
if f_num % 2 == 0: #detection per two frame
#black space at upper frame
blank_image = np.zeros((64, 1920, 3), np.uint8)
frame[0:64, 0:1920] = blank_image
#set list for loop
park_cnt = [l_up, l_down, r_up, r_down]
RED_cnt = [RED_cnt_1, RED_cnt_2, RED_cnt_3, RED_cnt_4]
BLUE_cnt = [BLUE_cnt_1, BLUE_cnt_2, BLUE_cnt_3, BLUE_cnt_4]
Substracted = substraction(frame, first_gray) #background image
layerOutputs, start, end = yolo.YOLO_Detect(frame) #yolo detection
idxs, boxes, classIDs, confidences = yolo.YOLO_BOX_INFO(
frame, layerOutputs) #detected object info
#point of detected car
Vehicle_x = []
Vehicle_y = []
Vehicle_w = []
Vehicle_h = []
Vehicle_x, Vehicle_y, Vehicle_w, Vehicle_h = yolo.Position(
idxs, classIDs, boxes, Vehicle_x, Vehicle_y, Vehicle_w,
Vehicle_h)
#draw bounding box of detected car
yolo.Draw_Points(frame, Vehicle_x, Vehicle_y, Vehicle_w, Vehicle_h)
#left up
tracker_1, initBB_1, RED_cnt_1, BLUE_cnt_1 = Passing_Counter_Zone(Vehicle_x, Vehicle_y, Vehicle_w, Vehicle_h, initBB_1, frame, tracker_1, Substracted,\
RED_cnt_1, BLUE_cnt_1, vertices[0])
l_up, temp_r_1, temp_b_1 = park_count(park_cnt[0], temp_r_1,
temp_b_1, RED_cnt_1,
BLUE_cnt_1)
#left down
tracker_2, initBB_2, RED_cnt_2, BLUE_cnt_2 = Passing_Counter_Zone(Vehicle_x, Vehicle_y, Vehicle_w, Vehicle_h, initBB_2, frame, tracker_2, Substracted,\
RED_cnt_2, BLUE_cnt_2, vertices[1])
l_down, temp_r_2, temp_b_2 = park_count(park_cnt[1], temp_r_2,
temp_b_2, RED_cnt_2,
BLUE_cnt_2)
#right up
tracker_3, initBB_3, RED_cnt_3, BLUE_cnt_3 = Passing_Counter_Zone(Vehicle_x, Vehicle_y, Vehicle_w, Vehicle_h, initBB_3, frame, tracker_3, Substracted,\
RED_cnt_3, BLUE_cnt_3, vertices[2])
r_up, temp_r_2, temp_b_2 = park_count(park_cnt[2], temp_r_3,
temp_b_3, RED_cnt_3,
BLUE_cnt_3)
#right down
tracker_4, initBB_4, RED_cnt_4, BLUE_cnt_4 = Passing_Counter_Zone(Vehicle_x, Vehicle_y, Vehicle_w, Vehicle_h, initBB_4, frame, tracker_4, Substracted,\
RED_cnt_4, BLUE_cnt_4, vertices[3])
r_down, temp_r_2, temp_b_2 = park_count(park_cnt[3], temp_r_4,
temp_b_4, RED_cnt_4,
BLUE_cnt_4)
#draw lines
for i in range(0, 4):
draw_line(frame, vertices[i], RED_cnt[i], BLUE_cnt[i])
pts = detecting_zone(vertices[i])
cv2.polylines(frame, [pts], True, (0, 255, 0), 2)
fps.update()
fps.stop()
#text at upper frame
cv2.putText(frame, "FPS : " + "{:.2f}".format(fps.fps()), (50, 45),
cv2.FONT_HERSHEY_SIMPLEX, 1.5, (200, 200, 200), 2)
cv2.putText(
frame, pos[0] + ": {} / ".format(park_cnt[0]) + pos[1] +
": {} / ".format(park_cnt[1]) + pos[2] +
": {} / ".format(park_cnt[2]) + pos[3] +
": {}".format(park_cnt[3]), (450, 45),
cv2.FONT_HERSHEY_SIMPLEX, 1.5, (200, 200, 200), 2)
cv2.putText(frame, "Frame : " + "{}".format(f_num), (1500, 45),
cv2.FONT_HERSHEY_SIMPLEX, 1.5, (200, 200, 200), 2)
frame = cv2.resize(frame, (960, 540), interpolation=cv2.INTER_AREA
) #1920,1080 -> 1280,720 -> 960,540
Substracted = cv2.resize(Substracted, (960, 540),
interpolation=cv2.INTER_CUBIC)
cv2.imshow("frame", frame)
cv2.imshow("sub", Substracted)
wr.writerow([park_cnt[0], park_cnt[1], park_cnt[2], park_cnt[3]])
if cv2.waitKey(1) & 0xFF == ord('q'):
break
csv_file.close()
cap.release()
return