-
Notifications
You must be signed in to change notification settings - Fork 2
/
detect.py
91 lines (74 loc) · 2.97 KB
/
detect.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
import cv2
import numpy as np
import time
import datetime
# Load Yolo
net = cv2.dnn.readNet("yolo-coco/yolov3.weights", "yolo-coco/yolov3.cfg")
classes = []
with open("coco.names", "r") as f:
classes = [line.strip() for line in f.readlines()]
layer_names = net.getLayerNames()
outputlayers = [layer_names[i-1] for i in net.getUnconnectedOutLayers()]
colors = np.random.uniform(0, 255, size=(len(classes), 3))
# Loading image
cap = cv2.VideoCapture(0)
font = cv2.FONT_HERSHEY_PLAIN
starting_time = time.time()
frame_id = 0
while True:
_, frame = cap.read()
frame_id += 1
height, width, channels = frame.shape
# Detecting objects
blob = cv2.dnn.blobFromImage(frame, 0.00392, (90, 90), (0, 0, 0), True, crop=False)
net.setInput(blob)
outs = net.forward(outputlayers)
# Showing informations on the screen
class_ids = []
confidences = []
boxes = []
for out in outs:
for detection in out:
scores = detection[5:]
class_id = np.argmax(scores)
confidence = scores[class_id]
if confidence > 0.2:
# Object detected
center_x = int(detection[0] * width)
center_y = int(detection[1] * height)
w = int(detection[2] * width)
h = int(detection[3] * height)
# Rectangle coordinates
x = int(center_x - w / 2)
y = int(center_y - h / 2)
boxes.append([x, y, w, h])
confidences.append(float(confidence))
class_ids.append(class_id)
indexes = cv2.dnn.NMSBoxes(boxes, confidences, 0.8, 0.3)
for i in range(len(boxes)):
if i in indexes:
x, y, w, h = boxes[i]
label = str(classes[class_ids[i]])
confidence = confidences[i]
color = colors[class_ids[i]]
cv2.rectangle(frame, (x, y), (x + w, y + h), color, 2)
cv2.putText(frame, label + " " + str(round(confidence, 2)), (x, y + 30), font, 3, color, 3)
cv2.rectangle(frame, (550, 400), (80, 80), (0, 0, 255), 2)
cv2.putText(frame, "Alya Siha Nesne Takip", (10, 30), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255 ), 2)
cv2.putText(frame, "Basarili Kilitlenme : 0", (10, 60), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0,0,255),2)
cv2.putText(frame, "Veri Gonderimi : Basarili", (10, 420), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255), 2)
now = datetime.datetime.now()
current_time = now.strftime("%H:%M:%S")
cv2.putText(frame, current_time, (550, 50), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255), 2)
cv2.imshow("Alya Siha Otonom Kilitlenme", frame)
if cv2.waitKey(1) & 0xFF == ord("q"):
print("Görüntü sonlandırıldı.")
break
elapsed_time = time.time() - starting_time
fps = frame_id / elapsed_time
cv2.putText(frame, "FPS: " + str(round(fps, 10)), (10, 50), font, 1, (0, 0, 0), 3)
key = cv2.waitKey(1)
if key == 27:
break
cam.release()
cv2.destroyAllWindows()