-
Notifications
You must be signed in to change notification settings - Fork 0
/
main.py
43 lines (34 loc) · 1.26 KB
/
main.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
import cv2
# Read class names from file
classNames = []
classFile = 'labels.txt'
with open(classFile , 'rt') as f:
classNames = f.read().rstrip('\n').split('\n')
# Load pre-trained model
configPath = 'ssd_mobilenet_v3_large_coco_2020_01_14.pbtxt'
weightsPath = 'frozen_inference_graph.pb'
net = cv2.dnn_DetectionModel(weightsPath, configPath)
net.setInputSize(320, 320)
net.setInputScale(1.0/127.5)
net.setInputMean((127.5, 127.5, 127.5))
net.setInputSwapRB(True)
# Open default camera
cap = cv2.VideoCapture(0)
while True:
# Read frames from camera
ret, img = cap.read()
# Detect objects in the frame
classIds, confs, bbox = net.detect(img, confThreshold=0.5)
# Draw bounding boxes and labels for detected objects
if len(classIds) != 0:
for classId, confidence, box in zip(classIds.flatten(), confs.flatten(), bbox):
cv2.rectangle(img, box, color=(0, 255, 0), thickness=2)
cv2.putText(img, classNames[classId-1], (box[0]+10, box[1]+30), cv2.FONT_HERSHEY_COMPLEX, 1, (0, 255, 0), 2)
# Show output
cv2.imshow('Output', img)
# Exit on pressing 'q'
if cv2.waitKey(1) == ord('q'):
break
# Release camera and close windows
cap.release()
cv2.destroyAllWindows()