RaspBerry Pi4 with OpenVion and Movidius

 1 import cv2 as cv
 2 import sys
 3 import logging as log
 4 
 5 # openvino_fd_myriad.py
 6 filename =‘./‘
 7 
 8 log.basicConfig(format="[ %(levelname)s ] %(message)s", level=log.INFO, stream=sys.stdout)
 9 
10 if len(sys.argv) > 1 :
11     filename = filename + sys.argv[1]
12 else:
13     filename = filename + ‘Girls.jpg‘
14     
15 log.info("Image is " + filename)
16 # Load the model.
17 net = cv.dnn.readNet(‘face-detection-adas-0001.xml‘,‘face-detection-adas-0001.bin‘)
18 
19 # Specify target device.
20 
21 net.setPreferableTarget(cv.dnn.DNN_TARGET_MYRIAD)
22 
23 log.info("Inference model is face-detection-adas-0001")
24 # Read an image.
25 frame = cv.imread(filename)
26 
27 if frame is None:
28     raise Exception(‘Image not found!‘)
29 
30 log.info("Perform an inference " + filename)
31 # Prepare input blob and perform an inference.
32 blob = cv.dnn.blobFromImage(frame, size=(672, 384), ddepth=cv.CV_8U)
33 net.setInput(blob)
34 out = net.forward()
35 
36 i = 0
37 # Draw detected faces on the frame.
38 for detection in out.reshape(-1, 7):
39     confidence = float(detection[2])
40     xmin = int(detection[3] * frame.shape[1])
41     ymin = int(detection[4] * frame.shape[0])
42     xmax = int(detection[5] * frame.shape[1])
43     ymax = int(detection[6] * frame.shape[0])
44     if confidence > 0.5:
45         cv.rectangle(frame, (xmin, ymin), (xmax, ymax), color=(0, 255, 0), thickness=1)
46         cv.rectangle(frame, (xmin-1, ymin-1),(xmin+70, ymin-10), color=(0, 255, 0), thickness= -1)
47         i = i + 1
48         cv.putText(frame, ‘Human : ‘ + str(i) + ‘ ‘ + str(confidence) , (xmin, ymin -2), cv.FONT_HERSHEY_SIMPLEX, 0.3, (0,0,0), thickness=1)
49 
50 # Save the frame to an image file.
51 cv.imwrite(filename + ‘_out.png‘, frame)
52 log.info("Save the frame to an image file as png : " + filename)