def capture():
size = 4
vs = VideoStream(usePiCamera=1).start()
time.sleep(2.0)
#loading the xml file
classifier = cv2.CascadeClassifier('pill_classifier.xml')
sampleNum = 0
while True:
frame = vs.read()
# Resizing to speed up detection
mini = cv2.resize(frame,
(frame.shape[1] / size, frame.shape[0] / size))
# detecting using classifier
pills = classifier.detectMultiScale(mini)
# Drawing rectangles around each pill
for p in pills:
(x, y, w, h) = [v * size for v in p] #Scale the shapesize backup
cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0),
thickness=4)
#Saving the images and incrementing counter
sampleNum = sampleNum + 1
sub_pill = frame[y:y + h, x:x + w]
PillFileName = "data/pill_detected" + str(sampleNum) + ".jpg"
cv2.imwrite(PillFileName, sub_pill)
#Display captured image
cv2.imshow('img', frame)
if cv2.waitKey(50) & 0xFF == ord('q'):
break
# break if the sample number is more than 30
elif sampleNum > 29:
break
vs.quit()
cv2.destroyAllWindows()
