def see(polly,camera):
camera.capture(filename)
camera.close()
topn = inception_predict.predict_from_local_file(filename, N=5)
print topn
top1 = topn[0]
# Convert probability to integer percentage
prob = (str)((int)(top1[0]*100))
# Remove category number
item = top1[1].split(' ')
item = ' '.join(item[1:])
message = "I'm "+prob+"% sure that this is a "+item+". "
return message
return ''.join(random.choice(string.lowercase) for i in range(length))
#while True:
# Create unique image name
uniqueid = 'mxnet_uuid_{0}_{1}'.format(randomword(3),strftime("%Y%m%d%H%M%S",gmtime()))
ret, frame = cap.read()
imgdir = 'images/'
filename = 'tx1_image_{0}_{1}.jpg'.format(randomword(3),strftime("%Y%m%d%H%M%S",gmtime()))
cv2.imwrite(imgdir + filename, frame)
# Run inception prediction on image
try:
topn = inception_predict.predict_from_local_file(imgdir + filename, N=5)
except:
errorcondition = "true"
# CPU Temp
f = open("/sys/devices/virtual/thermal/thermal_zone1/temp","r")
cputemp = str( f.readline() )
cputemp = cputemp.replace('\n','')
cputemp = cputemp.strip()
cputemp = str(round(float(cputemp)) / 1000)
cputempf = str(round(9.0/5.0 * float(cputemp) + 32))
f.close()
# GPU Temp
f = open("/sys/devices/virtual/thermal/thermal_zone2/temp","r")
gputemp = str( f.readline() )
#filename = '/home/pi/cap.jpg'
filename = '/tmp/cap.jpg'
# camera.start_preview()
# camera.capture(filename)
cv2.imwrite(filename, image)
vidcap.release()
# camera.stop_preview()
fin = open(filename, 'rb')
encoded_image_bytes = fin.read()
fin.close()
logging.info("Finalizando o processamento de imagem")
logging.info("Iniciando o inception_predict")
topn = inception_predict.predict_from_local_file(filename, N=2)
logging.info("Finalizando o inception_predict")
# MQTT settings
logging.info("Iniciando a insercao do label no MQTT")
topicname = 'recyclesorter/demo-' + str(datetime.now().strftime("%Y-%m-%d-%H"))
deviceid = random.choice(deviceids)
datetimenow = str(datetime.now())
myAWSIoTMQTTClient.connect()
horizonalpin = 15
vertizalpin = 12
recylefound = 0
logging.info("Finalizando a insercao do label no MQTT")
#if not use_motion_capture:
camera = picamera.PiCamera()
while True:
if use_motion_capture:
if (GPIO.input(motion_sensor_pin)):
print('Motion detected at ', timestamp())
# with picamera.PiCamera() as camera:
# camera.resolution = (1024, 1024)
time.sleep(2)
t = timestamp()
fname = image_directory + t + '.jpg'
camera.capture(fname)
print('saved image', fname)
topn, predstr = inception_predict.predict_from_local_file(fname,
N=5)
print(predstr)
with open(prediction_directory + t + '.json', 'wa') as f:
json.dump(predstr, f)
else:
# Take the jpg image from camera
print("Capturing")
filename = '/home/pi/cap.jpg'
# Show quick preview of what's being captured
camera.start_preview()
camera.capture(filename)
camera.stop_preview()
# Run inception prediction on image
print("Predicting")