def __init__(self):
# Using OpenCV to capture from device 0. If you have trouble capturing
# from a webcam, comment the line below out and use a video file
# instead.
# self.video = cv2.VideoCapture(0)
self.video = cv2.VideoCapture(cameraIPURL)
self.motionDetector = MotionDetector()
def main():
logging.basicConfig(level=logging.INFO)
puntosHomography = []
config = FileReader(parse_args().config_file)
image_file = config.getProp('image_file')
video_file = config.getProp('video_file')
data_file = config.getProp('data_file')
start_frame = int(config.getProp('start_frame'))
folder_photos = config.getProp('folder_photos')
folder_photos_mobile = config.getProp('folder_photos_mobile')
response = login().json()
question1 = "¿Quiere configurar los estacionemiento? Escriba S/N!"
if (QuestionInput.realize(question1)):
drawCoordinates(image_file, data_file, response['token'])
else:
print("Bicicleteros:")
res = getAllBicycleParkings(response['token'])
question1_2 = "Elija un número de bicicletero existente:"
if (QuestionInput.realizeNumberBicycle(question1_2) == 1):
data_file = config.getProp('cache_data_file')
question2 = "¿Quiere configurar con homografia el estacionemiento? Escriba S/N!"
if (QuestionInput.realize(question2)):
puntosHomography = get_image_homography(image_file)
with open(data_file, "r") as data:
points = yaml.load(data)
#response = login().json()
detector = MotionDetector(video_file, points, int(start_frame),
folder_photos, response['token'],
folder_photos_mobile)
detector.detect_motion(puntosHomography)
def frameProcessor(queue):
#processes and deals with motion capture
out = DatasetSaver("test/testPic",
mode='picture',
maxPics=1000,
maxSpaceMb=20,
debug=dataset_config.debug)
detector = MotionDetector(minMovementArea=dataset_config.min_area,
debug=dataset_config.debug)
prev_frame = None
while True:
frame = queue.get(
True) #True -> block until there is a frame in the queue
if prev_frame is None:
prev_frame = frame
continue
if detector.isMovement(prev_frame, frame):
if dataset_config.show:
cv2.imshow("Saved_Frame", frame)
out.write(frame)
prev_frame = frame
if cv2.waitKey(1) & 0xFF == ord('q'):
break
out.release() #Doesn't do anything since it's picture mode
cv2.destroyAllWindows()
def test_right_swipe2(self):
logger.info("Testing Right Swipe2")
md = MotionDetector("ZoeticRightSwipe2")
md.update([20, 20, 20, 2000, 20, 20])
md.update([20, 20, 20, 2000, 20, 20])
md.update([20, 20, 20, 2000, 20, 20])
md.update([2000, 2000, 20, 20, 20, 20])
md.update([2000, 2000, 20, 20, 20, 20])
md.update([20, 20, 20, 20, 2000, 20])
del md
def test_left_swipe(self):
logger.info("Testing Left Swipe")
md = MotionDetector("ZoeticLeftSwipe")
md.update([20, 20, 20, 20, 2000, 20])
md.update([2000, 2000, 20, 20, 20, 20])
md.update([20, 20, 20, 2000, 20, 20])
del md
def test_delayed_swipe(self):
logger.info("Testing Delayed Swipe")
md = MotionDetector("ZoeticDelayedSwipe")
md.update([20, 20, 20, 2000, 20, 20])
time.sleep(0.5)
md.update([2000, 2000, 20, 20, 20, 20])
time.sleep(0.5)
md.update([20, 20, 20, 20, 2000, 20])
del md
logger.info("\n\n")
class VideoCamera(object):
def __init__(self):
# Using OpenCV to capture from device 0. If you have trouble capturing
# from a webcam, comment the line below out and use a video file
# instead.
# self.video = cv2.VideoCapture(0)
self.video = cv2.VideoCapture(cameraIPURL)
self.motionDetector = MotionDetector()
def __del__(self):
self.video.release()
def get_frame(self):
ret, frame = self.video.read()
detectFrame = self.motionDetector.detect(frame)
ret, jpeg = cv2.imencode('.jpg', detectFrame)
return jpeg.tobytes()
def save_frame_to_image(self, path):
ret, frame = self.video.read()
try:
cv2.imwrite(path, frame)
except IOError:
pass
import time
from networkConnection import NetworkConnection
from motionDetector import MotionDetector
from broker import Broker
DETECTOR_PIN = 34
connection = NetworkConnection()
connection.do_connect()
print("is connected: " + str(connection.isConnected()))
motionDetector = MotionDetector(DETECTOR_PIN)
broker = Broker()
while True:
time.sleep(1)
if not connection.isConnected():
connection.do_connect()
if motionDetector.check() == True:
broker.objectDetected()
#!/usr/bin/env python
import sys
import Image
import ImageChops
from motionDetector import MotionDetector
from Filters.filter import Filter
from Filters.erosion import ErosionFilter
from Filters.difference import DifferenceFilter
from Filters.threshold import ThresholdFilter
if __name__ == '__main__':
if len(sys.argv) != 2:
print 'Usage:', sys.argv[0], '<image1> <image2'
sys.exit(1)
motion = MotionDetector(sys.argv[1])
motion.launchCPU()
from motionDetector import MotionDetector
from dataset_config import save_location, min_area, show, debug
###Setting up IP camera
os.system("sudo /home/nvidia/setup_camera.sh")
#cap = cv2.VideoCapture('rtsp://*****:*****@169.254.132.241:554/h264/ch1/main/av_stream')
cap = RobustCamera(0)
out = DatasetSaver(
"test/testPics", # should become test/testPic_0 etc
mode='picture',
maxPics=1000,
maxSpaceMb=100,
debug=debug) # 100mb
detector = MotionDetector(minMovementArea=min_area, debug=debug)
#backgroundFrame = cv2.imread("backgroundImage.jpg")
prev_frame = None # for motion detection
while True:
#out = cv2.VideoWriter('video_' + str(start_count) + "_" + dt_string + '.avi',cv2.VideoWriter_fourcc('D','I','V','X'), 30, (1280,720))
#out = cv2.VideoWriter(video_string_name, cv2.VideoWriter_fourcc('D','I','V','X'), 30, (1280,720))
ret, frame = cap.read()
frame = cv2.resize(frame, (1280, 720))
#height, width = frame.shape[:2]
if prev_frame is None:
prev_frame = frame #so that prev_frame is not none
continue