# cap = cv2.VideoCapture("/home/developer/PycharmProjects/SecureIt/obj_tracking/sort_deep/MOT16/train/test.mp4")
cap = cv2.VideoCapture(-1)
# cap = cv2.VideoCapture("/home/developer/PycharmProjects/SecureIt/data/videos/People Counting Demonstration.mp4")
from tf_session.tf_session_runner import SessionRunner
session_runner = SessionRunner()
session_runner.start()
while True:
ret, image = cap.read()
if ret:
break
od_api = TFObjectDetectionAPI(
PRETRAINED_faster_rcnn_inception_resnet_v2_atrous_coco_2018_01_28,
image.shape, 'tf_api', True)
# od_api = YOLOObjectDetectionAPI('yolo_api', True)
od_ip = od_api.get_in_pipe()
od_op = od_api.get_out_pipe()
od_api.use_session_runner(session_runner)
od_api.run()
ds_api = ImageEncoder(session_runner, PRETRAINED_mars_small128, 'ds_api')
ds_ip = ds_api.get_in_pipe()
ds_op = ds_api.get_out_pipe()
ds_api.run()
viewer = None
PRETRAINED_faster_rcnn_inception_resnet_v2_atrous_coco_2018_01_28, PRETRAINED_ssd_mobilenet_v1_coco_2017_11_17
from obj_tracking.sort.sort import Sort
from tf_session.tf_session_runner import SessionRunner
tracker = Sort(max_age=120, min_hits=5) # create instance of the SORT tracker
session_runner = SessionRunner()
session_runner.start()
cap0 = cv2.VideoCapture(-1)
while True:
ret, image0 = cap0.read()
if ret:
break
detection0 = TFObjectDetectionAPI(PRETRAINED_faster_rcnn_inception_v2_coco_2018_01_28, image0.shape,
'tf_api_0', True)
detection0.use_session_runner(session_runner)
ip0 = detection0.get_in_pipe()
op0 = detection0.get_out_pipe()
detection0.run()
# cap1 = cv2.VideoCapture(1)
# while True:
# ret, image1 = cap1.read()
# if ret:
# break
#
# detection1 = TFObjectDetectionAPI(PRETRAINED_faster_rcnn_inception_v2_coco_2018_01_28, image1.shape,
# 'tf_api_1', True)
# detection1.use_session_runner(session_runner)
# ip1 = detection1.get_in_pipe()
from tf_session.tf_session_runner import SessionRunner
from tf_session.tf_session_utils import Inference
session_runner = SessionRunner()
session_runner.start()
cap = cv2.VideoCapture("/home/developer/PycharmProjects/SecureIt/data/videos/abandoned_detection/abandoned_luggage.avi")
# cap = cv2.VideoCapture('/home/developer/Downloads/shoe_tracking.mp4')
# cap = cv2.VideoCapture(0)
while True:
ret, image = cap.read()
if ret:
break
# detector = YOLOObjectDetectionAPI('yolo_api', True)
detector = TFObjectDetectionAPI(PRETRAINED_faster_rcnn_inception_v2_coco_2018_01_28, image.shape, 'tf_api', True)
detector.use_session_runner(session_runner)
detector_ip = detector.get_in_pipe()
detector_op = detector.get_out_pipe()
detector.run()
tracker = OFISTObjectTrackingAPI(flush_pipe_on_read=True)
tracker.use_session_runner(session_runner)
trk_ip = tracker.get_in_pipe()
trk_op = tracker.get_out_pipe()
tracker.run()
def read_video():
while True:
ret, image = cap.read()
Thread(target=fs.get_app().run, args=("0.0.0.0", )).start()
session_runner = {}
detector = {}
cap = {}
pipe = {}
video_inputs = {
0: 0,
1: 1,
2: 2,
3: 3,
4: 4,
6: 'rtsp://*****:*****@192.168.0.6'
}
for i in video_inputs.keys():
session_runner[i] = SessionRunner(skip=True)
session_runner[i].start()
detector[i] = TFObjectDetectionAPI(
PRETRAINED_faster_rcnn_inception_v2_coco_2018_01_28, None,
'tf_api_' + str(i), True)
detector[i].use_session_runner(session_runner[i])
detector[i].run()
cap[i] = cv2.VideoCapture(video_inputs[i])
pipe[i] = Pipe()
fs.create('feed_' + str(i), pipe[i])
Thread(target=detect_objects,
args=(cap[i], pipe[i], detector[i], False)).start()