def loop():
n = 0
while True:
yield n
n += 1
if __name__ == "__main__":
webcam = args.webcam
mode = args.mode
if not os.path.exists(args.outputpath):
os.mkdir(args.outputpath)
# Load input video
fvs = WebcamLoader(webcam).start()
(fourcc, fps, frameSize) = fvs.videoinfo()
# Data writer
save_path = os.path.join(args.outputpath,
'AlphaPose_webcam' + webcam + '.avi')
writer = DataWriter(args.save_video, save_path,
cv2.VideoWriter_fourcc(*'XVID'), fps,
frameSize).start()
# Load YOLO model
print('Loading YOLO model..')
sys.stdout.flush()
det_model = Darknet("yolo/cfg/yolov3.cfg")
det_model.load_weights('models/yolo/yolov3.weights')
det_model.net_info['height'] = args.inp_dim
det_inp_dim = int(det_model.net_info['height'])
while True:
yield n
n += 1
if __name__ == '__main__':
url_1 = "rtsp://*****:*****@192.168.200.253:554/Streaming/Channels/101"
url_2 = "rtsp://*****:*****@192.168.200.253:554/Streaming/Channels/301"
num_cam = 2
webcam = args.webcam
if not os.path.exists(args.outputpath):
os.mkdir(args.outputpath)
# Load input video
fvs_0 = WebcamLoader(url_1).start()
fvs_1 = WebcamLoader(url_2).start()
(fourcc, fps, frameSize) = fvs_0.videoinfo()
# read the camera parameter of this dataset
# with open ( opt.camera_parameter_path,'rb' ) as f:
# camera_parameter = pickle.load (f)
# Data writer
save_path = os.path.join(args.outputpath,
'AlphaPose_webcam' + webcam + '.avi')
writer = DataWriter(args.save_video, save_path,
cv2.VideoWriter_fourcc(*'XVID'), fps,
frameSize).start()
img, orig_img, dim = prep_frame(frame, inp_dim)
im_dim_list = torch.FloatTensor([dim]).repeat(1, 2)
return img, orig_img, dim, im_dim_list
if __name__ == '__main__':
url_1 = "rtsp://*****:*****@192.168.200.253:554/Streaming/Channels/101"
url_2 = "rtsp://*****:*****@192.168.200.253:554/Streaming/Channels/301"
num_cam = 2
webcam = args.webcam
if not os.path.exists(args.outputpath):
os.mkdir(args.outputpath)
# Load input video
fvs_0 = WebcamLoader(url_1).start()
fvs_1 = WebcamLoader(url_2).start()
# detection module
print('Loading detection model ')
sys.stdout.flush()
det_model = inference.yolo_detecter()
# pose module
print('Loading pose model')
sys.stdout.flush()
pose_model = inference.pose_detection()
print('Starting webcam demo, press Ctrl + C to terminate...')
sys.stdout.flush()
im_names_desc = loop() # tqdm(loop())
def isfull(self):
return self.Q.full()
if __name__ == '__main__':
url_1 = "rtsp://*****:*****@192.168.200.253:554/Streaming/Channels/101"
# url_1 = 0
url_2 = "rtsp://*****:*****@192.168.200.253:554/Streaming/Channels/301"
# url_2 = 0
webcam = args.webcam
if not os.path.exists(args.outputpath):
os.mkdir(args.outputpath)
# Load input video
fvs_0 = WebcamLoader(url_1).start()
fvs_1 = WebcamLoader(url_2).start()
(fourcc, fps1, frameSize1) = fvs_0.videoinfo()
(fourcc, fps2, frameSize2) = fvs_1.videoinfo()
# read the camera parameter of this dataset
# with open ( opt.camera_parameter_path,'rb' ) as f:
# camera_parameter = pickle.load (f)
# detection module
print('Loading detection model ')
sys.stdout.flush()
det_loader_1 = DetectionLoader(fvs_0, batchSize=1).start()
det_loader_2 = DetectionLoader(fvs_1, batchSize=1).start()
save_path = os.path.join(args.outputpath,