rendi.eka.putra/People-Counting-in-Real-Time
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fix: fix args config

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rendies 2023-01-12 19:34:42 +07:00
parent 8bb25650d1
commit 1fe9bc33b6
1 changed files with 32 additions and 19 deletions
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51
RunCounting.py
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@ -25,24 +25,24 @@ app = Flask(__name__)
cors = CORS(app) cors = CORS(app)
app.config['CORS_HEADERS'] = 'Content-Type' app.config['CORS_HEADERS'] = 'Content-Type'
def run(): def run(args):
global outputFrame, lock, people_count global outputFrame, lock, people_count
# construct the argument parse and parse the arguments # construct the argument parse and parse the arguments
ap = argparse.ArgumentParser() # ap = argparse.ArgumentParser()
ap.add_argument("-p", "--prototxt", required=False, # ap.add_argument("-p", "--prototxt", required=False,
help="path to Caffe 'deploy' prototxt file") # help="path to Caffe 'deploy' prototxt file")
ap.add_argument("-m", "--model", required=True, # ap.add_argument("-m", "--model", required=True,
help="path to Caffe pre-trained model") # help="path to Caffe pre-trained model")
ap.add_argument("-i", "--input", type=str, # ap.add_argument("-i", "--input", type=str,
help="path to optional input video file") # help="path to optional input video file")
ap.add_argument("-o", "--output", type=str, # ap.add_argument("-o", "--output", type=str,
help="path to optional output video file") # help="path to optional output video file")
# confidence default 0.4 # # confidence default 0.4
ap.add_argument("-c", "--confidence", type=float, default=0.4, # ap.add_argument("-c", "--confidence", type=float, default=0.4,
help="minimum probability to filter weak detections") # help="minimum probability to filter weak detections")
ap.add_argument("-s", "--skip-frames", type=int, default=30, # ap.add_argument("-s", "--skip-frames", type=int, default=30,
help="# of skip frames between detections") # help="# of skip frames between detections")
args = vars(ap.parse_args()) # args = vars(ap.parse_args())
# initialize the list of class labels MobileNet SSD was trained to # initialize the list of class labels MobileNet SSD was trained to
# detect # detect
@ -392,13 +392,26 @@ def video_feed():
if __name__ == '__main__': if __name__ == '__main__':
# construct the argument parser and parse command line arguments # construct the argument parser and parse command line arguments
ap = argparse.ArgumentParser() ap = argparse.ArgumentParser()
ap.add_argument("-i", "--ip", type=str, default="0.0.0.0", ap.add_argument("-t", "--ip", type=str, default="0.0.0.0",
help="ip address of the device") help="ip address of the device")
ap.add_argument("-o", "--port", type=int, default=8081, ap.add_argument("-u", "--port", type=int, default=8081,
help="ephemeral port number of the server (1024 to 65535)") help="ephemeral port number of the server (1024 to 65535)")
ap.add_argument("-p", "--prototxt", required=False,
help="path to Caffe 'deploy' prototxt file")
ap.add_argument("-m", "--model", required=True,
help="path to Caffe pre-trained model")
ap.add_argument("-i", "--input", type=str,
help="path to optional input video file")
ap.add_argument("-o", "--output", type=str,
help="path to optional output video file")
# confidence default 0.4
ap.add_argument("-c", "--confidence", type=float, default=0.4,
help="minimum probability to filter weak detections")
ap.add_argument("-s", "--skip-frames", type=int, default=30,
help="# of skip frames between detections")
args = vars(ap.parse_args()) args = vars(ap.parse_args())
# start a thread that will perform motion detection # start a thread that will perform motion detection
t = threading.Thread(target=run) t = threading.Thread(target=run, args=(args))
t.daemon = True t.daemon = True
t.start() t.start()
# start the flask app # start the flask app