Web streamer initial commit
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templates/index.html
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templates/index.html
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<html>
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<head>
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<title>rPi KVM by Petrkr</title>
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</head>
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<body>
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<h1>rPi KVM by Petrkr</h1>
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<img src="{{ url_for('video_feed') }}">
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</body>
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</html>
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webstreaming.py
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webstreaming.py
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from flask import Response
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from flask import Flask
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from flask import render_template
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import threading
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import argparse
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import datetime
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import imutils
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import time
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import cv2
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outputFrame = None
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lock = threading.Lock()
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# initialize a flask object
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app = Flask(__name__)
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cap = cv2.VideoCapture(0)
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cap.set(cv2.CAP_PROP_FRAME_WIDTH, 1920)
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cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 1080)
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time.sleep(1.0)
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@app.route("/")
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def index():
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# return the rendered template
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return render_template("index.html")
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def detect_motion(frameCount):
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global vs, outputFrame, lock
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while True:
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flag, frame = cap.read()
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if not flag:
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continue
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timestamp = datetime.datetime.now()
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cv2.putText(frame, timestamp.strftime(
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"%A %d %B %Y %I:%M:%S%p"), (10, frame.shape[0] - 10),
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cv2.FONT_HERSHEY_SIMPLEX, 0.35, (0, 0, 255), 1)
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with lock:
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outputFrame = frame.copy()
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def generate():
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global outputFrame, lock
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while True:
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with lock:
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if outputFrame is None:
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continue
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(flag, encodedImage) = cv2.imencode(".jpg", outputFrame)
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# ensure the frame was successfully encoded
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if not flag:
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continue
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# yield the output frame in the byte format
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yield(b'--frame\r\n' b'Content-Type: image/jpeg\r\n\r\n' +
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bytearray(encodedImage) + b'\r\n')
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@app.route("/video_feed")
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def video_feed():
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# return the response generated along with the specific media
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# type (mime type)
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return Response(generate(),
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mimetype = "multipart/x-mixed-replace; boundary=frame")
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# check to see if this is the main thread of execution
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if __name__ == '__main__':
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# construct the argument parser and parse command line arguments
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ap = argparse.ArgumentParser()
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ap.add_argument("-i", "--ip", type=str, required=True,
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help="ip address of the device")
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ap.add_argument("-o", "--port", type=int, required=True,
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help="ephemeral port number of the server (1024 to 65535)")
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ap.add_argument("-f", "--frame-count", type=int, default=32,
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help="# of frames used to construct the background model")
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args = vars(ap.parse_args())
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# start a thread that will perform motion detection
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t = threading.Thread(target=detect_motion, args=(
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args["frame_count"],))
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t.daemon = True
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t.start()
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# start the flask app
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app.run(host=args["ip"], port=args["port"], debug=True,
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threaded=True, use_reloader=False)
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