Cajal-course-code/subBgStream.py at main · young24/Cajal-course-code · GitHub

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import io
import picamera # Camera

#### THIS IS IMPORTANT FOR LIFE STREAMING ####
import logging
import socketserver
from threading import Condition
from http import server

#### THIS IS IMPORTANT FOR IMAGE PROCESSING ####
import numpy as np
import cv2

PAGE="""\
<html>
<head>
<title>picamera MJPEG streaming demo</title>
</head>
<body>
<img src="stream.mjpg" width="640" height="480" style="width:100%;height:100%;" />
</body>
</html>
"""

def myFaceDetection(img):

    det = cv2.CascadeClassifier("haarcascade_frontalface_default.xml")
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    rects = det.detectMultiScale(gray,
    scaleFactor=1.1,
    minNeighbors=5,
    minSize=(80, 80), # adjust to your image size, maybe smaller, maybe larger?
    flags=cv2.CASCADE_SCALE_IMAGE)
    for (x, y, w, h) in rects:
        # x: x location
        # y: y location
        # w: width of the rectangle
        # h: height of the rectangle
        # Remember, order in images: [y, x, channel]
        cv2.rectangle(img, (x, y), (x + w, y + h), (0, 255, 0), 20)


    return gray, rects

class StreamingOutput(object):
    def __init__(self):
        self.frame = None
        self.buffer = io.BytesIO()
        self.condition = Condition()

    def write(self, buf):
        if buf.startswith(b'\xff\xd8'):
            # New frame, copy the existing buffer's content and notify all
            # clients it's available
            self.buffer.truncate()
            with self.condition:
                self.frame = self.buffer.getvalue()
                self.condition.notify_all()
            self.buffer.seek(0)
        return self.buffer.write(buf)

class StreamingHandler(server.BaseHTTPRequestHandler):


    def do_GET(self):
        self.frame_i = 0
        self.bg = np.zeros((5, 480, 640), dtype=np.uint8)
        if self.path == '/':
            self.send_response(301)
            self.send_header('Location', '/index.html')
            self.end_headers()
        elif self.path == '/index.html':
            content = PAGE.encode('utf-8')
            self.send_response(200)
            self.send_header('Content-Type', 'text/html')
            self.send_header('Content-Length', len(content))
            self.end_headers()
            self.wfile.write(content)
        elif self.path == '/stream.mjpg':
            self.send_response(200)
            self.send_header('Age', 0)
            self.send_header('Cache-Control', 'no-cache, private')
            self.send_header('Pragma', 'no-cache')
            self.send_header('Content-Type', 'multipart/x-mixed-replace; boundary=FRAME')
            self.end_headers()
            try:
                while True:
                    with output.condition:
                        output.condition.wait()
                        frame = output.frame

                        ### The image is encoded in bytes,
                        ### needs to be converted to e.g. numpy array
                        frame = cv2.imdecode(np.frombuffer(frame, dtype=np.uint8),
                                             cv2.IMREAD_COLOR)


                        ###############
                        ## HERE CAN GO ALL IMAGE PROCESSING
                        ###############


                        ## face detection
                        frame, rects = myFaceDetection(frame)

                        ## update the background
                        idxBg = self.frame_i % 5
                        self.bg[idxBg] = frame
                        bgImg = np.mean(self.bg, 0)
                        frame = frame - bgImg

                        self.frame_i = self.frame_i + 1
                        for (x, y, w, h) in rects:
                            cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 20)

                        ## thresholding
                        ret, frame = cv2.threshold(frame, 20, 255, cv2.THRESH_BINARY)

                        # Find indices where we have mass
                        mass_x, mass_y = np.where(frame > 0)
                        # mass_x and mass_y are the list of x indices and y indices of mass pixels

                        Cx = int(np.average(mass_x))
                        Cy = int(np.average(mass_y))


                        ## draw a point at the mass center
                        frame = cv2.circle(frame, (Cx, Cy), radius = 15, color = (255, 255, 255), thickness = 7) # negative number for filled circle


                        ### and now we convert it back to JPEG to stream it
                        _, frame = cv2.imencode('.JPEG', frame)

                    self.wfile.write(b'--FRAME\r\n')
                    self.send_header('Content-Type', 'image/jpeg')
                    self.send_header('Content-Length', len(frame))
                    self.end_headers()
                    self.wfile.write(frame)
                    self.wfile.write(b'\r\n')
            except Exception as e:
                logging.warning(
                    'Removed streaming client %s: %s',
                    self.client_address, str(e))
        else:
            self.send_error(404)
            self.end_headers()

class StreamingServer(socketserver.ThreadingMixIn, server.HTTPServer):
    allow_reuse_address = True
    daemon_threads = True

# Open the camera and stream a low-res image (width 640, height 480 px)
with picamera.PiCamera(resolution='640x480', framerate=24) as camera:
    camera.vflip = True # Flips image vertically, depends on your camera mounting
    output = StreamingOutput()
    camera.start_recording(output, format='mjpeg')
    try:
        address = ('', 8000) # port 8000
        server = StreamingServer(address, StreamingHandler)
        server.serve_forever()
    finally:
        camera.stop_recording()