detector.py

import cv2
import imutils
import psutil

from utils import *


def detector_log(message: str):
    log("DTCT", message)


def detect_from_stream(input_pipe, output_pipe, pid):
    counter = 0
    firstFrame = None

    while input_pipe.poll(3) or psutil.pid_exists(pid):
        frame_string = input_pipe.recv()
        counter += 1
        if frame_string is None or frame_string == '':
            if not psutil.pid_exists(pid):
                break
            else:
                continue

        gray_frame = string_to_frame(frame_string)
        gray_frame = cv2.GaussianBlur(gray_frame, (21, 21), 0)

        # if the first frame is None, initialize it
        if firstFrame is None:
            detector_log("starting background model...")
            firstFrame = gray_frame.copy().astype("float")
            continue

        # accumulate the weighted average between the current frame and
        # previous frames, then compute the difference between the current
        # frame and running average
        cv2.accumulateWeighted(gray_frame, firstFrame, 0.05)

        frameDelta = cv2.absdiff(cv2.convertScaleAbs(gray_frame), cv2.convertScaleAbs(firstFrame))
        thresh = cv2.threshold(frameDelta, 25, 255, cv2.THRESH_BINARY)[1]

        # dilate the thresholded image to fill in holes, then find contours
        # on thresholded image
        thresh = cv2.dilate(thresh, None, iterations=2)
        cnts = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL,
            cv2.CHAIN_APPROX_SIMPLE)
        cnts = imutils.grab_contours(cnts)

        motion_rectangles = []
        # loop over the contours
        for c in cnts:
            # if the contour is too small, ignore it
            if cv2.contourArea(c) < 50:
                continue

            # compute the bounding box for the contour, draw it on the frame,
            # and update the text
            (x, y, w, h) = cv2.boundingRect(c)
            motion_rectangles += [((x, y), (x + w, y + h))]
        frame_and_detections = frame_string + "|" + str(motion_rectangles) + '\n'

        output_pipe.send(frame_and_detections)

    detector_log("finished detecting " + str(counter) + " frames")
    output_pipe.close()