started

.gitignore

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+
+data.json
+
+imgs/*
+
+__pycache__/
+
+.vscode/

mon.py

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+import requests
+import json
+import telebot
+import numpy as np
+import cv2
+
+import time
+
+login = "./data.json"
+loginDataJson = {}
+
+photos = "./imgs/"
+url = "http://192.168.178.25:8000/stream.mjpg"
+
+def checkCam():
+    cap = cv2.VideoCapture(url)
+    r, img = cap.read()
+    return img
+
+def saveImage(img):
+    name =  '{0:010x}'.format(int(time.time() * 256))[:10]
+    path = photos + name + '.png'
+    cv2.imwrite(path, img)
+    return path
+
+def notify(path):
+    global loginDataJson
+    photo = open(path, "rb")
+    json1 = {"chat_id": loginDataJson["chat_id"]}
+    files = {'photo': photo}
+    print(requests.post("https://api.telegram.org/bot" + loginDataJson["key"] + "/sendPhoto", json1, files=files))
+
+def loadLogin():
+    global loginDataJson
+    with open(login,  'r', encoding='utf-8') as f:
+        loginData = f.read()
+        loginDataJson = json.loads(loginData)
+
+loadLogin()
+

motion_detector.py

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+# USAGE
+# python motion_detector.py
+# python motion_detector.py --video videos/example_01.mp4
+
+# import the necessary packages
+from imutils.video import VideoStream
+import argparse
+import datetime
+import imutils
+import time
+import cv2
+import mon
+
+
+
+def increase_brightness(img, value=30):
+    hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
+    h, s, v = cv2.split(hsv)
+
+    lim = 255 - value
+    v[v > lim] = 255
+    v[v <= lim] += value
+
+    final_hsv = cv2.merge((h, s, v))
+    img = cv2.cvtColor(final_hsv, cv2.COLOR_HSV2BGR)
+
+    return img
+
+def compare(url):
+    # construct the argument parser and parse the arguments
+    ap = argparse.ArgumentParser()
+    ap.add_argument("-v", "--video", help="path to the video file")
+    ap.add_argument("-amin", "--min-area", type=int, default=3000, help="minimum area size")
+    ap.add_argument("-amax", "--max-area", type=int, default=10000, help="minimum area size")
+    args = vars(ap.parse_args())
+
+    # if the video argument is None, then we are reading from webcam
+    args["video"] = url
+    #args["video"] = "./videos/example_02.mp4"
+    vs = cv2.VideoCapture(args["video"])
+    counter = 0
+    threashold = 18
+    delay = .3
+    framerate = 30
+
+    # initialize the first frame in the video stream
+    firstFrame = None
+
+    # loop over the frames of the video
+    while True:
+        try:
+            # grab the current frame and initialize the occupied/unoccupied
+            # text
+            frame = vs.read()
+            frame = frame if args.get("video", None) is None else frame[1]
+            text = "Unoccupied"
+
+            # if the frame could not be grabbed, then we have reached the end
+            # of the video
+            if frame is None:
+                break
+
+            # resize the frame, convert it to grayscale, and blur it
+            frame = imutils.resize(frame, width=500)
+            #frame = increase_brightness(frame, value=50)
+            gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+            gray = cv2.GaussianBlur(gray, (31, 31), 0)
+
+            # if the first frame is None, initialize it
+            if firstFrame is None:
+                firstFrame = gray
+                continue
+
+            # compute the absolute difference between the current frame and
+            # first frame
+            frameDelta = cv2.absdiff(gray, firstFrame)
+
+            thresh = cv2.threshold(frameDelta, threashold, 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)
+
+            # loop over the contours
+            for c in cnts:
+                # if the contour is too small, ignore it
+                if cv2.contourArea(c) < args["min_area"]:
+                    continue
+                if cv2.contourArea(c) > args["max_area"]:
+                    continue
+                # compute the bounding box for the contour, draw it on the frame,
+                # and update the text
+
+                print(cv2.contourArea(c))
+
+                (x, y, w, h) = cv2.boundingRect(c)
+                cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
+                text = "Occupied"
+
+            # draw the text and timestamp on the frame
+            cv2.putText(frame, "Room Status: {}".format(text), (10, 20),
+                cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255), 2)
+            cv2.putText(frame, datetime.datetime.now().strftime("%A %d %B %Y %I:%M:%S%p"),
+                (10, frame.shape[0] - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.35, (0, 0, 255), 1)
+
+            if text == "Occupied":
+                img = frame
+                location = mon.saveImage(img)
+                mon.notify(location)
+
+            key = cv2.waitKey(1) & 0xFF
+
+            counter+=1
+            if counter % (framerate * delay) == 0:
+                firstFrame = gray
+        except:
+            # cleanup the camera and close any open windows
+            vs.stop() if args.get("video", None) is None else vs.release()
+            print("error")
+            time.sleep(10)
+
+    
+
+
+compare("http://192.168.178.25:8000/stream.mjpg")