From 24f66840fe614458ecb50345ddab469b4dbeb712 Mon Sep 17 00:00:00 2001 From: nicorossini Date: Wed, 3 Jan 2024 20:09:58 +0100 Subject: [PATCH 1/2] object detection algorithm using YOLO v8 --- ImageRecognition/src/ObjectDetectionYOLO.py | 168 ++++++++++++++++++++ yolo-Wheights/yolov8n.pt | Bin 0 -> 6534387 bytes 2 files changed, 168 insertions(+) create mode 100644 ImageRecognition/src/ObjectDetectionYOLO.py create mode 100644 yolo-Wheights/yolov8n.pt diff --git a/ImageRecognition/src/ObjectDetectionYOLO.py b/ImageRecognition/src/ObjectDetectionYOLO.py new file mode 100644 index 0000000..e2dc365 --- /dev/null +++ b/ImageRecognition/src/ObjectDetectionYOLO.py @@ -0,0 +1,168 @@ +from ultralytics import YOLO +import cv2 +import math +import threading +import requests +import numpy as np +from skimage.metrics import structural_similarity as ssim +from sklearn.metrics import mean_squared_error + +#model +model = YOLO("yolo-Wheights/yolov8n.pt") +#class of YOLO +classNames = ["person", "bicycle", "car", "motorbike", "aeroplane", "bus", "train", "truck", "boat", + "traffic light", "fire hydrant", "stop sign", "parking meter", "bench", "bird", "cat", + "dog", "horse", "sheep", "cow", "elephant", "bear", "zebra", "giraffe", "backpack", "umbrella", + "handbag", "tie", "suitcase", "frisbee", "skis", "snowboard", "sports ball", "kite", "baseball bat", + "baseball glove", "skateboard", "surfboard", "tennis racket", "bottle", "wine glass", "cup", + "fork", "knife", "spoon", "bowl", "banana", "apple", "sandwich", "orange", "broccoli", + "carrot", "hot dog", "pizza", "donut", "cake", "chair", "sofa", "pottedplant", "bed", + "diningtable", "toilet", "tvmonitor", "laptop", "mouse", "remote", "keyboard", "cell phone", + "microwave", "oven", "toaster", "sink", "refrigerator", "book", "clock", "vase", "scissors", + "teddy bear", "hair drier", "toothbrush" + ] + +cam1 = 'rtsp://192.168.1.41:80/ch0_0.264' +cam2 = 'rtsp://192.168.1.41:80/ch1_0.264' +cam3 = 'rtsp://192.168.1.41:80/ch2_0.264' +cam4 = 'rtsp://192.168.1.41:80/ch3_0.264' +cam5 = 'rtsp://192.168.1.41:80/ch4_0.264' +cam6 = 'rtsp://192.168.1.41:80/ch5_0.264' +cam7 = 'rtsp://192.168.1.41:80/ch6_0.264' +cam8 = 'rtsp://192.168.1.41:80/ch7_0.264' + +#setting of telegram +TOKEN = '6929905186:AAEouI3G2sbfS-y6ZzkXrpNgPQRAPs5_v-g' +channel_id = '792557360' + +last_sent_image = None + +def post_request(image): + global last_sent_image + apiURL = f"https://api.telegram.org/bot{TOKEN}/sendPhoto?chat_id={channel_id}" + + if last_sent_image is None: + last_sent_image = image + try: + response = requests.post(apiURL, files={'photo': image}) + print("Status code is: ", response.status_code) + except requests.exceptions.RequestException as e: + print("There was an exception that occurred while handling your request.", e) + else: + + # Resizing + flat_last_sent_image = last_sent_image.flatten() + flat_image = image.flatten() + min_len = min(len(flat_last_sent_image), len(flat_image)) + r_last_sent_image = cv2.resize(flat_last_sent_image.reshape(1, -1), (min_len, 1)) + r_image = cv2.resize(flat_image.reshape(1, -1), (min_len, 1)) + + #mean squared error + mse = mean_squared_error(r_last_sent_image, r_image) + print("MEAN SQUARED ERROR is: ", mse) + if mse > 105.85: + try: + response = requests.post(apiURL, files={'photo': image}) + print("Status code is: ", response.status_code) + + if response.status_code == 200: + last_sent_image = image + except requests.exceptions.RequestException as e: + print("There was an exception that occurred while handling your request.", e) + + + + +#filename = url of cam +#file_index = index of the file that can be assigned to each thread. cam1 has file_index as 1, cam2 has file_index as 2... +def detection(filename, file_index): + cap = cv2.VideoCapture(filename) # Read the video file + global last_sent_image + + while cap.isOpened(): + + success, img = cap.read() + # Exit the loop if no more frames in either video + if not success: + break + + results = model(img, stream = True, classes = 0, conf=0.5) + foundPerson = False + #coordinates + for r in results: + boxes = r.boxes + for box in boxes: + #bounding box + x1, y1, x2, y2 = box.xyxy[0] + x1, y1, x2, y2 = int(x1), int(y1), int(x2), int(y2) # convert to int values + # put box in cam + cv2.rectangle(img, (x1, y1), (x2, y2), (255, 0, 255), 3) + # confidence + confidence = math.ceil((box.conf[0]*100))/100 + print("Confidence --->",confidence) + # class name + cls = int(box.cls[0]) + print("Class name -->", classNames[cls]) + + foundPerson = True + + if(foundPerson): + _, img_encoded = cv2.imencode('.jpg', img) + post_request(img_encoded) + + + cap.release() + + + +#initialize thread +detect_thread1 = threading.Thread(target=detection, + args=(cam1, 1), + daemon=True) + +detect_thread2 = threading.Thread(target=detection, + args=(cam2, 2), + daemon=True) + +detect_thread3 = threading.Thread(target=detection, + args=(cam3, 3), + daemon=True) + +detect_thread4 = threading.Thread(target=detection, + args=(cam4, 4), + daemon=True) + +detect_thread5 = threading.Thread(target=detection, + args=(cam5, 5), + daemon=True) + +detect_thread6 = threading.Thread(target=detection, + args=(cam6, 6), + daemon=True) + +detect_thread7 = threading.Thread(target=detection, + args=(cam7, 7), + daemon=True) + +detect_thread8 = threading.Thread(target=detection, + args=(cam8, 8), + daemon=True) + +#start thread +detect_thread1.start() +detect_thread2.start() +detect_thread3.start() +detect_thread4.start() +detect_thread5.start() +detect_thread6.start() +detect_thread7.start() +detect_thread8.start() + +detect_thread1.join() +detect_thread2.join() +detect_thread3.join() +detect_thread4.join() +detect_thread5.join() +detect_thread6.join() +detect_thread7.join() +detect_thread8.join() \ No newline at end of file diff --git a/yolo-Wheights/yolov8n.pt b/yolo-Wheights/yolov8n.pt new file mode 100644 index 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