main.py

import cv2
import cvzone
import math
from ultralytics import YOLO

cap = cv2.VideoCapture('fall.mp4')

model = YOLO('yolov8s.pt')

classnames = []
with open('classes.txt', 'r') as f:
    classnames = f.read().splitlines()


while True:
    ret, frame = cap.read()
    frame = cv2.resize(frame, (980,740))

    results = model(frame)

    for info in results:
        parameters = info.boxes
        for box in parameters:
            x1, y1, x2, y2 = box.xyxy[0]
            x1, y1, x2, y2 = int(x1), int(y1), int(x2), int(y2)
            confidence = box.conf[0]
            class_detect = box.cls[0]
            class_detect = int(class_detect)
            class_detect = classnames[class_detect]
            conf = math.ceil(confidence * 100)


            # implement fall detection using the coordinates x1,y1,x2
            height = y2 - y1
            width = x2 - x1
            threshold  = height - width

            if conf > 80 and class_detect == 'person':
                cvzone.cornerRect(frame, [x1, y1, width, height], l=30, rt=6)
                cvzone.putTextRect(frame, f'{class_detect}', [x1 + 8, y1 - 12], thickness=2, scale=2)
            
            if threshold < 0:
                cvzone.putTextRect(frame, 'Fall Detected', [height, width], thickness=2, scale=2)
            
            else:pass


    cv2.imshow('frame', frame)
    if cv2.waitKey(1) & 0xFF == ord('t'):
        break


cap.release()
cv2.destroyAllWindows()