门店客流统计)

门店客流统计

• 代码部分
• 效果

代码部分

import cv2
import numpy as np
from tracker import *
import cvzone
import time

bg_subtractor = cv2.createBackgroundSubtractorMOG2(history=200, varThreshold=140)

# Open a video capture
video_capture = cv2.VideoCapture(r"store.mp4")


def RGB(event, x, y, flags, param):
    if event == cv2.EVENT_MOUSEMOVE:
        point = [x, y]
        print(point)


cv2.namedWindow('RGB')
cv2.setMouseCallback('RGB', RGB)
tracker = Tracker()

area1 = [(213, 165), (200, 189), (693, 373), (697, 341)]
area2 = [(195, 199), (186, 213), (683, 404), (689, 388)]
er = {}
counter1 = []
ex = {}
counter2 = []
while True:
    ret, frame = video_capture.read()
    if not ret:
        break

    frame = cv2.resize(frame, (1028, 500))

    mask = bg_subtractor.apply(frame)
    _, mask = cv2.threshold(mask, 245, 255, cv2.THRESH_BINARY)
    contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
    list = []
    for cnt in contours:
        area = cv2.contourArea(cnt)
        if area > 1500:
            # cv2.drawContours(frame, [cnt], -1, (0, 255, 0), 2)
            x, y, w, h = cv2.boundingRect(cnt)
            list.append([x, y, w, h])
    bbox_idx = tracker.update(list)
    for bbox in bbox_idx:
        x1, y1, x2, y2, id = bbox
        cx = int(x1 + x1 + x2) // 2
        cy = int(y1 + y1 + y2) // 2
        result = cv2.pointPolygonTest(np.array(area1, np.int32), ((cx, cy)), False)
        if result >= 0:
            er[id] = (cx, cy)
        if id in er:
            result1 = cv2.pointPolygonTest(np.array(area2, np.int32), ((cx, cy)), False)
            if result1 >= 0:
                cv2.rectangle(frame, (x1, y1), (x2 + x1, y2 + y1), (0, 255, 0), 3)
                cvzone.putTextRect(frame, f'{id}', (cx, cy), 2, 2)
                cv2.circle(frame, (cx, cy), 5, (0, 255, 0), -1)
                if counter1.count(id) == 0:
                    counter1.append(id)

        result2 = cv2.pointPolygonTest(np.array(area2, np.int32), ((cx, cy)), False)
        if result2 >= 0:
            ex[id] = (cx, cy)
        if id in ex:
            result3 = cv2.pointPolygonTest(np.array(area1, np.int32), ((cx, cy)), False)
            if result3 >= 0:
                cv2.rectangle(frame, (x1, y1), (x2 + x1, y2 + y1), (0, 0, 255), 3)
                cvzone.putTextRect(frame, f'{id}', (cx, cy), 2, 2)
                cv2.circle(frame, (cx, cy), 5, (0, 255, 0), -1)
                if counter2.count(id) == 0:
                    counter2.append(id)

    cv2.polylines(frame, [np.array(area1, np.int32)], True, (0, 0, 255), 2)
    cv2.polylines(frame, [np.array(area2, np.int32)], True, (0, 0, 255), 2)

    Enter = len(counter1)
    Exit = len(counter2)
    cvzone.putTextRect(frame, f'ENTER:-{Enter}', (50, 60), 2, 2)
    cvzone.putTextRect(frame, f'EXIT:-{Exit}', (50, 130), 2, 2)

    cv2.imshow('RGB', frame)
    time.sleep(0.01)
    if cv2.waitKey(1) & 0xFF == 27:  # Press 'Esc' to exit
        break

# Release the video capture and close windows
video_capture.release()
cv2.destroyAllWindows()

import math


class Tracker:
    def __init__(self):
        # Store the center positions of the objects
        self.center_points = {}
        # Keep the count of the IDs
        # each time a new object id detected, the count will increase by one
        self.id_count = 0


    def update(self, objects_rect):
        # Objects boxes and ids
        objects_bbs_ids = []

        # Get center point of new object
        for rect in objects_rect:
            x, y, w, h = rect
            cx = (x + x + w) // 2
            cy = (y + y + h) // 2

            # Find out if that object was detected already
            same_object_detected = False
            for id, pt in self.center_points.items():
                dist = math.hypot(cx - pt[0], cy - pt[1])

                if dist < 35:
                    self.center_points[id] = (cx, cy)
#                    print(self.center_points)
                    objects_bbs_ids.append([x, y, w, h, id])
                    same_object_detected = True
                    break

            # New object is detected we assign the ID to that object
            if same_object_detected is False:
                self.center_points[self.id_count] = (cx, cy)
                objects_bbs_ids.append([x, y, w, h, self.id_count])
                self.id_count += 1

        # Clean the dictionary by center points to remove IDS not used anymore
        new_center_points = {}
        for obj_bb_id in objects_bbs_ids:
            _, _, _, _, object_id = obj_bb_id
            center = self.center_points[object_id]
            new_center_points[object_id] = center

        # Update dictionary with IDs not used removed
        self.center_points = new_center_points.copy()
        return objects_bbs_ids

效果