yolov8 区域计数

1. 基础

本项目是在 Windows+YOLOV8环境配置 的基础上实现的，测距原理可见上边文章

2. 计数功能

2.1 计数模块

在指定区域内计数模块

def count_objects_in_region(boxes, region_points):
    """
    在指定区域内计数物体
    """
    count = 0
    for box in boxes:
        x_center, y_center, width, height = box
        center_point = (int(x_center), int(y_center))
        if is_inside_region(center_point, region_points):
            count += 1
    return count

2.2 判断模块

def is_inside_region(point, region_points):
    """
    判断点是否在指定区域内
    """
    return cv2.pointPolygonTest(np.array(region_points), point, False) >= 0

3. 主代码

import cv2
import numpy as np
from ultralytics import YOLO


def is_inside_region(point, region_points):
    """
    判断点是否在指定区域内
    """
    return cv2.pointPolygonTest(np.array(region_points), point, False) >= 0

def count_objects_in_region(boxes, region_points):
    """
    在指定区域内计数物体
    """
    count = 0
    for box in boxes:
        x_center, y_center, width, height = box
        center_point = (int(x_center), int(y_center))
        if is_inside_region(center_point, region_points):
            count += 1
    return count

def detect():

    model = YOLO("yolov8n.pt")
    cv2.namedWindow('Speed Estimation', cv2.WINDOW_NORMAL)
    cv2.resizeWindow('Speed Estimation', 1280, 360)  # 设置宽高
    cap = cv2.VideoCapture('ultralytics/assets/a3.mp4')
    out_video = cv2.VideoWriter('output.avi', cv2.VideoWriter_fourcc(*'XVID'), 30, (2560, 720))

    region_points = [(20, 20), (20, 600), (1200, 600), (1200, 20)]
    region_points_np = np.array(region_points)

    assert cap.isOpened(), "Error reading video file"
    while cap.isOpened():
        success, im0 = cap.read()
        if not success:
            print("Video frame is empty or video processing has been successfully completed.")
            break
        tracks = model.track(im0, persist=True,classes=[2])
        annotated_frame = tracks[0].plot()
        boxes = tracks[0].boxes.xywh.cpu()
        object_count = count_objects_in_region(boxes, region_points)
        cv2.polylines(annotated_frame, [region_points_np], isClosed=True, color=(255, 0, 0), thickness=2)
        print(object_count)

        cv2.imshow("Speed Estimation", annotated_frame)
        out_video.write(annotated_frame)
        if cv2.waitKey(1) == ord('q'):
            break
    out_video.release()
    cap.release()
    cv2.destroyAllWindows()
if __name__ == '__main__':
    detect()

4. 实验结果

本实验现在仅设置计数某一种类别的数目，对于多类别的计数后续会更新

5. 源码

可以去 Windows+YOLOV8环境配置 下载源码，然后把上边主代码贴进去运行即可