从视频流按帧获取图像并选定ROI，捕捉动态区域轨迹

使用cv2库将本地视频流按帧截取并捕捉ROI区域，通过matplotlib.pyplot 绘
制动态部分空间位置曲线。

1、从视频流按帧获取ROI，并跟踪

import cv2
import matplotlib.pyplot as plt

# 打开视频文件
cap = cv2.VideoCapture('video.mp4')

# 初始化跟踪器
tracker = cv2.TrackerKCF_create()

# 读取第一帧并初始化跟踪器
success, frame = cap.read()
bbox = cv2.selectROI(frame, False)
tracker.init(frame, bbox)

# 轨迹点列表
points = []

while True:
    # 读取一帧
    success, frame = cap.read()
    if not success:
        break
    
    # 跟踪目标
    success, bbox = tracker.update(frame)
    
    if success:
        # 绘制跟踪框
        x, y, w, h = [int(v) for v in bbox]
        cv2.rectangle(frame, (x, y), (x+w, y+h), (0, 255, 0), 2)
        
        # 记录跟踪器的中心点坐标
        center_x, center_y = x + w/2, y + h/2
        points.append((center_x, center_y))
    
    # 显示当前帧
    cv2.imshow('frame', frame)
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

# 释放资源
cap.release()
cv2.destroyAllWindows()

# 绘制轨迹
fig, ax = plt.subplots()
ax.set_aspect('equal')
ax.plot([p[0] for p in points], [p[1] for p in points], '-')
plt.show()

2、绘制保存的数据，按点绘制图像，显示轨迹

import csv
import matplotlib.pyplot as plt

# 从 CSV 文件中读取点数据
points = []
with open('data.csv', 'r') as csvfile:
    reader = csv.DictReader(csvfile)
    for row in reader:
        x = float(row['x'])
        y = float(row['y'])
        points.append((x, y))

# 绘制点数据
fig, ax = plt.subplots()
x_values = [p[0] for p in points]
y_values = [p[1] for p in points]
ax.plot(x_values, y_values)

# 显示图形
plt.show()