我想在视频中定义一个感兴趣区域并只处理该区域

Question

我在理解 opencv 感兴趣的区域时遇到问题。我有一些代码可以从我的first_frame. 我还可以用我的mouse_draw_rect函数绘制一个矩形。

现在，我希望背景减法只发生在我绘制的矩形内，因为我想加快算法处理速度。我知道我必须设置某种感兴趣的区域，但我昨天和今天都尝试了，但我从教程中尝试过的都没有奏效。有人可以帮助指导我完成这个过程吗？

编辑：试图修复代码

import numpy as np

import cv2

import matplotlib.pyplot as plt

cap = cv2.VideoCapture(0)

_, first_frame = cap.read()

def mouse_draw_rect(event, x, y, flags, params):

    global point1, point2, drawing, first_frame, x1, x2, y1, y2

    if event == cv2.EVENT_LBUTTONDOWN:

        if drawing is False:

            drawing = True

            point1 = (x, y)

            x1 = (x)

            y1 = (y)

        else:

            drawing = False

    elif event == cv2.EVENT_MOUSEMOVE:

        if drawing is True:

            point2 = (x, y)

            x2 = (x)

            y2 = (y)

    elif event == cv2.EVENT_MBUTTONDOWN:

        first_frame = frame

drawing = False

point1 = ()

point2 = ()

x1 = ()

x2 = ()

y1 = ()

y2 = ()

cv2.namedWindow('Original')

cv2.setMouseCallback("Original", mouse_draw_rect)

while True:

    ret, frame = cap.read( )

    if point1 and point2:

        cv2.rectangle(frame, point1, point2, (0, 0, 0),5)

    difference = cv2.absdiff(first_frame[y1:y2, x1:x2], frame[y1:y2, x1:x2])

    difference = cv2.GaussianBlur(difference, (3, 3), 0)

    _, difference = cv2.threshold(difference, 18, 255, cv2.THRESH_BINARY)

    cv2.imshow('first frame (1)', first_frame)

    cv2.imshow('Original', frame)

    cv2.imshow('difference', difference)

    key = cv2.waitKey(30) & 0xff

    if key == 27:

        break

cap.release()

cv2.destroyAllWindows()

Answer 1

只需按您绘制的矩形区域进行裁剪。代替difference = cv2.absdiff(first_frame, frame)利用difference = cv2.absdiff(first_frame[y1:y2, x1:x2], frame[y1:y2, x1:x2])

Answer 2

主要问题在于 ROI 选择事件以及当前如何调用它。当前的实现不是动态的，这意味着我们无法可视化我们正在尝试选择的 ROI。此外，我们甚至在选择 ROI 之前就已经开始处理。选择 ROI 的正确方法是，一旦我们捕获了第一帧，注册鼠标单击事件并无限期地可视化该帧imshow，waitKey(n)直到按下某个特定键。或者，我们可以通过使用waitKey(0)（未测试）在没有无限循环的情况下实现相同的效果。在这个阶段，我们应该能够绘制出想要的 ROI 矩形。这里的关键因素是必须通过使用无限循环或waitKey(0). 仅仅注册活动是不够的。完成 ROI 选择后，继续执行其余代码。一些建议如下：尽可能避免使用全局变量为 ROI 选择创建单独的窗口，然后将其丢弃为每个单独的任务创建单独的函数以下是演示正确使用鼠标单击事件来选择视频处理的 ROI 的完整代码：import numpy as npimport cv2import matplotlib.pyplot as pltORIGINAL_WINDOW_TITLE = 'Original'FIRST_FRAME_WINDOW_TITLE = 'First Frame'DIFFERENCE_WINDOW_TITLE = 'Difference'canvas = Nonedrawing = False # true if mouse is pressed#Retrieve first framedef initialize_camera(cap):    _, frame = cap.read()    return frame# mouse callback functiondef mouse_draw_rect(event,x,y,flags, params):    global drawing, canvas    if drawing:        canvas = params[0].copy()    if event == cv2.EVENT_LBUTTONDOWN:        drawing = True        params.append((x,y)) #Save first point    elif event == cv2.EVENT_MOUSEMOVE:        if drawing:            cv2.rectangle(canvas, params[1],(x,y),(0,255,0),2)    elif event == cv2.EVENT_LBUTTONUP:        drawing = False        params.append((x,y)) #Save second point        cv2.rectangle(canvas,params[1],params[2],(0,255,0),2)def select_roi(frame):    global canvas    canvas = frame.copy()    params = [frame]    ROI_SELECTION_WINDOW = 'Select ROI'    cv2.namedWindow(ROI_SELECTION_WINDOW)    cv2.setMouseCallback(ROI_SELECTION_WINDOW, mouse_draw_rect, params)    roi_selected = False    while True:        cv2.imshow(ROI_SELECTION_WINDOW, canvas)        key = cv2.waitKey(10)        #Press Enter to break the loop        if key == 13:            break;    cv2.destroyWindow(ROI_SELECTION_WINDOW)    roi_selected = (3 == len(params))    if roi_selected:        p1 = params[1]        p2 = params[2]        if (p1[0] == p2[0]) and (p1[1] == p2[1]):            roi_selected = False    #Use whole frame if ROI has not been selected    if not roi_selected:        print('ROI Not Selected. Using Full Frame')        p1 = (0,0)        p2 = (frame.shape[1] - 1, frame.shape[0] -1)    return roi_selected, p1, p2if __name__ == '__main__':    cap = cv2.VideoCapture(0)    #Grab first frame    first_frame = initialize_camera(cap)    #Select ROI for processing. Hit Enter after drawing the rectangle to finalize selection    roi_selected, point1, point2 = select_roi(first_frame)        #Grab ROI of first frame    first_frame_roi = first_frame[point1[1]:point2[1], point1[0]:point2[0], :]    #An empty image of full size just for visualization of difference    difference_image_canvas = np.zeros_like(first_frame)    while cap.isOpened():        ret, frame = cap.read()        if ret:            #ROI of current frame            roi = frame[point1[1]:point2[1], point1[0]:point2[0], :]            difference = cv2.absdiff(first_frame_roi, roi)            difference = cv2.GaussianBlur(difference, (3, 3), 0)            _, difference = cv2.threshold(difference, 18, 255, cv2.THRESH_BINARY)            #Overlay computed difference image onto the whole image for visualization            difference_image_canvas[point1[1]:point2[1], point1[0]:point2[0], :] = difference.copy()            cv2.imshow(FIRST_FRAME_WINDOW_TITLE, first_frame)            cv2.imshow(ORIGINAL_WINDOW_TITLE, frame)            cv2.imshow(DIFFERENCE_WINDOW_TITLE, difference_image_canvas)            key = cv2.waitKey(30) & 0xff            if key == 27:                break        else:            break    cap.release()    cv2.destroyAllWindows()专业提示： 有时，在初始化相机时，根据房间内的环境光，它需要一些时间来预热。您可以考虑跳过一些初始帧，让相机从初始化阶段稳定下来。可以通过initialize_camera在上述代码中定义函数来完成，如下所示：def initialize_camera(cap):    for i in range(0,60): #Skip first 60 frames        _, frame = cap.read()    return frame