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Python 如何从视频中提取ROI-将不相关的像素变黑_Python_Opencv_Image Processing_Computer Vision - Fatal编程技术网

Python 如何从视频中提取ROI-将不相关的像素变黑

Python 如何从视频中提取ROI-将不相关的像素变黑,python,opencv,image-processing,computer-vision,Python,Opencv,Image Processing,Computer Vision,我正在拍摄一个简单的视频,我用笔记本电脑的摄像头移动我的头,并跟踪我的头的移动 这是密码 import numpy as np import cv2 cap = cv2.VideoCapture(0) # take first frame of the video ret, frame = cap.read() # setup initial location of window r, h, c, w = 250, 90, 400, 125 # simply hardcoded the

我正在拍摄一个简单的视频,我用笔记本电脑的摄像头移动我的头,并跟踪我的头的移动

这是密码

import numpy as np
import cv2

cap = cv2.VideoCapture(0)

# take first frame of the video
ret, frame = cap.read()


# setup initial location of window
r, h, c, w = 250, 90, 400, 125  # simply hardcoded the values
track_window = (c, r, w, h)

# set up the ROI for tracking
roi = frame[r:r + h, c:c + w]
hsv_roi = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
mask = cv2.inRange(hsv_roi, np.array((0., 60., 32.)), np.array((180., 255., 255.)))
roi_hist = cv2.calcHist([hsv_roi], [0], mask, [180], [0, 180])
cv2.normalize(roi_hist, roi_hist, 0, 255, cv2.NORM_MINMAX)

# Setup the termination criteria, either 10 iteration or move by atleas1t 1 pt
term_crit = (cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_COUNT, 10, 1)

while (1):
    ret, frame = cap.read()
    if ret:
        hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
        dst = cv2.calcBackProject([hsv], [0], roi_hist, [0, 180], 1)
        # apply meanshift to get the new location
        ret, track_window = cv2.meanShift(dst, track_window, term_crit)
        # Draw it on image
        x, y, w, h = track_window
        cv2.rectangle(frame, (x, y), (x+w, y+h), (255,0, 0), 2)
        cv2.imshow('img2',frame)
        k = cv2.waitKey(60) & 0xff
        if k == 27:
            break
    else:
        break
cv2.destroyAllWindows()
cap.release()
我想把不在蓝色小长方形中的所有东西都涂黑(也就是剪掉)

我尝试用
frame[:x,:y]=0
frame[x+w:,y+h:]=0
将框架变黑,但我仍然看到矩形外的部分不是黑色的


有没有一个简单的方法可以做到这一点?

这对我来说很有效。也使用您的代码进行了测试

# Draw it on image
    x, y, w, h = track_window
    cv2.rectangle(frame, (x, y), (x+w, y+h), (255,0, 0), 2)
    dst = np.zeros_like(frame)
    dst[y:y+h,x:x+w] = frame[y:y+h,x:x+w]
    cv2.imshow('dst',dst)
什么是“部分”?你能提供一个截图吗?