python环境下OPenCV处理视频流局部区域像素值
参考我之前写的处理图片的文章:Python+OpenCV实现【图片】局部区域像素值处理(改进版)
开发环境:Python3.6.0 + OpenCV3.2.0
任务目标:摄像头采集图像(例如:480640),并对视频流每一帧(灰度图)特定矩形区域(48030)像素值进行行求和,得到一个480*1的数组,用这480个数据绘制条形图,即在逐帧采集视频流并处理后“实时”显示采集到的视频,并“实时”更新条形图。工作流程如下图:
源码:
# -*- coding:utf-8 -*- import cv2 import numpy as np camera = cv2.VideoCapture(0) # 参数0表示第一个摄像头 # camera = cv2.VideoCapture("test.avi") # 从文件读取视频 # 判断视频是否打开 if (camera.isOpened()): print 'Open' else: print 'Fail to open!' # # 测试用,查看视频size # size = (int(camera.get(cv2.CAP_PROP_FRAME_WIDTH)), # int(camera.get(cv2.CAP_PROP_FRAME_HEIGHT))) # print 'size:'+repr(size) rectangleCols = 30 while True: grabbed, frame_lwpCV = camera.read() # 逐帧采集视频流 if not grabbed: break gray_lwpCV = cv2.cvtColor(frame_lwpCV, cv2.COLOR_BGR2GRAY) # 转灰度图 frame_data = np.array(gray_lwpCV) # 每一帧循环存入数组 box_data = frame_data[:, 400:400+rectangleCols] # 取矩形目标区域 pixel_sum = np.sum(box_data, axis=1) # 行求和q length = len(gray_lwpCV) x = range(length) emptyImage = np.zeros((rectangleCols*10, length*2, 3), np.uint8) for i in x: cv2.rectangle(emptyImage, (i*2, (rectangleCols-pixel_sum[i]/255)*10), ((i+1)*2, rectangleCols*10), (255, 0, 0), 1) emptyImage = cv2.resize(emptyImage, (320, 240)) # 画目标区域 lwpCV_box = cv2.rectangle(frame_lwpCV, (400, 0), (430, length), (0, 255, 0), 2) cv2.imshow('lwpCVWindow', frame_lwpCV) # 显示采集到的视频流 cv2.imshow('sum', emptyImage) # 显示画出的条形图 key = cv2.waitKey(1) & 0xFF if key == ord('q'): break camera.release() cv2.destroyAllWindows()
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