如何在Matlab中使用for循环处理大视频，并且没有内存错误

本文介绍了如何在Matlab中使用for循环处理大视频，并且没有内存错误的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！ 问题描述 我是Matlab处理新手，我想在for循环（或不用它）内读取和处理一个大视频（超过200k帧）。特别是，我想： 用VideoReader阅读视频， 细分视频进入每个1000帧的n个纪元， 处理1000个帧的每个纪元，读取：纪元的第一帧，跳过2，读取帧，跳过2，等等（例如i = 1：3：nFrames）， 考虑到每个我需要将每个RGB帧转换为im2bw的新纪元 在转换之后，我需要考虑第一个视频帧（mov（1,1）.cdata）以及在时间段内读取的每一帧进行corr22D互相关。 将结果从corr2存储到一个向量中。 总之，这是我需要做的。谢谢大家 这是我到目前为止对corr2 for frame_ind = 1：nFrames mov（frame_ind）.cdata = im2bw（rgb2gray（read（xyloObj，frame_ind）），0.20）; （frame_ind-1） R（frame_ind2）= corr2（mov（1， frame_ind2）.cdata，MOV（1，frame_ind2 + 1）.cdata）; 结束 TF = isnan（R）; g = sum（TF）; f =（length（R）-g）; （g〜=（​​length（R））） %%如果零件有错误 disp（''Part_1'有视频干扰/噪音/问题，请参阅Testresult.txt获取更多信息。 else %%如果零件没有错误 displ = strcat（'Part_1没有视频干扰/噪音/问题。 end 解决方案这是我的版本： mov = VideoReader（'movie.avi'）; nFrames = mov.NumberOfFrames; len = 1000; ％＃epoch length step = 3; ％＃步长 ％每个时代的指数指数= bsxfun（@plus，1：step：len，（0：ceil（nFrames / len-1））'* len ）; ％＃' indices = num2cell（indices，2）; indices {end}（indices {end}> nFrames）= []; ％每个时代的循环 corr_coef = cell（size（indices））; for e = 1：numel（indices）％＃读取历元中的第一幅图像 img1 = read（mov，indices {e}（1））; img1 = rgb2gray（img1）;读取图像的剩余时间 corr_coef {e} = zeros（1，numel（indices {e}） - 1）; for f = 2：numel（indices {e}） img2 = read（mov，indices {e}（f））; img2 = rgb2gray（img2）; ％＃两个图像之间的计算corr2 corr_coef {e}（f-1）= corr2（img1，img2）; end end 单元格数组 corr_coef 包含每个时期的相关系数，其中每个单元格包含一个 corr_coef {e}（i） of corr2 请注意，如果其中一个帧是恒定的（例如全黑），那么在第一帧和第（i + 1） ，二维相关系数仅仅是NaN（零点除以零在公式） I'm new to Matlab processing, and I would like to read and process a large video (more than 200k frames) inside a "for loop" (or without it). In particular, i would like to:read the video with VideoReader,subdivide the video into n-epoch of 1000 frames each ones,process every epoch of 1000 frames, reading: the first frame of the epoch, skip two, read the frame, skip two, and so on (for example i=1:3:nFrames),considering every epoch i need to convert every "RGB-frame" read into im2bwafter the conversion i need to make the "corr2" 2D cross-correlation considering the first video frame ("mov(1,1).cdata") and every frames read within the epoch,store the result from "corr2" into a vector. In summary, this is what i need to do. Thank You allThis is what I have so far, about "corr2":for frame_ind = 1 : nFrames mov(frame_ind).cdata = im2bw(rgb2gray(read(xyloObj,frame_ind)),0.20); end%% Corr2 to compare BW video framesfor frame_ind2 = 1:(frame_ind-1) R(frame_ind2)=corr2(mov(1,frame_ind2).cdata,mov(1,frame_ind2+1).cdata);end TF= isnan(R); g=sum(TF); f=(length(R)-g);if (g~=(length(R))) %%If Part has errors disp('"Part_1" has video interferences/noise/problems, see "Testresult.txt" for more information.'); else %%If Part has not errors displ=strcat('"Part_1" has not video interferences/noise/problems.'); end 解决方案 Here is my version:mov = VideoReader('movie.avi');nFrames = mov.NumberOfFrames;len = 1000; %# epoch lengthstep = 3; %# step size%# indices of each epochindices = bsxfun(@plus, 1:step:len, (0:ceil(nFrames/len-1))'*len); %#'indices = num2cell(indices,2);indices{end}(indices{end}>nFrames) = [];%# loop over each epochcorr_coef = cell(size(indices));for e=1:numel(indices) %# read first image in epoch img1 = read(mov, indices{e}(1)); img1 = rgb2gray(img1); %# instead of im2bw(img1, graythresh(img1)) %# read rest of images in epoch corr_coef{e} = zeros(1,numel(indices{e})-1); for f=2:numel(indices{e}) img2 = read(mov, indices{e}(f)); img2 = rgb2gray(img2); %# compute corr2 between the two images corr_coef{e}(f-1) = corr2(img1,img2); endendThe cell array corr_coef contains the correlation coefficients in each epoch, where each cell contains a vector corr_coef{e}(i) of corr2 between the first frame and the (i+1)-th frame.Note that if one of the frames is constant (all black for example), the 2D correlation coefficient is simply NaN (zero divided by zero in the formula‌​) 这篇关于如何在Matlab中使用for循环处理大视频，并且没有内存错误的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持！