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getBatchWrapper_ucf101_imgs.m
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getBatchWrapper_ucf101_imgs.m
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function [ fn ] = getBatchWrapper_ucf101_imgs(opts, numThreads, trainopts)
fn = @(imdb,batch, moreopts) getBatch(imdb,batch,opts,numThreads, trainopts, moreopts) ;
end
% -------------------------------------------------------------------------
function [im,labels] = getBatch(imdb, batch, opts, numThreads, trainopts, moreopts)
% -------------------------------------------------------------------------
opts.nFrames = imdb.images.nFrames(batch);
images = cell(1,numel(opts.nFrames));
labels = imdb.images.label(batch) ;
for k = 1:numel(opts.nFrames)
images{k} = strcat([imdb.images.name{batch(k)}(1:end-4) filesep], images{k} ) ;
end
if ~isempty(moreopts) || nargin < 6
for f = fieldnames(moreopts)'
f = char(f) ;
trainopts.(f) = moreopts.(f);
end
end
opts.nFramesPerVid = trainopts.nFramesPerVid;
opts.numAugments = trainopts.numAugments;
opts.frameSample = trainopts.frameSample;
opts.augmentation = trainopts.augmentation;
if isfield(trainopts, 'temporalStride')
opts.temporalStride = trainopts.temporalStride(randi(numel(trainopts.temporalStride))) ; % shuffle;
end
if isfield(trainopts, 'keepFramesDim')
keepFramesDim = trainopts.keepFramesDim;
else
keepFramesDim = false;
end
if isfield(trainopts, 'cheapResize')
opts.cheapResize = trainopts.cheapResize;
end
if isfield(trainopts, 'prefetch')
opts.prefetch = trainopts.prefetch;
end
if isfield(trainopts, 'frameList')
opts.frameList = trainopts.frameList;
end
im = cnn_ucf101_get_frame_batch(images, opts, ...
'numThreads', numThreads, ...
'augmentation', opts.augmentation , ...
'imageDir', imdb.imageDir) ;
if iscell(im), return; end
labels = imdb.images.label(batch) ;
if nargout == 1 % to work with dag code
if ndims(im) > 4 && ~keepFramesDim
sz = size(im);
nFrames = sz(5:end);
im = permute(im, [1 2 3 5 4]);
im = reshape(im, sz(1), sz(2), sz(3), []);
end
if size(im,3) > 1
im = {'input', im(:,:,end-2:end,:,:), 'label', labels, 'input_flow', im(:,:,1:end-3,:,:)} ;
else
im = {'input', im, 'label', labels} ;
end
end
end