Run aggregate channel features object detector on given image(s). The input 'I' can either be a single image (or filename) or a cell array of images (or filenames). In the first case, the return is a set of bbs where each row has the format [x y w h score] and score is the confidence of detection. If the input is a cell array, the output is a cell array where each element is a set of bbs in the form above (in this case a parfor loop is used to speed execution). If 'fileName' is specified, the bbs are saved to a comma separated text file and the output is set to bbs=1. If saving detections for multiple images the output is stored in the format [imgId x y w h score] and imgId is a one-indexed image id. A cell of detectors trained with the same channels can be specified, detected bbs from each detector are concatenated. If using multiple detectors and opts.pNms.separate=1 then each bb has a sixth element bbType=j, where j is the j-th detector, see bbNms.m for details. USAGE bbs = acfDetect( I, detector, [fileName] ) INPUTS I - input image(s) of filename(s) of input image(s) detector - detector(s) trained via acfTrain fileName - [] target filename (if specified return is 1) OUTPUTS bbs - [nx5] array of bounding boxes or cell array of bbs EXAMPLE See also acfTrain, acfModify, bbGt>loadAll, bbNms Piotr's Computer Vision Matlab Toolbox Version 3.40 Copyright 2014 Piotr Dollar. [pdollar-at-gmail.com] Licensed under the Simplified BSD License [see external/bsd.txt]