Web>>> m = torchvision.ops.MultiScaleRoIAlign( ['feat1', 'feat3'], 3, 2) >>> i = OrderedDict() >>> i['feat1'] = torch.rand(1, 5, 64, 64) >>> i['feat2'] = torch.rand(1, 5, 32, 32) # this feature won't be used in the pooling >>> i['feat3'] = torch.rand(1, 5, 16, 16) >>> # create some random bounding boxes >>> boxes = torch.rand(6, 4) * 256; boxes[:, … FEAT3 is released under the GNU General Public License version 3, see the file 'copyright.txt' in the top level directory for details. DEPENDECIES FEAT depends on: cmake 3.9 or greater python 2.6 or greater gcc 4.8+ or icc 16+ or clang 3.6+ or MSVC++ 2015+ or AOCC 1.3+
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