Training FasterRCNNObjectDetector with LayerGraph error with MinBoxSizes
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When running the training instruction for a Faster RCNN with a LayerGraph the 'MinBoxSizes' parameter won't let it start:
Error using vision.internal.cnn.parseInputsFasterRCNN (line 67)
'MinBoxSizes' is not supported when the input network is a LayerGraph.
Error in trainFasterRCNNObjectDetector (line 333)
vision.internal.cnn.parseInputsFasterRCNN(...
Error in FRCNN (line 86)
detector = trainFasterRCNNObjectDetector(images, lgraph, options, ...
The documentation states that:
"You cannot use this property if you set the network to a LayerGraph object or if you resume training from a detector checkpoint."
And my options don't have the 'MinBoxSizes' parameter set, so it goes automatically on 'auto', not allowing the training.
detector = trainFasterRCNNObjectDetector(images, lgraph, options, ...
'NegativeOverlapRange', [0 0.3], ...
'PositiveOverlapRange', [0.6 1], ...
'BoxPyramidScale', 1.2);
How do I solve this and get rid of the 'MinBoxSizes' parameter? Or is there a way to convert the LayerGraph into another type of variable for the training as a workaround?
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回答 (2 件)
Tunai Marques
2019 年 10 月 28 日
That does solve the problem because no more scaling is going to be done in the anchors. However, what if you want to use the 'BoxPyramidScale' and 'NumBoxPyramidLevels' parameters? I am interested in having anchors of vastly different sizes, and I am also using lgraph as input. Did you find a solution for that?
Cheers.
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