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maxmzkr
fast-rcnn
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a2b35f2a
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a2b35f2a
authored
10 years ago
by
Ross Girshick
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simple README and some cleanup when makin
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all
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python setup.py build_ext
--inplace
rm
-rf
build
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# Fast R-CNN
### Installation
0.
Extract the source code:
`$ tar zxvf fast-rcnn.tgz`
; call the source directory
`$FRCNN`
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Build Cython modules:
`$ cd $FRCNN && make`
(there will probably be some benign warnings that you can ignore)
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Build Caffe:
`$ cd $FRCNN/caffe-master`
and follow the
[
Caffe installation instructions
](
http://caffe.berkeleyvision.org/installation.html
)
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Establish symlinks for VOCdevkits
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Symlink
`$FRCNN/datasets/VOCdevkit2007`
to where you have the PASCAL VOC 2007 devkit and data installed
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And similiarly for other PASCAL VOC 20xy datasets
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Symlink
`$FRCNN/datasets/cache`
to somewhere that will store cached dataset files
### Usage
Train a Fast R-CNN detector. For example, train a VGG 16 network on VOC 2007 trainval:
`./experiments/train_net.py --gpu 0 --solver models/VGG_16/solver.prototxt --weights /data/reference_caffe_nets/VGG_ILSVRC_16_layers.v2.caffemodel`
Test a Fast R-CNN detector. For example, test the VGG 16 network on VOC 2007 test:
`./experiments/test_net.py --gpu 1 --def models/VGG_16/test.prototxt --net snapshots/vgg16_fast_rcnn_iter_40000.caffemodel`
Test output is written underneath
`$FRCNN/output`
.
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