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Zahra Rajabi
py-faster-rcnn
Commits
ae903eac
Commit
ae903eac
authored
May 05, 2015
by
Ross Girshick
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Add pointers for computing object proposals
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README.md
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# *Fast* R-CNN
# *Fast* R-CNN
: Fast Region-based Convolutional Networks for object detection
Created by Ross Girshick at Microsoft Research, Redmond.
...
...
@@ -128,6 +128,20 @@ matlab # wait for matlab to start...
Fast R-CNN training is implemented in Python only, but test-time detection functionality also exists in MATLAB.
See
`matlab/fast_rcnn_demo.m`
and
`matlab/fast_rcnn_im_detect.m`
for details.
**Computing object proposals**
The demo uses pre-computed selective search proposals computed with
[
this code
](
https://github.com/rbgirshick/rcnn/blob/master/selective_search/selective_search_boxes.m
)
.
If you'd like to compute proposals on your own images, there are many options.
Here are some pointers; if you run into trouble using these resources please direct questions to the respective authors.
1.
Selective Search:
[
original matlab code
](
http://disi.unitn.it/~uijlings/MyHomepage/index.php#page=projects1
)
,
[
python wrapper
](
https://github.com/sergeyk/selective_search_ijcv_with_python
)
2.
EdgeBoxes:
[
matlab code
](
https://github.com/pdollar/edges
)
3.
GOP and LPO:
[
python code
](
http://www.philkr.net/
)
4.
MCG:
[
matlab code
](
http://www.eecs.berkeley.edu/Research/Projects/CS/vision/grouping/mcg/
)
5.
RIGOR:
[
matlab code
](
http://cpl.cc.gatech.edu/projects/RIGOR/
)
Apologies if I've left your method off this list. Feel free to contact me and ask for it to be included.
### Beyond the demo: installation for training and testing models
1.
Download the training, validation, test data and VOCdevkit
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