Commit 8abd6f35 authored by Ross Girshick's avatar Ross Girshick
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instructions for unpacking pascal

parent 4e2b4996
...@@ -41,7 +41,7 @@ LICENSE file for details). ...@@ -41,7 +41,7 @@ LICENSE file for details).
0. Change into that directory: `$ cd rcnn` 0. Change into that directory: `$ cd rcnn`
0. R-CNN expects to find Caffe in `external/caffe`, so create a symlink: `$ ln -sf $CAFFE_HOME external/caffe` 0. R-CNN expects to find Caffe in `external/caffe`, so create a symlink: `$ ln -sf $CAFFE_HOME external/caffe`
0. Start MATLAB (make sure you're in the `rcnn` folder): `$ matlab` 0. Start MATLAB (make sure you're in the `rcnn` folder): `$ matlab`
0. You'll be prompted to download the [Selective Search](http://disi.unitn.it/~uijlings/MyHomepage/index.php#page=projects1) code, which we cannot redistribute. You should see the message `R-CNN startup done` followed by the MATLAB prompt. 0. You'll be prompted to download the [Selective Search](http://disi.unitn.it/~uijlings/MyHomepage/index.php#page=projects1) code, which we cannot redistribute. Afterwards, you should see the message `R-CNN startup done` followed by the MATLAB prompt `>>`.
0. Run the build script: `>> rcnn_build()` (builds [liblinear](http://www.csie.ntu.edu.tw/~cjlin/liblinear/) and [Selective Search](http://www.science.uva.nl/research/publications/2013/UijlingsIJCV2013/)). Don't worry if you see compiler warnings while building liblinear, this is normal on my system. 0. Run the build script: `>> rcnn_build()` (builds [liblinear](http://www.csie.ntu.edu.tw/~cjlin/liblinear/) and [Selective Search](http://www.science.uva.nl/research/publications/2013/UijlingsIJCV2013/)). Don't worry if you see compiler warnings while building liblinear, this is normal on my system.
0. Check that Caffe and MATLAB wrapper are set up correctly (this code should run without error): `>> key = caffe('get_init_key');` (expected output is key = -2) 0. Check that Caffe and MATLAB wrapper are set up correctly (this code should run without error): `>> key = caffe('get_init_key');` (expected output is key = -2)
0. Download the data package, which includes precompute models (see below). 0. Download the data package, which includes precompute models (see below).
...@@ -68,6 +68,7 @@ Let's assume that you've downloaded the precomputed detectors. Now: ...@@ -68,6 +68,7 @@ Let's assume that you've downloaded the precomputed detectors. Now:
2. Start MATLAB `$ matlab`. 2. Start MATLAB `$ matlab`.
* **Important:** if you don't see the message `R-CNN startup done` when MATLAB starts, then you probably didn't start MATLAB in `rcnn` directory. * **Important:** if you don't see the message `R-CNN startup done` when MATLAB starts, then you probably didn't start MATLAB in `rcnn` directory.
3. Run the demo: `>> rcnn_demo` 3. Run the demo: `>> rcnn_demo`
3. Enjoy the detected bicycle and person
### Training your own R-CNN detector on PASCAL VOC ### Training your own R-CNN detector on PASCAL VOC
...@@ -79,21 +80,36 @@ You'll need about 200GB of disk space free for the feature cache (which is store ...@@ -79,21 +80,36 @@ You'll need about 200GB of disk space free for the feature cache (which is store
#### Installing PASCAL VOC 2007 #### Installing PASCAL VOC 2007
1. Download the training and validation data [here](http://pascallin.ecs.soton.ac.uk/challenges/VOC/voc2007/VOCtrainval_06-Nov-2007.tar). 0. Download the training, validation, test data and VOCdevkit:
2. Download the test data [here](http://pascallin.ecs.soton.ac.uk/challenges/VOC/voc2007/VOCtest_06-Nov-2007.tar).
3. Download the VOCdevkit [here](http://pascallin.ecs.soton.ac.uk/challenges/VOC/voc2007/VOCdevkit_08-Jun-2007.tar).
4. Extract all of these tars into one directory, let's call it `VOCdevkit`. It should have this basic structure:
<pre> <pre>
VOCdevkit/ % development kit $ wget http://pascallin.ecs.soton.ac.uk/challenges/VOC/voc2007/VOCtrainval_06-Nov-2007.tar
VOCdevkit/VOCcode/ % VOC utility code $ wget http://pascallin.ecs.soton.ac.uk/challenges/VOC/voc2007/VOCtest_06-Nov-2007.tar
VOCdevkit/VOC2007 % image sets, annotations, etc. $ wget http://pascallin.ecs.soton.ac.uk/challenges/VOC/voc2007/VOCdevkit_08-Jun-2007.tar
... and several other directories ... </pre>
</pre>
0. Extract all of these tars into one directory, it's called `VOCdevkit`.
<pre>
$ tar xvf VOCtrainval_06-Nov-2007.tar
$ tar xvf VOCtest_06-Nov-2007.tar
$ tar xvf VOCdevkit_08-Jun-2007.tar
</pre>
0. It should have this basic structure:
<pre>
VOCdevkit/ % development kit
VOCdevkit/VOCcode/ % VOC utility code
VOCdevkit/VOC2007 % image sets, annotations, etc.
... and several other directories ...
</pre>
I use a symlink to hook the R-CNN codebase to the PASCAL VOC dataset: 0. I use a symlink to hook the R-CNN codebase to the PASCAL VOC dataset:
`$ cd rcnn/datasets` and then `$ ln -sf /your/path/to/voc2007/VOCdevkit VOCdevkit2007` <pre>
$ ln -sf /your/path/to/voc2007/VOCdevkit /path/to/rcnn/datasets/VOCdevkit2007
</pre>
#### Extracting features #### Extracting features
......
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