前提是已经配置好Caffe，opencv，Python

教程：

https://github.com/735545856/py-faster-rcnn#disclaimer

指导：

Clone the Faster R-CNN repository

# Make sure to clone with --recursive git clone --recursive https://github.com/rbgirshick/py-faster-rcnn.git

We'll call the directory that you cloned Faster R-CNN into FRCN_ROOT

Ignore notes 1 and 2 if you followed step 1 above.

Note 1: If you didn't clone Faster R-CNN with the --recursive flag, then you'll need to manually clone thecaffe-fast-rcnn submodule:

git submodule update --init --recursive

Note 2: The caffe-fast-rcnn submodule needs to be on thefaster-rcnn branch (or equivalent detached state). This will happen automaticallyif you followed step 1 instructions.

Build the Cython modules

cd $FRCN_ROOT/lib make

Build Caffe and pycaffe

cd $FRCN_ROOT/caffe-fast-rcnn # Now follow the Caffe installation instructions here: # http://caffe.berkeleyvision.org/installation.html # If you're experienced with Caffe and have all of the requirements installed # and your Makefile.config in place, then simply do: make -j8 && make pycaffe

            这个有点问题， 需将配置好的caffe-master目录下，有makefile和makefile.config ，将其拷贝到caffe-fast-rcnn 下（原来的请备份好），运行 make -j8 && make pycaffe

           5. Download pre-computed Faster R-CNN detectors

cd $FRCN_ROOT ./data/scripts/fetch_faster_rcnn_models.sh

This will populate the $FRCN_ROOT/data folder with faster_rcnn_models. Seedata/README.md for details.These models were trained on VOC 2007 trainval.

            这个有点问题， 到这个指定的目录下，进行如下命令：  chmod +x fetch_faster_rcnn_models.sh,  然后运行：  ./fetch_faster_rcnn_models.sh

至此，告一段落。为了运行demo效果，还要做如下工作。

Beyond the demo: installation for training and testing models

Download the training, validation, test data and VOCdevkit

wget http://host.robots.ox.ac.uk/pascal/VOC/voc2007/VOCtrainval_06-Nov-2007.tar wget http://host.robots.ox.ac.uk/pascal/VOC/voc2007/VOCtest_06-Nov-2007.tar wget http://host.robots.ox.ac.uk/pascal/VOC/voc2007/VOCdevkit_08-Jun-2007.tar

Extract all of these tars into one directory named VOCdevkit

tar xvf VOCtrainval_06-Nov-2007.tar tar xvf VOCtest_06-Nov-2007.tar tar xvf VOCdevkit_08-Jun-2007.tar

It should have this basic structure

$VOCdevkit/ # development kit $VOCdevkit/VOCcode/ # VOC utility code $VOCdevkit/VOC2007 # image sets, annotations, etc. # ... and several other directories ...

Create symlinks for the PASCAL VOC dataset

cd $FRCN_ROOT/data ln -s $VOCdevkit VOCdevkit2007

          5. To run the demo

cd $FRCN_ROOT ./tools/demo.py

即可运行demo

主要参考： https://github.com/735545856/py-faster-rcnn#disclaimer