如何才能将Faster R-CNN训练起来？

　　首先进入　Faster RCNN 的官网啦，即：https://github.com/rbgirshick/py-faster-rcnn#installation-sufficient-for-the-demo

　　先用提供的　model　自己测试一下效果嘛。。。

　　按照官网安装教程，安装基本需求。

Installation (sufficient for the demo)

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 the caffe-fast-rcnn submodule:
```
git submodule update --init --recursive
```
Note 2: The caffe-fast-rcnn submodule needs to be on the faster-rcnn branch (or equivalent detached state). This will happen automatically if 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

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. See data/README.md for details. These models were trained on VOC 2007 trainval.

Demo

After successfully completing basic installation, you'll be ready to run the demo.

To run the demo

cd $FRCN_ROOT

./tools/demo.py

The demo performs detection using a VGG16 network trained for detection on PASCAL VOC 2007.

　　你自己要下载一个　caffe-master，因为这个检测方法就是调用　caffe的啦，自己下载了，然后放到(注意，是拷贝内容)：

　　./py-faster-rcnn-master/caffe-fast-rcnn/

　　然而，情况总是不太顺利啊，遇到了如下问题：

　　执行　demo 的过程中，遇到的首个问题是：

wangxiao@GTX980:~/Desktop/py-faster-rcnn-master$ ./tools/demo.py
Traceback (most recent call last):
File "./tools/demo.py", line 18, in <module>
from fast_rcnn.test import im_detect
File "/home/wangxiao/Desktop/py-faster-rcnn-master/tools/../lib/fast_rcnn/test.py", line 16, in <module>
import caffe
File "/home/wangxiao/Desktop/py-faster-rcnn-master/tools/../caffe-fast-rcnn/python/caffe/__init__.py", line 1, in <module>
from .pycaffe import Net, SGDSolver, NesterovSolver, AdaGradSolver, RMSPropSolver, AdaDeltaSolver, AdamSolver
File "/home/wangxiao/Desktop/py-faster-rcnn-master/tools/../caffe-fast-rcnn/python/caffe/pycaffe.py", line 15, in <module>
import caffe.io
File "/home/wangxiao/Desktop/py-faster-rcnn-master/tools/../caffe-fast-rcnn/python/caffe/io.py", line 2, in <module>
import skimage.io
ImportError: No module named skimage.io
wangxiao@GTX980:~/Desktop/py-faster-rcnn-master$

　　解决方法是：　sudo easy_install -U scikit-image

　　那么，就这样完了？？　噢，ｎｏ，并不是：

wangxiao@GTX980:~/Desktop/py-faster-rcnn-master/tools$ ./demo.py
/usr/local/lib/python2.7/dist-packages/matplotlib-2.0.0b3-py2.7-linux-x86_64.egg/matplotlib/font_manager.py:279: UserWarning: Matplotlib is building the font cache using fc-list. This may take a moment.
warnings.warn('Matplotlib is building the font cache using fc-list. This may take a moment.')
Traceback (most recent call last):
File "./demo.py", line 127, in <module>
'fetch_faster_rcnn_models.sh?').format(caffemodel))
IOError: /home/wangxiao/Desktop/py-faster-rcnn-master/data/faster_rcnn_models/VGG16_faster_rcnn_final.caffemodel not found.
Did you run ./data/script/fetch_faster_rcnn_models.sh?

　　因为你测试的时候，没有提供给他测试的 model啊，ｏｋ，执行这句吧，下载一个模型：

　　 ./data/script/fetch_faster_rcnn_models.sh

　　速度还是有点慢的，耐心等候啊，少年！

　　然后，

wangxiao@GTX980:~/Desktop/py-faster-rcnn-master/tools$ ./demo.py
WARNING: Logging before InitGoogleLogging() is written to STDERR
W0729 10:57:41.107311 7997 _caffe.cpp:122] DEPRECATION WARNING - deprecated use of Python interface
W0729 10:57:41.107381 7997 _caffe.cpp:123] Use this instead (with the named "weights" parameter):
W0729 10:57:41.107398 7997 _caffe.cpp:125] Net('/home/wangxiao/Desktop/py-faster-rcnn-master/models/pascal_voc/VGG16/faster_rcnn_alt_opt/faster_rcnn_test.pt', 1, weights='/home/wangxiao/Desktop/py-faster-rcnn-master/data/faster_rcnn_models/VGG16_faster_rcnn_final.caffemodel')
[libprotobuf ERROR google/protobuf/text_format.cc:245] Error parsing text-format caffe.NetParameter: 350:21: Message type "caffe.LayerParameter" has no field named "roi_pooling_param".
F0729 10:57:41.132531 7997 upgrade_proto.cpp:79] Check failed: ReadProtoFromTextFile(param_file, param) Failed to parse NetParameter file: /home/wangxiao/Desktop/py-faster-rcnn-master/models/pascal_voc/VGG16/faster_rcnn_alt_opt/faster_rcnn_test.pt
*** Check failure stack trace: ***
Aborted
wangxiao@GTX980:~/Desktop/py-faster-rcnn-master/tools$

　　我更新了一下系统，但是提示我无法更新啊。。。

wangxiao@GTX980:~$ sudo apt-get update
[sudo] password for wangxiao:
E: Type 'Reading' is not known on line 1 in source list /etc/apt/sources.list.d/bazel.list
E: The list of sources could not be read.

　　进去这个路径，将这个文件删掉，即可，即：sudo rm /etc/apt/sources.list.d/bazel.list

　　之前出现各种蛋疼的情况主要是因为：不能自己从ｃａｆｆｅ官网下的那个caffe来用，而应该是从作者自己的 github上来下。

　　然后加到对应的文件夹进行编译，就不会出现这些问题了。

　　至于训练的话，有两种方式，一种是： end-to-end，即：

　　在终端执行：选择　GPU-0，网络为: ZF 数据集为: pascal_voc

　　./experiments/scripts/faster_rcnn_end2end.sh 0 ZF pascal_voc

　　那么，就可以跑了　。。。

　　不像　matlab版本那么蛋疼，跑一下，就会自动关闭matlab一次，╮（╯▽╰）╭　伤不起　。。。

　　这是最终跑出来的结果：ｍAP 是：59.09 %　　　

Saving cached annotations to /home/wangxiao/Desktop/py-faster-rcnn-master/data/VOCdevkit2007/annotations_cache/annots.pkl
AP for aeroplane = 0.6043
AP for bicycle = 0.7138
AP for bird = 0.5504
AP for boat = 0.4721
AP for bottle = 0.3404
AP for bus = 0.6633
AP for car = 0.7369
AP for cat = 0.7021
AP for chair = 0.3631
AP for cow = 0.6086
AP for diningtable = 0.6191
AP for dog = 0.6469
AP for horse = 0.7789
AP for motorbike = 0.6782
AP for person = 0.6489
AP for pottedplant = 0.3073
AP for sheep = 0.5715
AP for sofa = 0.5015
AP for train = 0.7026
AP for tvmonitor = 0.6089
Mean AP = 0.5909
~~~~~~~~
Results:
0.604
0.714
0.550
0.472
0.340
0.663
0.737
0.702
0.363
0.609
0.619
0.647
0.779
0.678
0.649
0.307
0.571
0.502
0.703
0.609
0.591
~~~~~~~~

--------------------------------------------------------------
Results computed with the **unofficial** Python eval code.
Results should be very close to the official MATLAB eval code.
Recompute with `./tools/reval.py --matlab ...` for your paper.
-- Thanks, The Management
--------------------------------------------------------------

real 5m25.471s
user 5m11.620s
sys 0m35.848s

　　Matlab 版本碰到过如下的问题：

　　1. 找不到 ZF文件夹下面的 test.prototxt 文件：

fast_rcnn startup done
GPU 1: free memory 3786178560
Use GPU 1
Error using CHECK_FILE_EXIST (line 4)
/home/wangxiao/Desktop/matlab-faster_rcnn-master/experiments/models/rpn_prototxts/ZF/test.prototxt does not exist

Error in caffe.get_net (line 21)
CHECK_FILE_EXIST(model_file);

Error in caffe.Net (line 31)
self = caffe.get_net(varargin{:});

Error in proposal_calc_output_size (line 10)
caffe_net = caffe.Net(test_net_def_file, 'test');

Error in script_faster_rcnn_VOC2007_ZF>proposal_prepare_anchors (line 91)
[output_width_map, output_height_map] ...

Error in script_faster_rcnn_VOC2007_ZF (line 41)
[conf_proposal.anchors, conf_proposal.output_width_map, conf_proposal.output_height_map] ...

解决方案是：没有下载那个文件，囧，下载地址：https://onedrive.live.com/download?resid=36FEC490FBC32F1A!113&authkey=!AIzdm0sD_SmhUQ4&ithint=file%2czip

2. 将上一个问题搞定后，有出现新的，这个有点摸不着头脑了：

fast_rcnn startup done
GPU 1: free memory 3761143808
Use GPU 1
No appropriate method, property, or field reshape_as_input for class caffe.Net.

Error in proposal_calc_output_size (line 28)
caffe_net.reshape_as_input(net_inputs);

Error in script_faster_rcnn_VOC2007_ZF>proposal_prepare_anchors (line 91)
[output_width_map, output_height_map] ...

Error in script_faster_rcnn_VOC2007_ZF (line 41)
[conf_proposal.anchors, conf_proposal.output_width_map, conf_proposal.output_height_map]
...

解决方法是：可能是你 caffe　版本不对，重新从 faster rcnn　官网上下载，然后编译　。。。　

3. 更蛋疼的是这个问题，表面上看，正在运行，但是这个时候你看看终端上的显示：

File not found: ./models/rpn_prototxts/ZF/train_vali.prototxt

但是，这个文件明明就放在那里啊。。。无语。。。

解决方案是：由于下载的model中，关于 prototxt文件中路径的问题，请改为绝对路径，如下图所示，且用”/“作为分隔符，因为下载了的分隔符是不对的，所以，一直找不到这个文件，哎，坑啊。。。。

搞完之后，就可以继续正常的运行了。。。

fast_rcnn startup done

GPU 1: free memory 3676987392

Use GPU 1

Warning: Specified caffe folder

(/home/wangxiao/Documents/faster_rcnn-master/experiments/external/caffe/matlab/caffe_faster_rcnn) is not exist,

change to default one (/home/wangxiao/Documents/faster_rcnn-master/experiments/external/caffe/matlab)

> In active_caffe_mex at 19

  In script_faster_rcnn_VOC2007_ZF at 17

Cleared 0 solvers and 1 stand-alone nets

***************

stage one proposal

***************

conf:

                      batch_size: 256

                    bg_thresh_hi: 0.3000

                    bg_thresh_lo: 0

                       bg_weight: 1

         drop_boxes_runoff_image: 1

                     feat_stride: 16

                     fg_fraction: 0.5000

                       fg_thresh: 0.7000

                     image_means: [224x224x3 single]

                   ims_per_batch: 1

                        max_size: 1000

                        rng_seed: 6

                          scales: 600

                  target_only_gt: 1

                     test_binary: 0

    test_drop_boxes_runoff_image: 0

                   test_max_size: 1000

               test_min_box_size: 16

                        test_nms: 0.3000

                     test_scales: 600

                     use_flipped: 1

                         use_gpu: 1

                         anchors: [9x4 double]

                output_width_map: [901x1 containers.Map]

               output_height_map: [901x1 containers.Map]

opts:

           cache_name: 'faster_rcnn_VOC2007_ZF_stage1_rpn'

                 conf: [1x1 struct]

               do_val: 1

           imdb_train: {[1x1 struct]}

             imdb_val: [1x1 struct]

             net_file: '/home/wangxiao/Documents/faster_rcnn-master/experiments/models/pre_trained_models/ZF/ZF...'

          roidb_train: {[1x1 struct]}

            roidb_val: [1x1 struct]

    snapshot_interval: 10000

      solver_def_file: '/home/wangxiao/Documents/faster_rcnn-master/experiments/models/rpn_prototxts/ZF/solver_...'

         val_interval: 2000

            val_iters: 500

Preparing training data...Starting parallel pool (parpool) using the 'local' profile ... connected to 4 workers.

Done.

Preparing validation data...Done.

------------------------- Iteration 2000 -------------------------

Training : err_fg 0.521, err_bg 0.0187, loss (cls 0.242 + reg 0.0218)

Testing  : err_fg 0.487, err_bg 0.0131, loss (cls 0.203 + reg 0.0167)

------------------------- Iteration 4000 -------------------------

Training : err_fg 0.495, err_bg 0.0187, loss (cls 0.209 + reg 0.0206)

Testing  : err_fg 0.458, err_bg 0.0143, loss (cls 0.182 + reg 0.0158)

------------------------- Iteration 6000 -------------------------

Training : err_fg 0.462, err_bg 0.0205, loss (cls 0.196 + reg 0.0189)

Testing  : err_fg 0.409, err_bg 0.0229, loss (cls 0.177 + reg 0.0184)

------------------------- Iteration 8000 -------------------------

Training : err_fg 0.46, err_bg 0.0196, loss (cls 0.19 + reg 0.0194)

Testing  : err_fg 0.404, err_bg 0.0163, loss (cls 0.165 + reg 0.0151)

------------------------- Iteration 10000 -------------------------

Training : err_fg 0.437, err_bg 0.0202, loss (cls 0.179 + reg 0.0189)

Testing  : err_fg 0.413, err_bg 0.0154, loss (cls 0.168 + reg 0.0158)

Saved as /home/wangxiao/Documents/faster_rcnn-master/experiments/output/rpn_cachedir/faster_rcnn_VOC2007_ZF_stage1_rpn/voc_2007_trainval/iter_10000

4. Faster RCNN 运行出现问题：

fast_rcnn startup done
Error using gpuDevice (line 26)
An unexpected error occurred during CUDA execution. The CUDA error was:
cannot set while device is active in this process

Error in auto_select_gpu (line 15)
g = gpuDevice(i);

Error in script_faster_rcnn_VOC2007_ZF (line 16)
opts.gpu_id = auto_select_gpu;

答：如果之前正常运行，突然出现这个问题，重启你的 matlab，然后以 sudo 开启，重新跑一下就没事了。。。

5. 下面是今天重新跑　faster RCNN　遇到的一个问题：

解决方案是：

　　数据集的名字或者文件夹不存在，额，将数据集加上就行了．．．

6. 之前一直很纳闷，script_faster_rcnn_VOC0712_VGG16.m 这个脚本的数据集该怎么设置？是分别单独设置两个文件夹，还是将其放到一个文件夹中？？？

　　看到这个代码，我终于恍然大悟　．．．