caffe版faster-RCNN环境搭建
- faster-rcnn提出论文： 《Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks》
- faster-rcnn 的算法详解可看这篇博文（清晰易懂，良心博文！）： http://blog.csdn.net/shenxiaolu1984/article/details/51152614
- faster-rcnn Python版本源码地址：https://github.com/rbgirshick/py-faster-rcnn
- 基本按照官网上的readme
1.电脑上已经有可运行caffe所需的环境
2.下载faster-rcnn python版本源码
git clone --recursive https://github.com/rbgirshick/py-faster-rcnn.git
3. 进入/py-faster-rcnn/lib 进行编译，build the Cython modules
cd py-faster-rcnn/lib
make
- 如果重新升级或者降级numpy依赖包，需要重新去掉之前生成的文件，重新make; 否则会报这里面的错
问题：
python setup.py build_ext --inplace
running build_ext
cythoning utils/bbox.pyx to utils/bbox.c Error compiling Cython file:
------------------------------------------------------------
...
# Copyright (c) 2015 Microsoft
# Licensed under The MIT License [see LICENSE for details]
# Written by Sergey Karayev
# -------------------------------------------------------- cimport cython
^
------------------------------------------------------------ utils/bbox.pyx:8:8: Compiler crash in AnalyseDeclarationsTransform File 'ModuleNode.py', line 122, in analyse_declarations: ModuleNode(bbox.pyx:1:0,
full_module_name = 'utils.cython_bbox')
File 'Nodes.py', line 408, in analyse_declarations: StatListNode(bbox.pyx:8:0)
File 'Nodes.py', line 408, in analyse_declarations: StatListNode(bbox.pyx:8:8)
File 'Nodes.py', line 7396, in analyse_declarations: CImportStatNode(bbox.pyx:8:8,
module_name = u'cython') File "/home/dsp/anaconda2/lib/python2.7/site-packages/Cython/Utils.py", line 148, in search_include_directories
path = os.path.join(dir, dotted_filename)
File "/home/dsp/anaconda2/lib/python2.7/posixpath.py", line 73, in join
path += '/' + b
UnicodeDecodeError: 'ascii' codec can't decode byte 0xe6 in position 10: ordinal not in range(128)
building 'utils.cython_bbox' extension
gcc -pthread -B /home/dsp/anaconda2/compiler_compat -Wl,--sysroot=/ -fno-strict-aliasing -g -O2 -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -I/home/dsp/anaconda2/lib/python2.7/site-packages/numpy/core/include -I/home/dsp/anaconda2/include/python2.7 -c utils/bbox.c -o build/temp.linux-x86_64-2.7/utils/bbox.o -Wno-cpp -Wno-unused-function
utils/bbox.c:1:2: error: #error Do not use this file, it is the result of a failed Cython compilation.
#error Do not use this file, it is the result of a failed Cython compilation.
^
error: command 'gcc' failed with exit status 1
Makefile:2: recipe for target 'all' failed
make: *** [all] Error 1
- 先各种百度，安装cython等；结果发现时路径的坑
- 神坑：路径；py-faster-rcnn存放位置路径中不能有中文，否则报错UnicodeDecodeError: 'ascii' codec can't decode byte 0xe6 in position
- 最后放到 /home/uername/ 下直接makec成功
4.编译/py-faster-rcnn/caffe-fast-rcnn
cd py-faster-rcnn/caffe-fast-rcnn
make -j32 && make pycaffe
- Makefile.config文件直接用的本机配置caffe的文件
- 问题：
dsp@dsp-PowerEdge-R730:/home/user/ran/Desktop/protobuf-2.6.$ protoc
[libprotobuf FATAL google/protobuf/stubs/common.cc:] This program requires version 3.4. of the Protocol Buffer runtime library, but the installed version is 2.6.. Please update your library. If you compiled the program yourself, make sure that your headers are from the same version of Protocol Buffers as your link-time library. (Version verification failed in "google/protobuf/any.pb.cc".)
terminate called after throwing an instance of 'google::protobuf::FatalException'
what(): This program requires version 3.4. of the Protocol Buffer runtime library, but the installed version is 2.6.. Please update your library. If you compiled the program yourself, make sure that your headers are from the same version of Protocol Buffers as your link-time library. (Version verification failed in "google/protobuf/any.pb.cc".)
Aborted (core dumped)
这个问题是服务器上的错误：http://blog.csdn.net/m0_37477175/article/details/78233983
https://www.cnblogs.com/javaee6/p/4849051.html
https://github.com/BVLC/caffe/issues/5711
前面两种方法都是了没有解决，后面github上的issue也没有给出解决方法，看以后能不能解决！！！
In file included from ./include/caffe/util/device_alternate.hpp:40:0,
from ./include/caffe/common.hpp:19,
from ./include/caffe/blob.hpp:8,
from src/caffe/blob.cpp:4:
./include/caffe/util/cudnn.hpp:8:34: fatal error: caffe/proto/caffe.pb.h: 没有那个文件或目录
- 按照：解决方法： 用protoc从caffe/src/caffe/proto/caffe.proto生成caffe.pb.h和caffe.pb.cc ，http://blog.csdn.net/xmzwlw/article/details/48270225没有作用；后面还有一串错误
In file included from ./include/caffe/util/device_alternate.hpp:40:0,
from ./include/caffe/common.hpp:19,
from ./include/caffe/blob.hpp:8,
from ./include/caffe/layers/loss_layer.hpp:6,
from src/caffe/layers/loss_layer.cpp:3:
./include/caffe/util/cudnn.hpp: In function ‘const char* cudnnGetErrorString(cudnnStatus_t)’:
./include/caffe/util/cudnn.hpp:21:10: warning: enumeration value ‘CUDNN_STATUS_RUNTIME_PREREQUISITE_MISSING’ not handled in switch [-Wswitch]
switch (status) {
^
./include/caffe/util/cudnn.hpp: In function ‘void caffe::cudnn::setConvolutionDesc(cudnnConvolutionStruct**, cudnnTensorDescriptor_t, cudnnFilterDescriptor_t, int, int, int, int)’:
./include/caffe/util/cudnn.hpp:108:70: error: too few arguments to function ‘cudnnStatus_t cudnnSetConvolution2dDescriptor(cudnnConvolutionDescriptor_t, int, int, int, int, int, int, cudnnConvolutionMode_t, cudnnDataType_t)’
pad_h, pad_w, stride_h, stride_w, 1, 1, CUDNN_CROSS_CORRELATION));
^
./include/caffe/util/cudnn.hpp:15:28: note: in definition of macro ‘CUDNN_CHECK’
cudnnStatus_t status = condition; \
^
In file included from ./include/caffe/util/cudnn.hpp:5:0,
from ./include/caffe/util/device_alternate.hpp:40,
from ./include/caffe/common.hpp:19,
from ./include/caffe/blob.hpp:8,
from ./include/caffe/layers/loss_layer.hpp:6,
from src/caffe/layers/loss_layer.cpp:3:
/usr/local/cuda/include/cudnn.h:500:27: note: declared here
cudnnStatus_t CUDNNWINAPI cudnnSetConvolution2dDescriptor( cudnnConvolutionDescriptor_t convDesc,
^
In file included from ./include/caffe/util/device_alternate.hpp:40:0,
from ./include/caffe/common.hpp:19,
from ./include/caffe/blob.hpp:8,
from ./include/caffe/layers/loss_layer.hpp:6,
from src/caffe/layers/loss_layer.cpp:3:
./include/caffe/util/cudnn.hpp: In function ‘void caffe::cudnn::createPoolingDesc(cudnnPoolingStruct**, caffe::PoolingParameter_PoolMethod, cudnnPoolingMode_t*, int, int, int, int, int, int)’:
./include/caffe/util/cudnn.hpp:127:41: error: too few arguments to function ‘cudnnStatus_t cudnnSetPooling2dDescriptor(cudnnPoolingDescriptor_t, cudnnPoolingMode_t, cudnnNanPropagation_t, int, int, int, int, int, int)’
pad_h, pad_w, stride_h, stride_w));
^
./include/caffe/util/cudnn.hpp:15:28: note: in definition of macro ‘CUDNN_CHECK’
cudnnStatus_t status = condition; \
^
In file included from ./include/caffe/util/cudnn.hpp:5:0,
from ./include/caffe/util/device_alternate.hpp:40,
from ./include/caffe/common.hpp:19,
from ./include/caffe/blob.hpp:8,
from ./include/caffe/layers/loss_layer.hpp:6,
from src/caffe/layers/loss_layer.cpp:3:
- 后面发现时cndnn版本不兼容：Faster R-CNN 和最新的版本cuDNN V5.0不兼容问题
解决方法： cd py-faster-rcnn/caffe-fast-rcnn
Git remote add caffe https://github.com/BVLC/caffe.git
git fetch caffe
git merge caffe/master 在合并之后注释掉include/caffe/layers/python_layer.hppa文件里的self_.attr(“phase”) = static_cast(this->phase_)- 重新从caffe中fetch and merge
- 遇到merge冲突，直接编辑
// Caffe utility functions
bp::def("init_log", &InitLog);
bp::def("init_log", &InitLogLevel);
bp::def("init_log", &InitLogLevelPipe);
bp::def("log", &Log);
bp::def("has_nccl", &HasNCCL);
bp::def("set_mode_cpu", &set_mode_cpu);
bp::def("set_mode_gpu", &set_mode_gpu);
bp::def("set_random_seed", &set_random_seed);
bp::def("set_device", &Caffe::SetDevice);
<<<<<<< HEAD
bp::def("set_random_seed", &Caffe::set_random_seed);
=======
bp::def("solver_count", &Caffe::solver_count);
bp::def("set_solver_count", &Caffe::set_solver_count);
bp::def("solver_rank", &Caffe::solver_rank);
bp::def("set_solver_rank", &Caffe::set_solver_rank);
bp::def("set_multiprocess", &Caffe::set_multiprocess);
>>>>>>> caffe/master
- 最后编译成功；faster-rcnn 安装里面也提到了处理版本不兼容，进行文件替换的方法
AR -o .build_release/lib/libcaffe.a
LD -o .build_release/lib/libcaffe.so.1.0.0
CXX/LD -o .build_release/tools/convert_imageset.bin
CXX/LD -o .build_release/tools/train_net.bin
CXX/LD -o .build_release/tools/finetune_net.bin
CXX/LD -o .build_release/tools/compute_image_mean.bin
CXX/LD -o .build_release/tools/upgrade_net_proto_text.bin
CXX/LD -o .build_release/tools/test_net.bin
CXX/LD -o .build_release/tools/upgrade_net_proto_binary.bin
CXX/LD -o .build_release/tools/upgrade_solver_proto_text.bin
CXX/LD -o .build_release/tools/net_speed_benchmark.bin
CXX/LD -o .build_release/tools/device_query.bin
CXX/LD -o .build_release/tools/extract_features.bin
CXX/LD -o .build_release/examples/cifar10/convert_cifar_data.bin
CXX/LD -o .build_release/examples/mnist/convert_mnist_data.bin
CXX/LD -o .build_release/examples/cpp_classification/classification.bin
CXX/LD -o .build_release/tools/caffe.bin
CXX/LD -o .build_release/examples/siamese/convert_mnist_siamese_data.bin
CXX/LD -o python/caffe/_caffe.so python/caffe/_caffe.cpp
touch python/caffe/proto/__init__.py
PROTOC (python) src/caffe/proto/caffe.proto
5、下载Faster R-CNN的预训练模型
cd py-faster-rcnn
./data/scripts/fetch_faster_rcnn_models.sh
model:https://dl.dropboxusercontent.com/s/o6ii098bu51d139/faster_rcnn_models.tgz?dl=0
6、运行demo.py
cd py-faster-rcnn
./tools/demo.py7.Usage:训练
To train and test a Faster R-CNN detector using the alternating optimization algorithm from our NIPS 2015 paper, use experiments/scripts/faster_rcnn_alt_opt.sh. Output is written underneath $FRCN_ROOT/output.
cd $FRCN_ROOT
./experiments/scripts/faster_rcnn_alt_opt.sh [GPU_ID] [NET] [--set ...]
# GPU_ID is the GPU you want to train on
# NET in {ZF, VGG_CNN_M_1024, VGG16} is the network arch to use
# --set ... allows you to specify fast_rcnn.config options, e.g.
# --set EXP_DIR seed_rng1701 RNG_SEED 1701
AttributeError: 'module' object has no attribute 'text_format'
在文件./lib/fast_rcnn/train.py增加一行import google.protobuf.text_format 即可解决问题
8.后续问题
I1119 21:29:42.451519 21365 net.cpp:744] Ignoring source layer pool5_spm6
I1119 21:29:42.451537 21365 net.cpp:744] Ignoring source layer pool5_spm6_flatten
I1119 21:29:42.481129 21365 net.cpp:744] Ignoring source layer fc8
I1119 21:29:42.481151 21365 net.cpp:744] Ignoring source layer prob
Solving...
Process Process-3:
Traceback (most recent call last):
File "/home/dsp/anaconda2/lib/python2.7/multiprocessing/process.py", line 267, in _bootstrap
self.run()
File "/home/dsp/anaconda2/lib/python2.7/multiprocessing/process.py", line 114, in run
self._target(*self._args, **self._kwargs)
File "./tools/train_faster_rcnn_alt_opt.py", line 195, in train_fast_rcnn
max_iters=max_iters)
File "/home/dsp/py-faster-rcnn/tools/../lib/fast_rcnn/train.py", line 162, in train_net
model_paths = sw.train_model(max_iters)
File "/home/dsp/py-faster-rcnn/tools/../lib/fast_rcnn/train.py", line 103, in train_model
self.solver.step(1)
File "/home/dsp/py-faster-rcnn/tools/../lib/roi_data_layer/layer.py", line 144, in forward
blobs = self._get_next_minibatch()
File "/home/dsp/py-faster-rcnn/tools/../lib/roi_data_layer/layer.py", line 63, in _get_next_minibatch
return get_minibatch(minibatch_db, self._num_classes)
File "/home/dsp/py-faster-rcnn/tools/../lib/roi_data_layer/minibatch.py", line 55, in get_minibatch
num_classes)
File "/home/dsp/py-faster-rcnn/tools/../lib/roi_data_layer/minibatch.py", line 100, in _sample_rois
fg_inds, size=fg_rois_per_this_image, replace=False)
File "mtrand.pyx", line 1187, in mtrand.RandomState.choice
TypeError: 'numpy.float64' object cannot be interpreted as an index TypeError: 'numpy.float64' object cannot be interpreted as an index
还是numpy版本的问题，直接换一个版本好了
sudo pip install -U numpy==1.11.0 --这个错 “ImportError: numpy.core.multiarray failed to import”好像就是lib库里面没有重新make,去掉之前
+ ./tools/train_faster_rcnn_alt_opt.py --gpu 0 --net_name ZF --weights data/imagenet_models/ZF.v2.caffemodel --imdb voc_2007_trainval --cfg experiments/cfgs/faster_rcnn_alt_opt.yml
Traceback (most recent call last):
File "./tools/train_faster_rcnn_alt_opt.py", line 19, in <module>
from datasets.factory import get_imdb
File "/home/dsp/py-faster-rcnn/tools/../lib/datasets/factory.py", line 13, in <module>
from datasets.coco import coco
File "/home/dsp/py-faster-rcnn/tools/../lib/datasets/coco.py", line 20, in <module>
from pycocotools.coco import COCO
File "/home/dsp/py-faster-rcnn/tools/../lib/pycocotools/coco.py", line 58, in <module>
import mask
File "/home/dsp/py-faster-rcnn/tools/../lib/pycocotools/mask.py", line 3, in <module>
import pycocotools._mask as _mask
File "pycocotools/_mask.pyx", line 20, in init pycocotools._mask
File "__init__.pxd", line 989, in numpy.import_array
ImportError: numpy.core.multiarray failed to import
Reading annotation for 4901/4952
Saving cached annotations to /home/dsp/py-faster-rcnn/data/VOCdevkit2007/annotations_cache/annots.pkl
AP for aeroplane = 0.0339
AP for bicycle = 0.1139
AP for bird = 0.0069
AP for boat = 0.0646
Traceback (most recent call last):
File "./tools/test_net.py", line 90, in <module>
test_net(net, imdb, max_per_image=args.max_per_image, vis=args.vis)
File "/home/dsp/py-faster-rcnn/tools/../lib/fast_rcnn/test.py", line 295, in test_net
imdb.evaluate_detections(all_boxes, output_dir)
File "/home/dsp/py-faster-rcnn/tools/../lib/datasets/pascal_voc.py", line 322, in evaluate_detections
self._do_python_eval(output_dir)
File "/home/dsp/py-faster-rcnn/tools/../lib/datasets/pascal_voc.py", line 285, in _do_python_eval
use_07_metric=use_07_metric)
File "/home/dsp/py-faster-rcnn/tools/../lib/datasets/voc_eval.py", line 148, in voc_eval
BB = BB[sorted_ind, :]
IndexError: too many indices for array
http://blog.csdn.net/weinaonao5418/article/details/54234684
File "/home/dl-box/wei/py-faster-rcnn/tools/../lib/datasets/voc_eval.py", line 149, in voc_eval
BB = BB[sorted_ind, :]
IndexError: too many indices for array
这个错是说没有学习到东西，我用了[4000,2000,4000,2000]试了一下也不行。不过能看到这个错误，如果你的数据集做的没有问题的话，用[80000,40000,80000,40000]（亲测大概16小时，1341张图）运行你自己的数据集就没问题了。为了省时间我用的是[40000,20000,40000,2000]（大概8小时，50张图）。这个时间好像与图片大小和图片数量关系不大。感觉只与迭代次数有关。
- Reference
http://blog.csdn.net/mydear_11000/article/details/70241139
caffe版faster-RCNN环境搭建的更多相关文章
- Go版GTK：环境搭建(windows)
Go版GTK:环境搭建(windows) https://blog.csdn.net/tennysonsky/article/details/79221507 所属专栏: Go语言开发实战 1 ...
- 记pytorch版faster rcnn配置运行中的一些坑
记pytorch版faster rcnn配置运行中的一些坑 项目地址 https://github.com/jwyang/faster-rcnn.pytorch 一般安装配置参考README.md文件 ...
- Tensorflow版Faster RCNN源码解析（TFFRCNN） （2）推断（测试）过程不使用RPN时代码运行流程
本blog为github上CharlesShang/TFFRCNN版源码解析系列代码笔记第二篇 推断(测试)过程不使用RPN时代码运行流程 作者:Jiang Wu 原文见:https://hom ...
- Windows下如何采用微软的Caffe配置Faster R-CNN
前言 比较简单的一篇博客.https://github.com/microsoft/caffe 微软的Caffe以在Windows下编译简单而受到了很多人的喜爱(包括我),只用改改prop配置然后无脑 ...
- Cocos2d-x 3.0正式版及android环境搭建
开发环境是:mac + xcode + eclipse ,在win以下的环境和这个都是一样的,唯一不一样的就是环境变量的配置. 以下主要介绍cocos2d-x环境的设置以及android的环境搭建 1 ...
- python 版Faster Rcnn
直接按照官网https://github.com/rbgirshick/py-faster-rcnn上的教程对faster Rcnn进行编译的时候,会发有一些层由于cudnn版本的更新,会报错如下: ...
- caffe之mac下环境搭建
参考 http://www.linuxidc.com/Linux/2016-09/135026.html 1. 安装brew,也叫homebrew,mac下类似于ubuntu的apt-get功能 cu ...
- Tensorflow版Faster RCNN源码解析（TFFRCNN） （1） VGGnet_test.py
本blog为github上CharlesShang/TFFRCNN版源码解析系列代码笔记第1篇 VGGnet_test.py ----作者:Jiang Wu(吴疆),未经允许,禁止转载--- -- ...
- faster rcnn环境编译
步骤和fast rcnn的编译一样,在编译中遇到了一个问题: 刚开始是以为python-numpy没有安装到位,后来发现是Makefile.config的配置出现了问题.原来的配置是: PYTHON_ ...
- caffe 用faster rcnn 训练自己的数据 遇到的问题
1 . 怎么处理那些pyx和.c .h文件 在lib下有一些文件为.pyx文件,遇到不能import可以cython 那个文件,然后把lib文件夹重新make一下. 遇到.c 和 .h一样的操作. 2 ...
随机推荐
- Python虚拟机之异常控制流（五）
Python中的异常控制语义结构 在Python虚拟机之异常控制流(四)这一章中,我们考察了Python的异常在虚拟机中的级别上是什么东西,抛出异常这个动作在虚拟机的级别上对应的行为,最后,我们还剖析 ...
- Hydux: 一个 Elm-like 的 全功能的 Redux 替代品
在学习和使用 Fable + Elmish 一段时间之后,对 Elm 架构有了更具体的了解, 和预料中的一样,Redux 这种来自 Elm 的风格果然还是和强类型的 Meta Language 语言更 ...
- Leetcode23--->Merge K sorted Lists(合并k个排序的单链表)
题目: 合并k个排序将k个已排序的链表合并为一个排好序的链表,并分析其时间复杂度 . 解题思路: 类似于归并排序的思想,lists中存放的是多个单链表,将lists的头和尾两个链表合并,放在头,头向后 ...
- 编译TensorFlow CPU指令集优化版
编译TensorFlow CPU指令集优化版 如题,CPU指令集优化版,说的是针对某种特定的CPU型号进行过优化的版本.通常官方给的版本是没有针对特定CPU进行过优化的,有网友称,优化过的版本相比优化 ...
- [python 函数学习篇]默认参数
python函数: 默认参数: retries= 这种形式 def ask_ok(prompt, retries=, complaint='Yes or no, please!'): while Tr ...
- Spring配置文件中使用ref local与ref bean的区别
Spring配置文件中使用ref local与ref bean的区别.在ApplicationResources.properties文件中,使用<ref bean>与<ref lo ...
- 【java基础 17】集合中各实现类的性能分析
大致的再回顾一下java集合框架的基本情况 一.各Set实现类的性能分析 1.1,HashSet用于添加.查询 HashSet和TreeSet是Set的两个典型实现,HashSet的性能总是比Tree ...
- poj1985&&第四次CCF软件认证第4题 求树的直径
Cow Marathon Time Limit: 2000MS Memory Limit: 30000K Total Submissions: 4216 Accepted: 2137 Case ...
- 【Luogu】P4231三步必杀（差分，差分）
题目链接 郑重宣布我以后真的再也不会信样例了,三种写法都能过 另:谁评的蓝题难度qwq 蓝题有这么恐怖吗 两次差分,第一次差分,前缀和求出增量数组,第二次求出原数组顺便更新答案 看题解之后……第二次差 ...
- javascript中 for循环的一些写法 for length 以及for in 还有 for of 的区别
最近在写一些前端的代码,遇到一个产品列表遍历的问题,正好使用到for 的几种用法,于是研究了下. 代码如下,先说明下goodslist 是一个产品列表 形如这样的数据格式 { ‘types’:1, ' ...