Faster rcnn 训练自己的数据集
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安装cpython，python-opencv easydict
pip install cpython
pip install easydict
apt-get install python-opencv进如 py-faster-rcnn/lib 进行make操作
make进入 py-faster-rcnn/caffe-fast-rcnn
cp Makefile.config.example Makefile.config对Makefile.config文件进行配置，我的配置文件如下：
## Refer to http://caffe.berkeleyvision.org/installation.html
# Contributions simplifying and improving our build system are welcome!
# cuDNN acceleration switch (uncomment to build with cuDNN).
USE_CUDNN := 1
# CPU-only switch (uncomment to build without GPU support).
# CPU_ONLY := 1
# uncomment to disable IO dependencies and corresponding data layers
# USE_OPENCV := 0
# USE_LEVELDB := 0
# USE_LMDB := 0
# uncomment to allow MDB_NOLOCK when reading LMDB files (only if necessary)
# You should not set this flag if you will be reading LMDBs with any
# possibility of simultaneous read and write
# ALLOW_LMDB_NOLOCK := 1
# Uncomment if you're using OpenCV 3
# OPENCV_VERSION := 3
# To customize your choice of compiler, uncomment and set the following.
# N.B. the default for Linux is g++ and the default for OSX is clang++
# CUSTOM_CXX := g++
# CUDA directory contains bin/ and lib/ directories that we need.
CUDA_DIR := /usr/local/cuda
# On Ubuntu 14.04, if cuda tools are installed via
# "sudo apt-get install nvidia-cuda-toolkit" then use this instead:
# CUDA_DIR := /usr
# CUDA architecture setting: going with all of them.
# For CUDA < 6.0, comment the *_50 lines for compatibility.
CUDA_ARCH := -gencode arch=compute_20,code=sm_20 \
-gencode arch=compute_20,code=sm_21 \
-gencode arch=compute_30,code=sm_30 \
-gencode arch=compute_35,code=sm_35 \
-gencode arch=compute_50,code=sm_50 \
-gencode arch=compute_50,code=compute_50
# BLAS choice:
# atlas for ATLAS (default)
# mkl for MKL
# open for OpenBlas
BLAS := atlas
# Custom (MKL/ATLAS/OpenBLAS) include and lib directories.
# Leave commented to accept the defaults for your choice of BLAS
# (which should work)!
# BLAS_INCLUDE := /path/to/your/blas
# BLAS_LIB := /path/to/your/blas
# Homebrew puts openblas in a directory that is not on the standard search path
# BLAS_INCLUDE := $(shell brew --prefix openblas)/include
# BLAS_LIB := $(shell brew --prefix openblas)/lib
# This is required only if you will compile the matlab interface.
# MATLAB directory should contain the mex binary in /bin.
# MATLAB_DIR := /usr/local
# MATLAB_DIR := /Applications/MATLAB_R2012b.app
# NOTE: this is required only if you will compile the python interface.
# We need to be able to find Python.h and numpy/arrayobject.h.
PYTHON_INCLUDE := /usr/include/python2.7 \
/usr/lib/python2.7/dist-packages/numpy/core/include
# Anaconda Python distribution is quite popular. Include path:
# Verify anaconda location, sometimes it's in root.
# ANACONDA_HOME := $(HOME)/anaconda
# PYTHON_INCLUDE := $(ANACONDA_HOME)/include \
# $(ANACONDA_HOME)/include/python2.7 \
# $(ANACONDA_HOME)/lib/python2.7/site-packages/numpy/core/include \
# Uncomment to use Python 3 (default is Python 2)
# PYTHON_LIBRARIES := boost_python3 python3.5m
# PYTHON_INCLUDE := /usr/include/python3.5m \
# /usr/lib/python3.5/dist-packages/numpy/core/include
# We need to be able to find libpythonX.X.so or .dylib.
PYTHON_LIB := /usr/lib
# PYTHON_LIB := $(ANACONDA_HOME)/lib
# Homebrew installs numpy in a non standard path (keg only)
# PYTHON_INCLUDE += $(dir $(shell python -c 'import numpy.core; print(numpy.core.__file__)'))/include
# PYTHON_LIB += $(shell brew --prefix numpy)/lib
# Uncomment to support layers written in Python (will link against Python libs)
WITH_PYTHON_LAYER := 1
# Whatever else you find you need goes here.
INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include /usr/include/hdf5/serial
LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/lib
# If Homebrew is installed at a non standard location (for example your home directory) and you use it for general dependencies
# INCLUDE_DIRS += $(shell brew --prefix)/include
# LIBRARY_DIRS += $(shell brew --prefix)/lib
# Uncomment to use `pkg-config` to specify OpenCV library paths.
# (Usually not necessary -- OpenCV libraries are normally installed in one of the above $LIBRARY_DIRS.)
# USE_PKG_CONFIG := 1
BUILD_DIR := build
DISTRIBUTE_DIR := distribute
# Uncomment for debugging. Does not work on OSX due to https://github.com/BVLC/caffe/issues/171
# DEBUG := 1
# The ID of the GPU that 'make runtest' will use to run unit tests.
TEST_GPUID := 0
# enable pretty build (comment to see full commands)
Q ?= @配置完Makefile.config文件后，执行：
make -j4
make pycaffe- 数据制作：
目标检测数据集制作工具 labelImg <>
修改 ../py-faster-rcnn/data/VOCdevkit2007/VOC2007/ 目录下的 Annotations 和 JPEGImage 以及ImageSets/Main 三个文件夹，下面依次讲述这个三个文件夹
JPEGImage 文件夹保存着所有图片，这里我们所有图片的格式统一都是jpg，命名规则**"000001.jpg"** 开始。
Annotation 文件夹保存着每张图片对应的XML文件，这里我们将我们的XML文件格式贴出来：
<annotation>
<folder>VOC2007</folder>
<filename>000001.jpg</filename>
<source>
<database>Unknown</database>
</source>
<size>
<width>499</width>
<height>374</height>
<depth>3</depth>
</size>
<segmented>0</segmented>
<object>
<name>label_A</name>
<pose>Frontal</pose>
<truncated>1</truncated>
<difficult>0</difficult>
<bndbox>
<xmin>121</xmin>
<ymin>127</ymin>
<xmax>208</xmax>
<ymax>144</ymax>
</bndbox>
</object>
<object>
<name>label_B</name>
<pose>Frontal</pose>
<truncated>1</truncated>
<difficult>0</difficult>
<bndbox>
<xmin>194</xmin>
<ymin>153</ymin>
<xmax>240</xmax>
<ymax>170</ymax>
</bndbox>
</object>
<object>
<name>label_C</name>
<pose>Frontal</pose>
<truncated>1</truncated>
<difficult>0</difficult>
<bndbox>
<xmin>119</xmin>
<ymin>202</ymin>
<xmax>301</xmax>
<ymax>252</ymax>
</bndbox>
</object>
<object>
<name>label_D</name>
<pose>Frontal</pose>
<truncated>1</truncated>
<difficult>0</difficult>
<bndbox>
<xmin>117</xmin>
<ymin>267</ymin>
<xmax>391</xmax>
<ymax>290</ymax>
</bndbox>
</object>
<object>
<name>label_E</name>
<pose>Frontal</pose>
<truncated>1</truncated>
<difficult>0</difficult>
<bndbox>
<xmin>89</xmin>
<ymin>98</ymin>
<xmax>421</xmax>
<ymax>312</ymax>
</bndbox>
</object>
</annotation>ImageSets/Main 文件夹下包含4个.txt文件，分别为 train.txt val.txt trainval.txt test.txt ，没给txt中保存都是图片的名称。
注意：trainval.txt 为 train.txt 和 val.txt的总和。train.txt 和 val.txt 里面保存的样本数一定要为偶数，否则会报错
- 代码部分修改
修改 py-faster-rcnn/models/pascal_voc/ZF/faster_rcnn_alt_opt/stage1_rcnn_train.pt 和 stage2_fast_rcnn_train.pt 两个文件
name: "ZF"
layer {
name: 'data'
type: 'Python'
top: 'data'
top: 'rois'
top: 'labels'
top: 'bbox_targets'
top: 'bbox_inside_weights'
top: 'bbox_outside_weights'
python_param {
module: 'roi_data_layer.layer'
layer: 'RoIDataLayer'
param_str: "'num_classes': 6" #按训练集类更改，该值为类别数+1
}
}
layer {
name: "cls_score"
type: "InnerProduct"
bottom: "fc7"
top: "cls_score"
param { lr_mult: 1.0 }
param { lr_mult: 2.0 }
inner_product_param {
num_output: 6 #按训练集类更改，该值为类别数+1
weight_filler {
type: "gaussian"
std: 0.01
}
bias_filler {
type: "constant"
value: 0
}
}
}
layer {
name: "bbox_pred"
type: "InnerProduct"
bottom: "fc7"
top: "bbox_pred"
param { lr_mult: 1.0 }
param { lr_mult: 2.0 }
inner_product_param {
num_output: 24 #按训练集类更改，该值为（类别数+1）
weight_filler {
type: "gaussian"
std: 0.001
}
bias_filler {
type: "constant"
value: 0
}
}
}修改 py-faster-rcnn/models/pascal_voc/ZF/faster_rcnn_alt_opt/stage1_rpn_train.pt 和 stage2_rpn_train.pt
name: "ZF"
layer {
name: 'input-data'
type: 'Python'
top: 'data'
top: 'im_info'
top: 'gt_boxes'
python_param {
module: 'roi_data_layer.layer'
layer: 'RoIDataLayer'
param_str: "'num_classes': 6" #按训练集类更改，该值为类别数+1
}
}修改py-faster-rcnn/models/pascal_voc/ZF/faster_rcnn_alt_opt/faster_rcnn_test.pt
layer {
name: "cls_score"
type: "InnerProduct"
bottom: "fc7"
top: "cls_score"
inner_product_param {
num_output: 6 #按训练集类更改，该值为类别数+1
}
}
layer {
name: "bbox_pred"
type: "InnerProduct"
bottom: "fc7"
top: "bbox_pred"
inner_product_param {
num_output: 24 #按训练集类更改，该值为（类别数+1）
}
}修改 py-faster-rcnn/lib/datasets/pascal_voc.py
注意 标签名尽可能为英文小写。否则会报bug
self._classes = ('__background__', # always index 0
'label_a','label_b','label_c','label_d','label_e')
# 'aeroplane', 'bicycle', 'bird', 'boat',
# 'bottle', 'bus', 'car', 'cat', 'chair',
# 'cow', 'diningtable', 'dog', 'horse',
# 'motorbike', 'person', 'pottedplant',
# 'sheep', 'sofa', 'train', 'tvmonitor')修改 py-faster-rcnn/lib/datasets/imdb.py
def append_flipped_images(self):
num_images = self.num_images
#widths = self._get_widths()
widths = [PIL.Image.open(self.image_path_at(i)).size[0]
for i in xrange(self.num_images)]
for i in xrange(num_images):
boxes = self.roidb[i]['boxes'].copy()
oldx1 = boxes[:, 0].copy()
oldx2 = boxes[:, 2].copy()
boxes[:, 0] = widths[i] - oldx2 - 1
boxes[:, 2] = widths[i] - oldx1 - 1
for b in range(len(boxes)):
if boxes[b][2] < boxes[b][0]:
boxes[b][0] = 0
assert (boxes[:, 2] >= boxes[:, 0]).all()
entry = {'boxes' : boxes,
'gt_overlaps' : self.roidb[i]['gt_overlaps'],
'gt_classes' : self.roidb[i]['gt_classes'],
'flipped' : True}
self.roidb.append(entry)
self._image_index = self._image_index删除缓存文件
删除 py-faster-rcnn文件夹下所有的.pyc 文件 以及 data文件件下的cache文件夹，
删除 data/VOCdevkit2007/annotations_cache 文件夹
删除 py-faster-rcnn/lib/datasets/ 下的imdb.pyc 和 pascal_voc.pyc
开始训练：
./experiments/scripts/faster_rcnn_alt_opt.sh 0 ZF pascal_voc全部评论 (0)
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