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Я хочу обучить сеть, чтобы распознать RGB на изображении. (вход: 256X256 изображений и некоторое значение RGB).caffe - Неудачное открытие HDF5 файла: train.h5
Я написал сценарий, который создает файл hdf5 для поплавков нескольких лейблов:
import h5py, os
import caffe
import numpy as np
SIZE = 256 # images size
with open('/home/path/images):
lines = T.readlines()
X = np.zeros((len(lines), SIZE, SIZE, 3), dtype='f4')
r = np.zeros((len(lines),1), dtype='f4')
g = np.zeros((len(lines),1), dtype='f4')
b = np.zeros((len(lines),1), dtype='f4')
for i,l in enumerate(lines):
sp = l.split(' ')
img = caffe.io.load_image(sp[0])
# img = caffe.io.resize(img, (3, SIZE, SIZE)) # resize to fixed $
print img
X[i] = img
# print X[i]
r[i] = float(sp[1])
g[i] = float(sp[2])
b[i] = float(sp[3])
print "R" + str(r[i]) + "G" + str(g[i]) + "B" + str(b[i])
with h5py.File('/home/path/train.h5','$
H.create_dataset('X', data=X)
H.create_dataset('r', data=r)
H.create_dataset('g', data=g)
H.create_dataset('b', data=b)
with open('/home/path/train_h5_list.tx$
L.write('train.h5') # list all h5 files
Im использованием многоступенчатой метки регрессии сети. когда я бегу ПОЕЗД на этой сети с моим набором данных (HDF5) я получил эту ошибку:
name: "FKPReg"
state {
phase: TRAIN
}
layer {
name: "fkp"
type: "HDF5Data"
top: "data"
top: "label"
include {
phase: TRAIN
}
hdf5_data_param {
source: "/home/path/train_h5_list.txt"
batch_size: 64
}
}
layer {
name: "conv1"
type: "Convolution"
bottom: "data"
top: "conv1"
convolution_param {
num_output: 32
kernel_size: 11
stride: 2
bias_filler {
type: "constant"
value: 0.1
}
}
}
layer {
name: "relu2"
type: "ReLU"
bottom: "conv1"
top: "conv1"
}
layer {
name: "pool1"
type: "Pooling"
bottom: "conv1"
top: "pool1"
pooling_param {
pool: MAX
kernel_size: 2
stride: 2
}
}
layer {
name: "conv2"
type: "Convolution"
bottom: "pool1"
top: "conv2"
convolution_param {
num_output: 64
pad: 2
kernel_size: 7
group: 2
bias_filler {
type: "constant"
value: 0.1
}
}
}
layer {
name: "relu2"
type: "ReLU"
bottom: "conv2"
top: "conv2"
}
layer {
name: "pool2"
type: "Pooling"
bottom: "conv2"
top: "pool2"
pooling_param {
pool: MAX
kernel_size: 2
stride: 2
}
}
layer {
name: "norm2"
type: "LRN"
bottom: "pool2"
top: "norm2"
lrn_param {
local_size: 3
alpha: 5e-05
beta: 0.75
norm_region: WITHIN_CHANNEL
}
}
layer {
name: "conv3"
type: "Convolution"
bottom: "norm2"
top: "conv3"
convolution_param {
num_output: 32
pad: 1
kernel_size: 5
bias_filler {
type: "constant"
value: 0.1
}
}
}
layer {
name: "relu3"
type: "ReLU"
bottom: "conv3"
top: "conv3"
}
layer {
name: "conv4"
type: "Convolution"
bottom: "conv3"
top: "conv4"
convolution_param {
num_output: 64
pad: 1
kernel_size: 5
bias_filler {
type: "constant"
value: 0.1
}
}
}
layer {
name: "relu4"
type: "ReLU"
bottom: "conv4"
top: "conv4"
}
layer {
name: "conv5"
type: "Convolution"
bottom: "conv4"
top: "conv5"
convolution_param {
num_output: 32
pad: 1
kernel_size: 5
bias_filler {
type: "constant"
value: 0.1
}
}
}
layer {
name: "relu5"
type: "ReLU"
bottom: "conv5"
top: "conv5"
}
layer {
name: "pool5"
type: "Pooling"
bottom: "conv5"
top: "pool5"
pooling_param {
pool: MAX
kernel_size: 4
stride: 2
}
}
layer {
name: "drop0"
type: "Dropout"
bottom: "pool5"
top: "pool5"
dropout_param {
dropout_ratio: 0.5
}
}
layer {
name: "ip1"
type: "InnerProduct"
bottom: "pool5"
top: "ip1"
inner_product_param {
num_output: 100
bias_filler {
type: "constant"
value: 0.1
}
}
}
layer {
name: "relu4"
type: "ReLU"
bottom: "ip1"
top: "ip1"
}
layer {
name: "drop1"
type: "Dropout"
bottom: "ip1"
top: "ip1"
dropout_param {
dropout_ratio: 0.5
}
}
layer {
name: "ip2"
type: "InnerProduct"
bottom: "ip1"
top: "ip2"
inner_product_param {
num_output: 3
bias_filler {
type: "constant"
value: 0.1
}
}
}
layer {
name: "relu22"
type: "ReLU"
bottom: "ip2"
top: "ip2"
}
layer {
name: "loss"
type: "EuclideanLoss"
bottom: "ip2"
bottom: "label"
top: "loss"
}
I1106 11:47:52.235343 28083 layer_factory.hpp:74] Creating layer fkp
I1106 11:47:52.235384 28083 net.cpp:90] Creating Layer fkp
I1106 11:47:52.235410 28083 net.cpp:368] fkp -> data
I1106 11:47:52.235443 28083 net.cpp:368] fkp -> label
I1106 11:47:52.235481 28083 net.cpp:120] Setting up fkp
I1106 11:47:52.235496 28083 hdf5_data_layer.cpp:80] Loading list of HDF5 filenames from: /home/path/train_h5_list.txt
I1106 11:47:52.235568 28083 hdf5_data_layer.cpp:94] Number of HDF5 files: 1
HDF5-DIAG: Error detected in HDF5 (1.8.11) thread 140703305845312:
#000: ../../../src/H5F.c line 1586 in H5Fopen(): unable to open file
major: File accessibilty
minor: Unable to open file
#001: ../../../src/H5F.c line 1275 in H5F_open(): unable to open file: time = Sun Nov 6 11:47:52 2016
, name = 'train.h5', tent_flags = 0
major: File accessibilty
minor: Unable to open file
#002: ../../../src/H5FD.c line 987 in H5FD_open(): open failed
major: Virtual File Layer
minor: Unable to initialize object
#003: ../../../src/H5FDsec2.c line 343 in H5FD_sec2_open(): unable to open file: name = 'train.h5', errno = 2, error message = 'No such file or directory', flags = 0, o_flags = 0
major: File accessibilty
minor: Unable to open file
F1106 11:47:52.236398 28083 hdf5_data_layer.cpp:32] Failed opening HDF5 file: train.h5
*** Check failure stack trace: ***
@ 0x7ff809dfcdaa (unknown)
@ 0x7ff809dfcce4 (unknown)
@ 0x7ff809dfc6e6 (unknown)
@ 0x7ff809dff687 (unknown)
@ 0x7ff80a194406 caffe::HDF5DataLayer<>::LoadHDF5FileData()
@ 0x7ff80a192c98 caffe::HDF5DataLayer<>::LayerSetUp()
@ 0x7ff80a173be3 caffe::Net<>::Init()
@ 0x7ff80a175952 caffe::Net<>::Net()
@ 0x7ff80a15bbf0 caffe::Solver<>::InitTrainNet()
@ 0x7ff80a15cbc3 caffe::Solver<>::Init()
@ 0x7ff80a15cd96 caffe::Solver<>::Solver()
@ 0x40c5d0 caffe::GetSolver<>()
@ 0x406611 train()
@ 0x404bb1 main
@ 0x7ff80930ef45 (unknown)
@ 0x40515d (unknown)
@ (nil) (unknown)
Aborted (core dumped)
Что я делаю неправильно? спасибо
У вас есть смешные '' 'в строках кода. Вы уверены, что вставили код, который вы используете? – Shai
жаль, что я скопировал код из моей оболочки (слишком длинная последовательность) –