匿名用戶

1級(jí)

2018-11-19 回答

import numpy as np

import os

import matplotlib.pyplot as plt

import lmdb

from PIL import Image

import random

import sys

# import caffe module

caffe_root = '/home/henglan/Desktop/caffe-hybridnet/'

sys.path.insert(0, caffe_root + 'python')

import caffe

# read file

train_file = open('train.txt')

inputs_data_train = train_file.readlines()

train_file.close()

print("Creating Training Data LMDB File ..... ")

in_db = lmdb.open('Train_Data_lmdb',map_size=int(1e12))

with in_db.begin(write=True) as in_txn:

for in_idx, in_ in enumerate(inputs_data_train):

# print in_idx

in_ = in_.strip()

im = np.array(Image.open(in_))

Dtype = im.dtype

if len(im.shape) == 2:

print('here')

(row, col) = im.shape

im3 = np.zeros([row, col, 3], Dtype)

for i in range(3):

im3 [:, :, i] = im

im = im3

print('here')

im = im[:,:,::-1]

im = Image.fromarray(im)

im = np.array(im,Dtype)

im = im.transpose((2,0,1))

im_dat = caffe.io.array_to_datum(im)

in_txn.put('{:0>10d}'.format(in_idx),im_dat.SerializeToString())

in_db.close()

# read file

label_file = open('label.txt')

inputs_data_label = label_file.readlines()

label_file.close()

print("Creating Training Label LMDB File ..... ")

in_db1 = lmdb.open('Label_Data_lmdb',map_size=int(1e12))

with in_db1.begin(write=True) as in_txn:

for in_idx, in_ in enumerate(inputs_data_label):

in_ = in_.strip()

Dtype = 'uint8'

L = np.array(Image.open(in_), Dtype)

Limg = Image.fromarray(L)

L = np.array(Limg,Dtype)

L = L.reshape(L.shape[0],L.shape[1],1)

L = L.transpose((2,0,1))

L_dat = caffe.io.array_to_datum(L)

in_txn.put('{:0>10d}'.format(in_idx),L_dat.SerializeToString())

in_db1.close()

print("Finish creating lmdb file ......")

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