def test_str(self):
d = Datum()
d.add_string('name', 'john')
d.add_number('age', 20)
d.add_binary('image', '0101')
self.assertEquals('datum{string_values: [[\'name\', \'john\']], num_values: [[\'age\', 20.0]], binary_values: [[\'image\', \'0101\']]}',
str(d))
def test_str(self):
d = Datum()
d.add_string('name', 'john')
d.add_number('age', 20)
d.add_binary('image', b('0101'))
s = str(d)
self.assertTrue('datum{string_values: [[\'name\', \'john\']], num_values: [[\'age\', 20.0]], binary_values: [[\'image\', \'0101\']]}' == s or 'datum{string_values: [[\'name\', \'john\']], num_values: [[\'age\', 20.0]], binary_values: [[\'image\', b\'0101\']]}' == s)
def make_datum_binary(title=None, text=None, picture=None):
d = Datum()
if title:
d.add_string("title", title)
if text:
d.add_string("text", text)
if picture:
d.add_binary("img", picture)
return d
def make_datum(title=None, text=None, picture=None):
d = Datum()
if title:
d.add_string("title", title)
if text:
d.add_string("text", text)
if picture:
with open(picture, "rb") as f:
d.add_binary("img", f.read())
return d
def test_str(self):
d = Datum()
d.add_string('name', 'john')
d.add_number('age', 20)
d.add_binary('image', b('0101'))
s = str(d)
self.assertTrue(
'datum{string_values: [[\'name\', \'john\']], num_values: [[\'age\', 20.0]], binary_values: [[\'image\', \'0101\']]}'
== s or
'datum{string_values: [[\'name\', \'john\']], num_values: [[\'age\', 20.0]], binary_values: [[\'image\', b\'0101\']]}'
== s)
def get_traindata(labels):
traindata = []
for index in range(n_train):
imgfile = "{}.jpg"
img = os.path.join(dir, imgfile.format(index))
with open(img, "rb") as f:
binary = f.read()
label = labels[index][1]
d = Datum()
d.add_binary("image", binary)
traindata.append([label, d])
print("num of train data :", len(traindata))
return traindata
def get_traindata(labels):
traindata = []
for index in range(n_train):
img = dir+str(index)+".jpg"
with open(img,"rb") as f:
binary = f.read()
label = labels[index][1]
print label,index
d = Datum()
d.add_binary("image",binary)
traindata.append([label,d])
print "num of train data :",len(traindata)
return traindata
def get_traindata(labels):
traindata = []
for index in range(n_train):
imgfile = "{}.jpg"
img = os.path.join(dir,imgfile.format(index))
with open(img,"rb") as f:
binary = f.read()
label = labels[index][1]
d = Datum()
d.add_binary("image",binary)
traindata.append([label,d])
print ("num of train data :",len(traindata))
return traindata
def get_testdata(labels):
testdata = []
testlabels = []
for index in range(n_train,(n_train+n_test)):
img = dir+str(index)+".jpg"
with open(img,"rb") as f:
binary = f.read()
d = Datum()
d.add_binary("image",binary)
testdata.append([d])
testlabels.append(labels[index][1])
print "num of test data :",len(testdata)
return testdata
def get_testdata(labels):
testdata = []
testlabels = []
for index in range(n_train,(n_train+n_test)):
imgfile = "{}.jpg"
img = os.path.join(dir, imgfile.format(index))
with open(img,"rb") as f:
binary = f.read()
d = Datum()
d.add_binary("image",binary)
testdata.append([d])
testlabels.append(labels[index][1])
print ("num of test data :",len(testdata))
return testdata
def get_testdata(labels, data):
testdata = []
with open(data, "rb") as f:
for i in range(len(labels)):
binary = f.read(28 * 28)
d = Datum()
d.add_binary("image", binary)
# reader = csv.reader(f)
# for row in reader:
# d = Datum()
# d.add_binary("image",row)
testdata.append([d])
print "num of test data :", len(testdata)
return testdata
def get_testdata(labels):
testdata = []
testlabels = []
for index in range(n_train, (n_train + n_test)):
imgfile = "{}.jpg"
img = os.path.join(dir, imgfile.format(index))
with open(img, "rb") as f:
binary = f.read()
d = Datum()
d.add_binary("image", binary)
testdata.append([d])
testlabels.append(labels[index][1])
print("num of test data :", len(testdata))
return testdata
def get_traindata(labels, data):
traindata = []
with open(data, "rb") as f:
for i in range(len(labels)):
binary = f.read(28 * 28)
d = Datum()
d.add_binary("image", binary)
traindata.append([labels[i], d])
# reader = csv.reader(f)
# for i,row in enumerate(reader):
# print row
# d = Datum()
# d.add_binary("image",row)
# traindata.append([labels[i],d])
print "num of train data :", len(traindata)
return traindata
def test_add_binary(self):
d = Datum()
d.add_binary('key', b('value'))
self.assertEqual(([], [], [['key', b('value')]]), d.to_msgpack())
def gen_datum(filename):
with open(filename,"rb") as f:
binary = f.read()
d = Datum()
d.add_binary("image", binary)
return d
def make_datum():
d = Datum()
d.add_string('string-key', 'str')
d.add_number('number-key', 1.0)
d.add_binary('binary-key', b'bin')
return d
def test_add_binary(self):
d = Datum()
d.add_binary('key', b('value'))
self.assertEquals(
([], [], [['key', b('value')]]),
d.to_msgpack())
def gen_datum(filename):
with open(filename, "rb") as f:
binary = f.read()
d = Datum()
d.add_binary("image", binary)
return d
#-*- coding:utf-8 -*-
import jubatus
from jubatus.common import Datum
"""
画像特徴抽出プラグインを試す
"""
# ファイルをバイナリモードで開く
with open("./dataset/Lenna.jpg", "br") as f:
data = f.read()
d = Datum()
d.add_binary("image", data)
client = jubatus.Weight("127.0.0.1", 9199, "")
res = client.calc_weight(d)
print(res)
