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)