def test_basic_usage(self):
		model_filename = 'tmp/basic_usage.pkl'
		recognizer = Recognizer()
		recognizer.load_data([
			'BLACK', 'BLUE', 'BROWN', 'GREEN',
			'PINK', 'WHITE', 'YELLOW',
			'CONE', 'MAPSCROLL', 'STONE',
			'NA',
		])
		recognizer.model = [RecognizerFlatten(), RecognizerSplit(), RecognizerPCA(), RecognizerSVM()]
		recognizer.fit()
		self.assertGreater(recognizer.score(), 0.9)
		recognizer.clear()
		recognizer.dump(model_filename)

		recognizer = Recognizer()
		recognizer.load(model_filename)
		data = Data()
		data.load_data([
			'BLACK', 'BLUE', 'BROWN', 'GREEN',
			'PINK', 'WHITE', 'YELLOW',
			'CONE', 'MAPSCROLL', 'STONE',
			'NA',
		])
		self.assertGreater(recognizer.score(data), 0.97)
	def test_dump_load(self):
		model_filename = 'tmp/test_model.pkl'
		self.subject.load_data(['BLACK', 'BLUE'])
		self.subject.model = [RecognizerFlatten(), RecognizerPCA(), RecognizerSVM()]
		self.subject.fit()
		self.subject.dump(model_filename)

		self.subject = Recognizer()
		self.subject.load(model_filename)
		data = Data()
		data.load_data(['BLACK', 'BLUE'])
		for X, y in zip(data.X, data.y):
			self.assertEqual(self.subject.predict(X), y)
class DataTest(unittest.TestCase):
	def setUp(self):
		self.original_base = ImageReader.base
		ImageReader.base = 'tests/fixtures/' + ImageReader.base

		self.subject = Data()

	def tearDown(self):
		ImageReader.base = self.original_base

	def test_load_data(self):
		self.subject.load_data(['BLACK', 'BLUE'])
		self.assertEqual(len(self.subject.X), len(self.subject.y))
		self.assertEqual(len(self.subject.X), 15)
Beispiel #4
0
class DataTest(unittest.TestCase):
    def setUp(self):
        self.original_base = ImageReader.base
        ImageReader.base = 'tests/fixtures/' + ImageReader.base

        self.subject = Data()

    def tearDown(self):
        ImageReader.base = self.original_base

    def test_load_data(self):
        self.subject.load_data(['BLACK', 'BLUE'])
        self.assertEqual(len(self.subject.X), len(self.subject.y))
        self.assertEqual(len(self.subject.X), 15)
Beispiel #5
0
    def test_dump_load(self):
        model_filename = 'tmp/test_model.pkl'
        self.subject.load_data(['BLACK', 'BLUE'])
        self.subject.model = [
            RecognizerFlatten(),
            RecognizerPCA(),
            RecognizerSVM()
        ]
        self.subject.fit()
        self.subject.dump(model_filename)

        self.subject = Recognizer()
        self.subject.load(model_filename)
        data = Data()
        data.load_data(['BLACK', 'BLUE'])
        for X, y in zip(data.X, data.y):
            self.assertEqual(self.subject.predict(X), y)
Beispiel #6
0
    def test_basic_usage(self):
        model_filename = 'tmp/basic_usage.pkl'
        recognizer = Recognizer()
        recognizer.load_data([
            'BLACK',
            'BLUE',
            'BROWN',
            'GREEN',
            'PINK',
            'WHITE',
            'YELLOW',
            'CONE',
            'MAPSCROLL',
            'STONE',
            'NA',
        ])
        recognizer.model = [
            RecognizerFlatten(),
            RecognizerSplit(),
            RecognizerPCA(),
            RecognizerSVM()
        ]
        recognizer.fit()
        self.assertGreater(recognizer.score(), 0.9)
        recognizer.clear()
        recognizer.dump(model_filename)

        recognizer = Recognizer()
        recognizer.load(model_filename)
        data = Data()
        data.load_data([
            'BLACK',
            'BLUE',
            'BROWN',
            'GREEN',
            'PINK',
            'WHITE',
            'YELLOW',
            'CONE',
            'MAPSCROLL',
            'STONE',
            'NA',
        ])
        self.assertGreater(recognizer.score(data), 0.97)
	def setUp(self):
		self.original_base = ImageReader.base
		ImageReader.base = 'tests/fixtures/' + ImageReader.base

		self.subject = Data()
Beispiel #8
0
    def setUp(self):
        self.original_base = ImageReader.base
        ImageReader.base = 'tests/fixtures/' + ImageReader.base

        self.subject = Data()