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)
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)
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)