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