def test_prediction(self):
x = TEST_DATA['pred']['x']
w = TEST_DATA['pred']['w']
theta = TEST_DATA['pred']['theta']
y = TEST_DATA['pred']['y']
y_computed = prediction(x, w, theta)
max_diff = np.max(np.abs(y - y_computed))
self.assertAlmostEqual(max_diff, 0, 6)
def test_prediction(self):
x = TEST_DATA['pred']['x']
w = TEST_DATA['pred']['w']
theta = TEST_DATA['pred']['theta']
y_expected = TEST_DATA['pred']['y']
y = prediction(x, w, theta)
self.assertEqual(np.shape(y), (50, 1))
np.testing.assert_almost_equal(y, y_expected)
def face_detect_patch(patch, w, theta):
patch = patch / 255.0
hog_patch = hog(patch)
return prediction(np.transpose(np.concatenate(([[1]], hog_patch))), w,
theta)