def test_read_img_caf_subtract_mean(self, mock_io): mock_io.load_image.return_value = \ np.array([[[0.01176471, 0.00784314, 0.00392157], [0.02352941, 0.01960784, 0.01568628] ], [[0.03529412, 0.03137255, 0.02745098], [0.04705882, 0.04313726, 0.03921569], ], [[0.05882353, 0.05490196, 0.05098039], [0.07058824, 0.06666667, 0.0627451 ] ], [[0.08235294, 0.07843138, 0.07450981], [0.09411765, 0.09019608, 0.08627451] ] ]) m = np.array((1., 2., 3.)) img = r.read_img_caf(self.path_img1, mean=m) for ch in range(3): for row in range(4): for col in range(2): assert_almost_equals(img[ch][row][col], self.img1[row][col][ch] - m[ch], places=5)
def test_read_img_caf_shape(self, mock_io): mock_io.load_image.return_value = np.array( [ [[0.01176471, 0.00784314, 0.00392157], [0.02352941, 0.01960784, 0.01568628]], [[0.03529412, 0.03137255, 0.02745098], [0.04705882, 0.04313726, 0.03921569]], [[0.05882353, 0.05490196, 0.05098039], [0.07058824, 0.06666667, 0.0627451]], [[0.08235294, 0.07843138, 0.07450981], [0.09411765, 0.09019608, 0.08627451]], ] ) assert_equal(r.read_img_caf(self.path_img1).shape, (3, 4, 2))
def test_read_img_caf_shape(self, mock_io): mock_io.load_image.return_value = \ np.array([[[0.01176471, 0.00784314, 0.00392157], [0.02352941, 0.01960784, 0.01568628] ], [[0.03529412, 0.03137255, 0.02745098], [0.04705882, 0.04313726, 0.03921569], ], [[0.05882353, 0.05490196, 0.05098039], [0.07058824, 0.06666667, 0.0627451 ] ], [[0.08235294, 0.07843138, 0.07450981], [0.09411765, 0.09019608, 0.08627451] ] ]) assert_equal(r.read_img_caf(self.path_img1).shape, (3, 4, 2))
def test_read_img_caf_pixels(self, mock_io): mock_io.load_image.return_value = np.array( [ [[0.01176471, 0.00784314, 0.00392157], [0.02352941, 0.01960784, 0.01568628]], [[0.03529412, 0.03137255, 0.02745098], [0.04705882, 0.04313726, 0.03921569]], [[0.05882353, 0.05490196, 0.05098039], [0.07058824, 0.06666667, 0.0627451]], [[0.08235294, 0.07843138, 0.07450981], [0.09411765, 0.09019608, 0.08627451]], ] ) img = r.read_img_caf(self.path_img1) for ch in range(3): for row in range(4): for col in range(2): assert_almost_equals(img[ch][row][col], self.img1[row][col][ch], places=5)