def test_rgb2gray(self):
in_img = np.random.rand(10, 10, 3).astype(np.float32)
out_img = mmcv.rgb2gray(in_img)
computed_gray = (in_img[:, :, 0] * 0.299 + in_img[:, :, 1] * 0.587 +
in_img[:, :, 2] * 0.114)
assert_array_almost_equal(out_img, computed_gray, decimal=4)
out_img_3d = mmcv.rgb2gray(in_img, True)
assert out_img_3d.shape == (10, 10, 1)
assert_array_almost_equal(out_img_3d[..., 0], out_img, decimal=4)
def __call__(self, results):
"""
Args:
img (ndarray): Image to be converted to grayscale.
Returns:
ndarray: Randomly grayscaled image.
"""
for key in results.get('img_fields', ['img']):
img = results[key]
num_output_channels = img.shape[2]
if random.random() < self.gray_prob:
if num_output_channels > 1:
img = mmcv.rgb2gray(img)[:, :, None]
results[key] = np.dstack(
[img for _ in range(num_output_channels)])
return results
results[key] = img
return results
mmcv.imshow(img, win_name='test image', wait_time=200)
if flag_4:
# Color space conversion
"""
Supported conversion methods:
bgr2gray
gray2bgr
bgr2rgb
rgb2bgr
bgr2hsv
hsv2bgr
"""
img = mmcv.imread("asset/a.jpg")
img1 = mmcv.bgr2rgb(img)
img2 = mmcv.rgb2gray(img1)
img3 = mmcv.bgr2hsv(img)
mmcv.imshow(img1)
mmcv.imshow(img2)
mmcv.imshow(img3)
if flag_5:
# Resize
"""
There are three resize methods. All imresize_* methods have an argument return_scale, if this argument is False, then the return value is merely the resized image, otherwise is a tuple (resized_img, scale).
"""
img = mmcv.imread("asset/a.jpg")
dst_img = mmcv.imread("asset/b.jpg")
# resize to a given size
resized_img = mmcv.imresize(img, (1000, 600), return_scale=True)
