The mean [123.675, 116.28, 103.53] is in the order of BGR or RGB？

[yvanyin]

The mean [123.675, 116.28, 103.53] is in the order of BGR or RGB？

[JUGGHM]

Hello, thank you for your kind words!

But I have a question while using it. In the code, when normalizing the image, is the order of mean = torch.tensor([123.675, 116.28, 103.53]) in RGB or BGR?

I found that the line of code rgb_origin = cv2.imread(an['rgb'])[:, :, ::-1].copy().astype(np.float32) in

Metric3D/mono/utils/do_test.py

Line 244 in 377e6c6

rgb_origin = cv2.imread(an['rgb'])[:, :, ::-1].copy()

has already converted the default BGR format, which is read by cv2.imread(), to RGB when reading the image.
Then, in this line of code rgb = cv2.cvtColor(rgb, cv2.COLOR_BGR2RGB) in https://github.com/YvanYin/Metric3D/blob/377e6c6642d0aca7aaa5a19e58fdcf5d0fd3d910/mono/utils/do_test.py#L189C5-L189C47, there is another conversion, which means the image is converted back to the BGR order. However, your comment says "BGR->RGB", so I would like to know whether the mean used for normalization is in RGB order or BGR order?

If I understand correctly, this normalization method is used to match the pre-trained ConvNext. However, it seems there is ambiguity here. Did you normalize the data in the training process in the same way, following the BGR order?

Thanks for pointing out this issue. We will fix it now.

[xbillowy]

Thanks for your reply!

[boqian-li]

Hi, I wanna know why this line still exits: rgb_origin = cv2.imread(an['rgb'])[:, :, ::-1].copy()
I wanna know we should use RGB order or BGR order for the input of the model??? @JUGGHM