Where to obtain the flat_inputs for S3DIS dataset?

[whuhxb]

Hi Authors:

Where to obtain the   self.inputs['neighbor_last'] = flat_inputs[4 * num_layers + 4]    in line 40 of RandLANet.py? And, where to obtain the flat_inputs in the RandLANet code? Thanks.
Best,

Xiaobing

[inspirelt]

Hi, Xiaobing. The related codes are posted as follows,

https://github.com/MCG-NJU/CGA-Net/blob/e7a46cb4379eb3c7979074779909e051f01d9d31/examples/RandLA-Net/main_S3DIS.py#L178-L191

[whuhxb]

@inspirelt Hi， I have one question. The code you released with CGA on S3DIS dataset, what the result is? Is the mIoU result: 65.4?

[inspirelt]

@whuhxb Hi, the result of the code is 68.6% on Area 5 of S3DIS.

[whuhxb]

@inspirelt OK. I see. Thanks for your reply. The result 68.6% on Area 5 of S3DIS is using CloserLook3D backbone.

[whuhxb]

@inspirelt Hi, I found that I can't obtain the results on Area 5 of S3DIS using RandLANet reported in your paper, the improvement is smaller than your paper. I have no idea what the problem is.

[inspirelt]

Have you changed any experiment settings? If using the default settings, you may try to use some other checkpoint files (I mainly used the last two checkpoint files) for testing.

[whuhxb]

@inspirelt I used the default experiment settings. Using which checkpoint files for testing? Do you have any suggestion?

[whuhxb]

@inspirelt Hi，how to calculate the improved area as shown in Figure 5?

[inspirelt]

Sorry for the late reply. I use the last two saved checkpoint files for testing. The improved area is calculated by

right_origin = (pred_origin==gt_label)
right_cga = (pred_cga==gt_label)
improved_area = (right_origin==False and right_cga==True)