WindVChen

Yes, each should comprise degrade folder. The whole structure can also refer to #2. The degraded images in val or test are for the possible use of loss calculation. As...

You can refer to the ```Test Process``` part in the [README.md](https://github.com/WindVChen/DRENet#readme). Note that before you run the code, you should make sure you have changed the val path in [ship.yaml](https://github.com/WindVChen/DRENet/blob/main/data/ship.yaml)...

For the first error, I actually failed to find the mentioned codeline ```x=torch.from_numpy(x)```, as in the original code, the codeline in line 217, common.py is ```return self.conv(torch.cat([x[..., ::2, ::2], x[...,...

@ramdhan1989 Hi, the raised error is because there is an additional operation of calculating FLOPs and Params in YOLOv5. E.g., here: https://github.com/WindVChen/DRENet/blob/3325fa6b832b127a0ec1c7e2cf122665e60ad25e/models/yolo.py#L97-L99 Thus, you should change the value of the...

The variation of Flops is normal, as FLOPs is positively correlated with feature map size. Therefore, the larger the input image, the larger the FLOPs.

This value is set to ensure not too blurry for a pixel far away from object targets. If you apply the method on high-resolution images such as 16m, the value...

Sorry for my late reply. The setting of minDis seems OK. You can give it a try, and I think the difference of minDis will not affect the final result...

For Example 1, the current design will lead to a rather smooth curve, which may not achieve the goal of blurring the background.  Since the distance here is between...

@ramdhan1989 Hi, sorry for reply late. From your descriptions, the reason why degraded images generate slowly mainly comes from the input images' high resolution. The current code generates the degraded...

@ramdhan1989 Directly resize is not recommended, as it may loss some small targets and also not consistent with training phase (training with high spatial resolution, while testing with lower). A...