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Inference results of 640x1600 model is abnormal #49
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Have you changed |
You mean changing 'out_size_factor' when change bev res from 128x128 to 256x256 ? we have done this. |
And the 640x1600, 128x128 model is modified from your 'bev_depth_lss_r50_256x704_128x128_20e_cbgs_2key.py', the only difference is change following params: |
Hi! I want to know where (which file?) you change the bev res from 128x128 to 256x256 ? I can not found it T T. Best wishes!! |
Hello, I also encountered this problem and only made the same modification on the original code. Have you solved this problem? I have been troubled by this problem for a long time, looking forward to your reply. |
The config params of 640x1600 model is as follows:
![image](https://user-images.githubusercontent.com/27052480/187882247-e99115b8-5ea6-4253-8f14-5564a0362e23.png)
final_dim = (640, 1600)
backbone_conf['final_dim'] = final_dim
ida_aug_conf['final_dim'] = final_dim
ida_aug_conf['resize_lim'] = (0.94, 1.25)
The inference results is strange, only the instance in CAM_BACK fov seems to be normal, while objects in other cam's fov tend to miss a certain scale
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