Comments (1)
We do not officially support changing the resolution on inference. For evaluation, we just upsample the generated images with cubic interpolation.
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Related Issues (20)
- The approximate training time for the video generation model HOT 3
- Bug in nuscenes_t_dataset HOT 1
- Your Loss is NaN HOT 9
- What's the meaning of several parametes in default.yaml? HOT 1
- How to use the pretrained weight "SDv1.5mv-rawbox_2023-09-07_18-39_224x400" to launch another train? HOT 3
- Adding objects HOT 1
- version of some packpages HOT 2
- Code for Quantitative Evaluation (Image Branch) HOT 1
- The training time for the entire nuscenes dataset is too long HOT 2
- Machine and time query request HOT 1
- Problems about training on one mechine 8 A100 HOT 7
- Issues related to FID calculation and BEVfusion HOT 7
- How long train 61 frames? HOT 5
- Can 61 frames pretrained weight be released? HOT 3
- Running on local URL: http://0.0.0.0:7860 To create a public link, set `share=True` in `launch()`. HOT 2
- docker images for magicdrive HOT 1
- ERROR: Could not build wheels for xformers, which is required to install pyproject.toml-based projects HOT 2
- Question about initialize class_tokens HOT 1
- AttributeError: 'NoneType' object has no attribute 'update' HOT 10
- cannot import name 'visualize_camera' from 'mmdet3d.core.utils'
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