Comments (2)
The diffused estimator provides a initial estimation of x_0, then diffuse to one specific timestep, finally reverse back.
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The diffused estimator provides a initial estimation of x_0, then diffuse to one specific timestep, finally reverse back.
ok, thanks!
from difface.
Related Issues (20)
- self.loss_fun in trainer.py is not defined. HOT 1
- training time HOT 1
- Could you release your metric calculation script please? HOT 2
- adjust_lr() missing 1 required argument HOT 6
- Can't load diffused estimator (SwinIR) trained model HOT 1
- 使用现有模型,测试,返回错误,如何解决? HOT 2
- retrain swinIR based on pretrained model, but met ERROR [KeyError: 'state_dict'] HOT 4
- Can't run inference_difface.py HOT 1
- About ckpts HOT 1
- Please provide the./configs/inpainting_debug.yaml file HOT 2
- Does adjustment of lr work? HOT 3
- RuntimeError: CUDA error: invalid device ordinal CUDA kernel errors might be asynchronously reported at some other API call,so the stacktrace below might be incorrect. For debugging consider passing CUDA_LAUNCH_BLOCKING=1. HOT 2
- cv2.error: OpenCV(4.8.0) :-1: error: (-5:Bad argument) in function 'imencode' > Overload resolution failed: > - Can't parse 'params'. Sequence item with index 1 has a wrong type > - Can't parse 'params'. Sequence item with index 1 has a wrong type HOT 3
- Model weight preservation in the Train diffused estimator (SwinIR) stage. HOT 2
- training time
- SwinIR path error HOT 2
- module diffusers has no attribute DifFacePipeline HOT 2
- It's not convenient to change the cuda device when running inferrence script. HOT 1
- Train swinIR face restoration using FFHQ on 1024x1024 resolution HOT 2
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