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**Describe the bug**
A clear and concise description of what the bug is.
If applicabl…
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Hi, thanks for your great work which I'm referencing in my version of craft. I noticed that in the training [example](https://keras-ocr.readthedocs.io/en/latest/examples/end_to_end_training.html#) you…
ghost updated
2 years ago
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Hi there, just adding this as I am unable to access the google drive for the pretrained weights as I do not have access. Are you planning on re-releasing this availability?
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For the following code:
```
import torch, torchvision
from efficientnet_pytorch import EfficientNet
from tqdm import tqdm
def main(l):
model = EfficientNet.from_pretrained(model_name='ef…
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Pretrained weights won't give you results like the demo you showed, or even bad ones. I have no doubts about your work.
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Hi @siyuanliii,
Thanks for this great work! I am excited for the code release!
I am reaching you about the integration with the 🤗 [hub](https://huggingface.co/models) from day 0, so you can trac…
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Thanks for your awesome work. If possible, could the pretrained MAE or ImageNet weights on the SAM encoder (ViT with input size 1024) be released? Since the encoder is different from MAE or ImageNet p…
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First of all, thank you for your outstanding contribution! However, I encountered a problem when using the promax model.
There is a mismatch in the expected shape of the tensor weights when trying to…
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Thank you very much for sharing your implementation. I am learning a lot from your Land_Cover_Segmentation.ipynb file.
Unfortunately, I cannot find the file "Land_Cover_Segmentation.ipynb" to load th…
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![image](https://github.com/1180300419/imperfect-deweathering/assets/23092190/03421816-477f-49bf-a9aa-1e8b6a1a66f0)
It is really a great work for imperfect deweathering. Herein I am writing to in…