haiyang-w / git Goto Github PK

I've encountered the following warnings when trying fast-mode,
I've tried loading BlipTokenizer, but why turned out to be the "BlipTokenizer" warning?

The tokenizer class you load from this checkpoint is not the same type as the class this function is called from. It may result in unexpected tokenization.
The tokenizer class you load from this checkpoint is 'BertTokenizer'.
The class this function is called from is 'BlipTokenizer'.

Besides, my demo run on an offline env,
where I can not download pretrained weights online

Is there any suggestions? Many thanks!

I try to use this awesome model like below

but it's not working.

Could i ask you what is the problem?

Thank you!

Hi,

Thank you for the code and the Readme which are both very well organized. I am trying to setup the few-shot and zero-shot datasets. Is there any details I need to take account of?

Thank you!.

能否提供hugging face的demo试玩？

Hi,

Thanks for making the code public. I'm trying to run few shot learning on LoveDA dataset. Once I start training, I get the following error.

FileNotFoundError: [Errno 2] No such file or directory: 'data/loveDA/ann_dir/train/1040.png'

My loveDA folder structure is as follows:

GiT
|──data
│   ├── loveDA
│   │   ├── img_dir
│   │   │   ├── train
│   │   │   ├── val
│   │   │   ├── test
│   │   ├── ann_dir
│   │   │   ├── train
│   │   │   |      |----- 1040.png.json
│   │   │   ├── val

as described here: https://github.com/Haiyang-W/GiT/blob/main/tools/dataset_preprocess/dataset_prepare.md

However, I see in the same link that I should run python tools/dataset_converters/loveda.py /path/to/loveDA but I don't see the file in the cloned repo. If this code is needed to fix this issue, can you please provide me with the dataset_converter file for loveda dataset?

When using the large and huge few-shot configurations for loveda dataset, since the config uses both the loveda base config and the git_large config, there are overlapping keys. Issue can be resolved by creating a copy of loveda_base and replacing git_base with git_large and load_from base to large.

Is there any other way to fix this? Or am I missing something here?

Thank you!

I try to train the single detection task with
"bash tools/dist_train.sh configs/GiT/single_detection_base.py 1 --work-dir output/test"

Could i ask you how to solve the problem?

Thank you!