forgedit's Issues
Will it be possible to use this implementation with stable diffusion XL?
I'm really impressed by what you've achieved. Quick question: Is it possible to use this implementation with stable diffusion XL?
Thanks for your help!
GPU
Hello, can this project run on GPUs of V100,16G
Incorrect path to blip model
While running the DreamBoothForgedit I am stuck at this error:
accelerate launch src/sample_dreambooth_batch_textencoder.py --train=False --interpolation=vp
The following values were not passed to `accelerate launch` and had defaults used instead:
`--num_processes` was set to a value of `1`
`--num_machines` was set to a value of `1`
`--mixed_precision` was set to a value of `'no'`
`--dynamo_backend` was set to a value of `'no'`
To avoid this warning pass in values for each of the problematic parameters or run `accelerate config`.
Traceback (most recent call last):
File "/root/miniconda3/envs/forgedit/lib/python3.10/site-packages/transformers/utils/hub.py", line 398, in cached_file
resolved_file = hf_hub_download(
File "/root/miniconda3/envs/forgedit/lib/python3.10/site-packages/huggingface_hub/utils/_validators.py", line 106, in _inner_fn
validate_repo_id(arg_value)
File "/root/miniconda3/envs/forgedit/lib/python3.10/site-packages/huggingface_hub/utils/_validators.py", line 154, in validate_repo_id
raise HFValidationError(
huggingface_hub.errors.HFValidationError: Repo id must be in the form 'repo_name' or 'namespace/repo_name': '/mnt/bn/editdiffusion/Forgedit/models/blip-image-captioning-base'. Use `repo_type` argument if needed.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/gans/docker/files/Forgedit/src/sample_dreambooth_batch_textencoder.py", line 61, in <module>
processor = BlipProcessor.from_pretrained(blipmodel)
File "/root/miniconda3/envs/forgedit/lib/python3.10/site-packages/transformers/processing_utils.py", line 465, in from_pretrained
args = cls._get_arguments_from_pretrained(pretrained_model_name_or_path, **kwargs)
File "/root/miniconda3/envs/forgedit/lib/python3.10/site-packages/transformers/processing_utils.py", line 511, in _get_arguments_from_pretrained
args.append(attribute_class.from_pretrained(pretrained_model_name_or_path, **kwargs))
File "/root/miniconda3/envs/forgedit/lib/python3.10/site-packages/transformers/image_processing_utils.py", line 205, in from_pretrained
image_processor_dict, kwargs = cls.get_image_processor_dict(pretrained_model_name_or_path, **kwargs)
File "/root/miniconda3/envs/forgedit/lib/python3.10/site-packages/transformers/image_processing_utils.py", line 334, in get_image_processor_dict
resolved_image_processor_file = cached_file(
File "/root/miniconda3/envs/forgedit/lib/python3.10/site-packages/transformers/utils/hub.py", line 462, in cached_file
raise EnvironmentError(
OSError: Incorrect path_or_model_id: '/mnt/bn/editdiffusion/Forgedit/models/blip-image-captioning-base'. Please provide either the path to a local folder or the repo_id of a model on the Hub.
Traceback (most recent call last):
File "/root/miniconda3/envs/forgedit/bin/accelerate", line 8, in <module>
sys.exit(main())
File "/root/miniconda3/envs/forgedit/lib/python3.10/site-packages/accelerate/commands/accelerate_cli.py", line 47, in main
args.func(args)
File "/root/miniconda3/envs/forgedit/lib/python3.10/site-packages/accelerate/commands/launch.py", line 1023, in launch_command
simple_launcher(args)
File "/root/miniconda3/envs/forgedit/lib/python3.10/site-packages/accelerate/commands/launch.py", line 643, in simple_launcher
raise subprocess.CalledProcessError(returncode=process.returncode, cmd=cmd)
subprocess.CalledProcessError: Command '['/root/miniconda3/envs/forgedit/bin/python', 'src/sample_dreambooth_batch_textencoder.py', '--train=False', '--interpolation=vp']' returned non-zero exit status 1.
(forgedit) [email protected]:/gans/docker/files/Forgedit#
examples
The edited image is blurry.
About TEdBench
Could you please provide the way we can download the TEdBench text guided image editing benchmark?
Also is it possible to use your implementation with stable diffusion 2.1?
Thanks in advance.
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