AI/diffusers
1
0
Fork 0
mirror of https://github.com/huggingface/diffusers.git synced 2026-01-27 17:22:53 +03:00
Code Activity

Add LANCZOS as default interplotation mode. (#11463)

Browse Source 
* Add LANCZOS as default interplotation mode.

* LANCZOS as default interplotation

* LANCZOS as default interplotation mode

* Added LANCZOS as default interplotation mode
This commit is contained in:
Vaibhav Kumawat
2025-04-30 23:52:38 +05:30
committed by GitHub
parent 38ced7ee59
commit daf0a23958
1 changed files with 41 additions and 3 deletions
Download Patch File Download Diff File Expand all files Collapse all files

44
examples/controlnet/train_controlnet_sdxl.py
View File

@@ -134,7 +134,25 @@ def log_validation(vae, unet, controlnet, args, accelerator, weight_dtype, step,
for validation_prompt, validation_image in zip(validation_prompts, validation_images):
validation_image = Image.open(validation_image).convert("RGB")
validation_image = validation_image.resize((args.resolution, args.resolution))
try:
interpolation = getattr(transforms.InterpolationMode, args.image_interpolation_mode.upper())
except (AttributeError, KeyError):
supported_interpolation_modes = [
f.lower() for f in dir(transforms.InterpolationMode) if not f.startswith("__") and not f.endswith("__")
]
raise ValueError(
f"Interpolation mode {args.image_interpolation_mode} is not supported. "
f"Please select one of the following: {', '.join(supported_interpolation_modes)}"
)
transform = transforms.Compose(
[
transforms.Resize(args.resolution, interpolation=interpolation),
transforms.CenterCrop(args.resolution),
]
)
validation_image = transform(validation_image)
images = []
@@ -587,6 +605,15 @@ def parse_args(input_args=None):
" more information see https://huggingface.co/docs/accelerate/v0.17.0/en/package_reference/accelerator#accelerate.Accelerator"
),
)
parser.add_argument(
"--image_interpolation_mode",
type=str,
default="lanczos",
choices=[
f.lower() for f in dir(transforms.InterpolationMode) if not f.startswith("__") and not f.endswith("__")
],
help="The image interpolation method to use for resizing images.",
)
if input_args is not None:
args = parser.parse_args(input_args)
@@ -732,9 +759,20 @@ def encode_prompt(prompt_batch, text_encoders, tokenizers, proportion_empty_prom
def prepare_train_dataset(dataset, accelerator):
try:
interpolation_mode = getattr(transforms.InterpolationMode, args.image_interpolation_mode.upper())
except (AttributeError, KeyError):
supported_interpolation_modes = [
f.lower() for f in dir(transforms.InterpolationMode) if not f.startswith("__") and not f.endswith("__")
]
raise ValueError(
f"Interpolation mode {args.image_interpolation_mode} is not supported. "
f"Please select one of the following: {', '.join(supported_interpolation_modes)}"
)
image_transforms = transforms.Compose(
[
transforms.Resize(args.resolution, interpolation=transforms.InterpolationMode.BILINEAR),
transforms.Resize(args.resolution, interpolation=interpolation_mode),
transforms.CenterCrop(args.resolution),
transforms.ToTensor(),
transforms.Normalize([0.5], [0.5]),
@@ -743,7 +781,7 @@ def prepare_train_dataset(dataset, accelerator):
conditioning_image_transforms = transforms.Compose(
[
transforms.Resize(args.resolution, interpolation=transforms.InterpolationMode.BILINEAR),
transforms.Resize(args.resolution, interpolation=interpolation_mode),
transforms.CenterCrop(args.resolution),
transforms.ToTensor(),
]