Skip to content

Bugfix for dreambooth flux2 img2img2 #12825

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
leisuzz wants to merge 2 commits into
base: main
Choose a base branch
from
+18 −5
Open

Bugfix for dreambooth flux2 img2img2 #12825

Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
7587a50
Bugfix for dreambooth flux2 img2img2
leisuzz Dec 11, 2025
b0fcc81
Merge branch 'main' into flux2
sayakpaul Dec 13, 2025
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
23 changes: 18 additions & 5 deletions examples/dreambooth/train_dreambooth_lora_flux2_img2img.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -339,7 +339,7 @@ def parse_args(input_args=None):
"--instance_prompt",
type=str,
default=None,
required=True,
required=False,
help="The prompt with identifier specifying the instance, e.g. 'photo of a TOK dog', 'in the style of TOK'",
)
parser.add_argument(
Expand Down Expand Up @@ -827,15 +827,28 @@ def __init__(
dest_image = self.cond_images[i]
image_width, image_height = dest_image.size
if image_width * image_height > 1024 * 1024:
dest_image = Flux2ImageProcessor.image_processor._resize_to_target_area(dest_image, 1024 * 1024)
dest_image = Flux2ImageProcessor._resize_to_target_area(dest_image, 1024 * 1024)
image_width, image_height = dest_image.size

multiple_of = 2 ** (4 - 1) # 2 ** (len(vae.config.block_out_channels) - 1), temp!
image_width = (image_width // multiple_of) * multiple_of
image_height = (image_height // multiple_of) * multiple_of
dest_image = Flux2ImageProcessor.image_processor.preprocess(
image_processor = Flux2ImageProcessor()
dest_image = image_processor.preprocess(
dest_image, height=image_height, width=image_width, resize_mode="crop"
)
# Convert back to PIL
dest_image = dest_image.squeeze(0)
if dest_image.min() < 0:
dest_image = (dest_image + 1) / 2
dest_image = (torch.clamp(dest_image, 0, 1) * 255).byte().cpu()

if dest_image.shape[0] == 1:
# Gray scale image
dest_image = Image.fromarray(dest_image.squeeze().numpy(), mode="L")
else:
# RGB scale image: (C, H, W) -> (H, W, C)
dest_image = TF.to_pil_image(dest_image)

dest_image = exif_transpose(dest_image)
if not dest_image.mode == "RGB":
Expand Down Expand Up @@ -1419,9 +1432,9 @@ def _encode_single(prompt: str):
args.instance_prompt, text_encoding_pipeline
)

validation_image = load_image(args.validation_image_path).convert("RGB")
validation_kwargs = {"image": validation_image}
if args.validation_prompt is not None:
validation_image = load_image(args.validation_image_path).convert("RGB")
validation_kwargs = {"image": validation_image}
if args.remote_text_encoder:
validation_kwargs["prompt_embeds"] = compute_remote_text_embeddings(args.validation_prompt)
else:
Expand Down