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Bugfix for dreambooth flux2 img2img2 (#12825)

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Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: Linoy Tsaban <57615435+linoytsaban@users.noreply.github.com>
This commit is contained in:
Leo Jiang
2026-01-09 00:04:44 -07:00
committed by GitHub
parent 2f66edc880
commit 08f8b7af9a
1 changed files with 18 additions and 5 deletions
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23
examples/dreambooth/train_dreambooth_lora_flux2_img2img.py
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@@ -346,7 +346,7 @@ 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(
@@ -835,15 +835,28 @@ class DreamBoothDataset(Dataset):
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":
@@ -1463,9 +1476,9 @@ def main(args):
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: