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import torch
from diffusers.utils import load_image, check_min_version
from controlnet_flux import FluxControlNetModel
from transformer_flux import FluxTransformer2DModel
from pipeline_flux_controlnet_inpaint import FluxControlNetInpaintingPipeline
import os
check_min_version("0.30.2")
# Set image path , mask path and prompt
# image_path='https://huggingface.co/alimama-creative/FLUX.1-dev-Controlnet-Inpainting-Alpha/resolve/main/images/bucket.png',
# mask_path='https://huggingface.co/alimama-creative/FLUX.1-dev-Controlnet-Inpainting-Alpha/resolve/main/images/bucket_mask.jpeg',
current_dir = os.path.dirname(os.path.abspath(__file__))
image_path = os.path.join(current_dir, "images_bucket.png")
mask_path = os.path.join(current_dir, "images_bucket_mask.jpeg")
prompt='a person wearing a white shoe, carrying a white bucket with text "Jitesh" on it with red color'
# print(f"Checkpoint file: {checkpoint_file}")
# Build pipeline
controlnet = FluxControlNetModel.from_pretrained("jiteshdhamaniya/alimama-creative-FLUX.1-dev-Controlnet-Inpainting-Alpha", torch_dtype=torch.bfloat16, local_files_only=True)
transformer = FluxTransformer2DModel.from_pretrained(
"black-forest-labs/FLUX.1-dev", subfolder='transformer', torch_dtype=torch.bfloat16, local_files_only=True
)
pipe = FluxControlNetInpaintingPipeline.from_pretrained(
"black-forest-labs/FLUX.1-dev",
controlnet=controlnet,
transformer=transformer,
torch_dtype=torch.bfloat16
).to("mps")
pipe.transformer.to(torch.bfloat16)
pipe.controlnet.to(torch.bfloat16)
# Load image and mask
size = (768, 768)
image = load_image(image_path).convert("RGB").resize(size)
mask = load_image(mask_path).convert("RGB").resize(size)
generator = torch.Generator(device="mps").manual_seed(24)
# Inpaint
result = pipe(
prompt=prompt,
height=size[1],
width=size[0],
control_image=image,
control_mask=mask,
num_inference_steps=28,
generator=generator,
controlnet_conditioning_scale=0.9,
guidance_scale=3.5,
negative_prompt="",
true_guidance_scale=1.0 # default: 3.5 for alpha and 1.0 for beta
).images[0]
result.save('flux_inpaint.png')
print("Successfully inpaint image")
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