Qwen-Image-Layered-MRP-MLX/src/mflux/generate_fill.py
2025-07-17 12:00:40 +02:00

63 lines
2.2 KiB
Python

from mflux.callbacks.callback_manager import CallbackManager
from mflux.config.config import Config
from mflux.error.exceptions import PromptFileReadError, StopImageGenerationException
from mflux.flux_tools.fill.flux_fill import Flux1Fill
from mflux.ui import defaults as ui_defaults
from mflux.ui.cli.parsers import CommandLineParser
from mflux.ui.prompt_utils import get_effective_prompt
def main():
# 0. Parse command line arguments
parser = CommandLineParser(description="Generate an image using the fill tool to complete masked areas.")
parser.add_general_arguments()
parser.add_model_arguments(require_model_arg=False)
parser.add_lora_arguments()
parser.add_image_generator_arguments(supports_metadata_config=False)
parser.add_fill_arguments()
parser.add_output_arguments()
args = parser.parse_args()
# 0. Default to a higher guidance value for fill related tasks.
if args.guidance is None:
args.guidance = ui_defaults.DEFAULT_DEV_FILL_GUIDANCE
# 1. Load the model
flux = Flux1Fill(
quantize=args.quantize,
local_path=args.path,
lora_paths=args.lora_paths,
lora_scales=args.lora_scales,
)
# 2. Register callbacks
memory_saver = CallbackManager.register_callbacks(args=args, flux=flux)
try:
for seed in args.seed:
# 3. Generate an image for each seed value
image = flux.generate_image(
seed=seed,
prompt=get_effective_prompt(args),
config=Config(
num_inference_steps=args.steps,
height=args.height,
width=args.width,
guidance=args.guidance,
image_path=args.image_path,
masked_image_path=args.masked_image_path,
),
)
# 4. Save the image
image.save(path=args.output.format(seed=seed), export_json_metadata=args.metadata)
except (StopImageGenerationException, PromptFileReadError) as exc:
print(exc)
finally:
if memory_saver:
print(memory_saver.memory_stats())
if __name__ == "__main__":
main()