Qwen-Image-Layered-MRP-MLX/src/mflux/upscale.py
2025-06-04 19:27:03 +02:00

57 lines
1.9 KiB
Python

from mflux import Config, Flux1Controlnet, ModelConfig, StopImageGenerationException
from mflux.callbacks.callback_manager import CallbackManager
from mflux.error.exceptions import PromptFileReadError
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="Upscale an image.")
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_controlnet_arguments()
parser.add_output_arguments()
args = parser.parse_args()
# 1. Load the model
flux = Flux1Controlnet(
model_config=ModelConfig.dev_controlnet_upscaler(),
quantize=args.quantize,
local_path=args.path,
lora_paths=args.lora_paths,
lora_scales=args.lora_scales,
)
# 2. Register the optional callbacks
memory_saver = CallbackManager.register_callbacks(args=args, flux=flux)
try:
for seed in args.seed:
# 3. Generate an upscaled image for each seed value
image = flux.generate_image(
seed=seed,
prompt=get_effective_prompt(args),
controlnet_image_path=args.controlnet_image_path,
config=Config(
num_inference_steps=args.steps,
height=args.height,
width=args.width,
controlnet_strength=args.controlnet_strength,
),
)
# 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()