File size: 1,193 Bytes
cbc09ea | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 | """VBVR-Pro-FLUX2-dev inference example.
Usage:
python example.py --model_path ./VBVR-Pro-FLUX2-dev
"""
import argparse
import torch
from PIL import Image
from diffusers import Flux2Pipeline
parser = argparse.ArgumentParser()
parser.add_argument("--model_path", type=str, default="VBVR-Pro-FLUX2-dev")
parser.add_argument("--image", type=str, required=True, help="Path to input image")
parser.add_argument("--prompt", type=str, required=True, help="Editing instruction")
parser.add_argument("--output", type=str, default="output.png")
parser.add_argument("--steps", type=int, default=50)
parser.add_argument("--seed", type=int, default=42)
args = parser.parse_args()
print(f"Loading model from: {args.model_path}")
pipe = Flux2Pipeline.from_pretrained(
args.model_path, torch_dtype=torch.bfloat16
)
pipe.enable_model_cpu_offload()
image = Image.open(args.image).convert("RGB")
print(f"Input image: {args.image} ({image.size[0]}x{image.size[1]})")
output = pipe(
image=image,
prompt=args.prompt,
num_inference_steps=args.steps,
guidance_scale=2.5,
generator=torch.manual_seed(args.seed),
).images[0]
output.save(args.output)
print(f"Saved to: {args.output}")
|