mirror of
https://github.com/modelscope/DiffSynth-Studio.git
synced 2026-03-18 22:08:13 +00:00
65 lines
1.9 KiB
Python
65 lines
1.9 KiB
Python
import torch
|
|
from diffsynth.pipelines.flux_image import FluxImagePipeline, ModelConfig
|
|
from PIL import Image
|
|
|
|
|
|
vram_config = {
|
|
"offload_dtype": torch.float8_e4m3fn,
|
|
"offload_device": "cpu",
|
|
"onload_dtype": torch.float8_e4m3fn,
|
|
"onload_device": "cpu",
|
|
"preparing_dtype": torch.float8_e4m3fn,
|
|
"preparing_device": "cuda",
|
|
"computation_dtype": torch.bfloat16,
|
|
"computation_device": "cuda",
|
|
}
|
|
pipe = FluxImagePipeline.from_pretrained(
|
|
torch_dtype=torch.bfloat16,
|
|
device="cuda",
|
|
model_configs=[
|
|
ModelConfig(model_id="black-forest-labs/FLUX.1-Kontext-dev", origin_file_pattern="flux1-kontext-dev.safetensors", **vram_config),
|
|
ModelConfig(model_id="black-forest-labs/FLUX.1-dev", origin_file_pattern="text_encoder/model.safetensors", **vram_config),
|
|
ModelConfig(model_id="black-forest-labs/FLUX.1-dev", origin_file_pattern="text_encoder_2/*.safetensors", **vram_config),
|
|
ModelConfig(model_id="black-forest-labs/FLUX.1-dev", origin_file_pattern="ae.safetensors", **vram_config),
|
|
],
|
|
vram_limit=torch.cuda.mem_get_info("cuda")[1] / (1024 ** 3) - 0.5,
|
|
)
|
|
|
|
image_1 = pipe(
|
|
prompt="a beautiful Asian long-haired female college student.",
|
|
embedded_guidance=2.5,
|
|
seed=1,
|
|
)
|
|
image_1.save("image_1.jpg")
|
|
|
|
image_2 = pipe(
|
|
prompt="transform the style to anime style.",
|
|
kontext_images=image_1,
|
|
embedded_guidance=2.5,
|
|
seed=2,
|
|
)
|
|
image_2.save("image_2.jpg")
|
|
|
|
image_3 = pipe(
|
|
prompt="let her smile.",
|
|
kontext_images=image_1,
|
|
embedded_guidance=2.5,
|
|
seed=3,
|
|
)
|
|
image_3.save("image_3.jpg")
|
|
|
|
image_4 = pipe(
|
|
prompt="let the girl play basketball.",
|
|
kontext_images=image_1,
|
|
embedded_guidance=2.5,
|
|
seed=4,
|
|
)
|
|
image_4.save("image_4.jpg")
|
|
|
|
image_5 = pipe(
|
|
prompt="move the girl to a park, let her sit on a chair.",
|
|
kontext_images=image_1,
|
|
embedded_guidance=2.5,
|
|
seed=5,
|
|
)
|
|
image_5.save("image_5.jpg") |