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Code Issues Packages Projects Releases Wiki Activity

Support JoyAI-Image-Edit (#1393)

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* auto intergrate joyimage model

* joyimage pipeline

* train

* ready

* styling

* joyai-image docs

* update readme

* pr review
This commit is contained in:
Hong Zhang
2026-04-15 16:57:11 +08:00
committed by GitHub
parent 8f18e24597
commit 079e51c9f3
21 changed files with 2040 additions and 123 deletions
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51
examples/joyai_image/model_inference_low_vram/JoyAI-Image-Edit.py Normal file
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from diffsynth.pipelines.joyai_image import JoyAIImagePipeline, ModelConfig
import torch
from PIL import Image
from modelscope import dataset_snapshot_download
# Download dataset
dataset_snapshot_download(
dataset_id="DiffSynth-Studio/diffsynth_example_dataset",
local_dir="data/diffsynth_example_dataset",
allow_file_pattern="joyai_image/JoyAI-Image-Edit/*"
)
vram_config = {
"offload_dtype": torch.bfloat16,
"offload_device": "cpu",
"onload_dtype": torch.bfloat16,
"onload_device": "cpu",
"preparing_dtype": torch.bfloat16,
"preparing_device": "cuda",
"computation_dtype": torch.bfloat16,
"computation_device": "cuda",
}
pipe = JoyAIImagePipeline.from_pretrained(
torch_dtype=torch.bfloat16,
device="cuda",
model_configs=[
ModelConfig(model_id="jd-opensource/JoyAI-Image-Edit", origin_file_pattern="transformer/transformer.pth", **vram_config),
ModelConfig(model_id="jd-opensource/JoyAI-Image-Edit", origin_file_pattern="JoyAI-Image-Und/model*.safetensors", **vram_config),
ModelConfig(model_id="jd-opensource/JoyAI-Image-Edit", origin_file_pattern="vae/Wan2.1_VAE.pth", **vram_config),
],
processor_config=ModelConfig(model_id="jd-opensource/JoyAI-Image-Edit", origin_file_pattern="JoyAI-Image-Und/"),
vram_limit=torch.cuda.mem_get_info("cuda")[1] / (1024 ** 3) - 0.5,
)
# Use first sample from dataset
dataset_base_path = "data/diffsynth_example_dataset/joyai_image/JoyAI-Image-Edit"
prompt = "将裙子改为粉色"
edit_image = Image.open(f"{dataset_base_path}/edit/image1.jpg").convert("RGB")
output = pipe(
prompt=prompt,
edit_image=edit_image,
height=1024,
width=1024,
seed=0,
num_inference_steps=30,
cfg_scale=5.0,
)
output.save("output_joyai_edit_low_vram.png")