support qwen-image-edit

This commit is contained in:
mi804
2025-08-18 16:07:45 +08:00
parent 7dc49bd036
commit 9f6922bba9
14 changed files with 212 additions and 19 deletions

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@@ -43,6 +43,7 @@ image.save("image.jpg")
|Model ID|Inference|Low VRAM Inference|Full Training|Validation after Full Training|LoRA Training|Validation after LoRA Training|
|-|-|-|-|-|-|-|
|[Qwen/Qwen-Image](https://www.modelscope.cn/models/Qwen/Qwen-Image)|[code](./model_inference/Qwen-Image.py)|[code](./model_inference_low_vram/Qwen-Image.py)|[code](./model_training/full/Qwen-Image.sh)|[code](./model_training/validate_full/Qwen-Image.py)|[code](./model_training/lora/Qwen-Image.sh)|[code](./model_training/validate_lora/Qwen-Image.py)|
|[Qwen/Qwen-Image-Edit](https://www.modelscope.cn/models/Qwen/Qwen-Image-Edit)|[code](./model_inference/Qwen-Image-Edit.py)|[code](./model_inference_low_vram/Qwen-Image-Edit.py)|[code](./model_training/full/Qwen-Image-Edit.sh)|[code](./model_training/validate_full/Qwen-Image-Edit.py)|[code](./model_training/lora/Qwen-Image-Edit.sh)|[code](./model_training/validate_lora/Qwen-Image-Edit.py)|
|[DiffSynth-Studio/Qwen-Image-Distill-Full](https://www.modelscope.cn/models/DiffSynth-Studio/Qwen-Image-Distill-Full)|[code](./model_inference/Qwen-Image-Distill-Full.py)|[code](./model_inference_low_vram/Qwen-Image-Distill-Full.py)|[code](./model_training/full/Qwen-Image-Distill-Full.sh)|[code](./model_training/validate_full/Qwen-Image-Distill-Full.py)|[code](./model_training/lora/Qwen-Image-Distill-Full.sh)|[code](./model_training/validate_lora/Qwen-Image-Distill-Full.py)|
|[DiffSynth-Studio/Qwen-Image-Distill-LoRA](https://www.modelscope.cn/models/DiffSynth-Studio/Qwen-Image-Distill-LoRA)|[code](./model_inference/Qwen-Image-Distill-LoRA.py)|[code](./model_inference_low_vram/Qwen-Image-Distill-LoRA.py)|-|-|-|-|
|[DiffSynth-Studio/Qwen-Image-EliGen](https://www.modelscope.cn/models/DiffSynth-Studio/Qwen-Image-EliGen)|[code](./model_inference/Qwen-Image-EliGen.py)|[code](./model_inference_low_vram/Qwen-Image-EliGen.py)|-|-|[code](./model_training/lora/Qwen-Image-EliGen.sh)|[code](./model_training/validate_lora/Qwen-Image-EliGen.py)|
@@ -235,6 +236,8 @@ The script includes the following parameters:
* `--model_paths`: Model paths to load. In JSON format.
* `--model_id_with_origin_paths`: Model ID with original paths, e.g., Qwen/Qwen-Image:transformer/diffusion_pytorch_model*.safetensors. Separate with commas.
* `--tokenizer_path`: Tokenizer path. Leave empty to auto-download.
* `--edit_model`: Whether to use Qwen-Image-Edit. If True, the model will be used for image editing.
* `--processor_path`: Path to the processor of Qwen-Image-Edit. Leave empty to auto-download.
* Training
* `--learning_rate`: Learning rate.
* `--weight_decay`: Weight decay.

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@@ -43,6 +43,7 @@ image.save("image.jpg")
|模型 ID|推理|低显存推理|全量训练|全量训练后验证|LoRA 训练|LoRA 训练后验证|
|-|-|-|-|-|-|-|
|[Qwen/Qwen-Image](https://www.modelscope.cn/models/Qwen/Qwen-Image)|[code](./model_inference/Qwen-Image.py)|[code](./model_inference_low_vram/Qwen-Image.py)|[code](./model_training/full/Qwen-Image.sh)|[code](./model_training/validate_full/Qwen-Image.py)|[code](./model_training/lora/Qwen-Image.sh)|[code](./model_training/validate_lora/Qwen-Image.py)|
|[Qwen/Qwen-Image-Edit](https://www.modelscope.cn/models/Qwen/Qwen-Image-Edit)|[code](./model_inference/Qwen-Image-Edit.py)|[code](./model_inference_low_vram/Qwen-Image-Edit.py)|[code](./model_training/full/Qwen-Image-Edit.sh)|[code](./model_training/validate_full/Qwen-Image-Edit.py)|[code](./model_training/lora/Qwen-Image-Edit.sh)|[code](./model_training/validate_lora/Qwen-Image-Edit.py)|
|[DiffSynth-Studio/Qwen-Image-Distill-Full](https://www.modelscope.cn/models/DiffSynth-Studio/Qwen-Image-Distill-Full)|[code](./model_inference/Qwen-Image-Distill-Full.py)|[code](./model_inference_low_vram/Qwen-Image-Distill-Full.py)|[code](./model_training/full/Qwen-Image-Distill-Full.sh)|[code](./model_training/validate_full/Qwen-Image-Distill-Full.py)|[code](./model_training/lora/Qwen-Image-Distill-Full.sh)|[code](./model_training/validate_lora/Qwen-Image-Distill-Full.py)|
|[DiffSynth-Studio/Qwen-Image-Distill-LoRA](https://www.modelscope.cn/models/DiffSynth-Studio/Qwen-Image-Distill-LoRA)|[code](./model_inference/Qwen-Image-Distill-LoRA.py)|[code](./model_inference_low_vram/Qwen-Image-Distill-LoRA.py)|-|-|-|-|
|[DiffSynth-Studio/Qwen-Image-EliGen](https://www.modelscope.cn/models/DiffSynth-Studio/Qwen-Image-EliGen)|[code](./model_inference/Qwen-Image-EliGen.py)|[code](./model_inference_low_vram/Qwen-Image-EliGen.py)|-|-|[code](./model_training/lora/Qwen-Image-EliGen.sh)|[code](./model_training/validate_lora/Qwen-Image-EliGen.py)|
@@ -235,6 +236,8 @@ Qwen-Image 系列模型训练通过统一的 [`./model_training/train.py`](./mod
* `--model_paths`: 要加载的模型路径。JSON 格式。
* `--model_id_with_origin_paths`: 带原始路径的模型 ID例如 Qwen/Qwen-Image:transformer/diffusion_pytorch_model*.safetensors。用逗号分隔。
* `--tokenizer_path`: tokenizer 路径,留空将会自动下载。
* `--edit_model`:是否使用 Qwen-Image-Edit。若为 True则将使用该模型进行图像编辑。
* `--processor_path`Qwen-Image-Edit 的 processor 路径。留空则自动下载。
* 训练
* `--learning_rate`: 学习率。
* `--weight_decay`:权重衰减大小。

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@@ -0,0 +1,22 @@
from diffsynth.pipelines.qwen_image import QwenImagePipeline, ModelConfig
import torch
pipe = QwenImagePipeline.from_pretrained(
torch_dtype=torch.bfloat16,
device="cuda",
model_configs=[
ModelConfig(model_id="Qwen/Qwen-Image-Edit", origin_file_pattern="transformer/diffusion_pytorch_model*.safetensors"),
ModelConfig(model_id="Qwen/Qwen-Image", origin_file_pattern="text_encoder/model*.safetensors"),
ModelConfig(model_id="Qwen/Qwen-Image", origin_file_pattern="vae/diffusion_pytorch_model.safetensors"),
],
tokenizer_config=None,
processor_config=ModelConfig(model_id="Qwen/Qwen-Image-Edit", origin_file_pattern="processor/"),
)
prompt = "精致肖像,水下少女,蓝裙飘逸,发丝轻扬,光影透澈,气泡环绕,面容恬静,细节精致,梦幻唯美。"
image = pipe(prompt=prompt, seed=0, num_inference_steps=40, height=1024, width=1024)
image.save("image1.jpg")
prompt = "将裙子改为粉色"
for seed in range(1, 10):
image = pipe(prompt, edit_image=image, seed=seed, num_inference_steps=40, height=1024, width=1024)
image.save(f"image2_{seed}.jpg")

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@@ -0,0 +1,24 @@
from diffsynth.pipelines.qwen_image import QwenImagePipeline, ModelConfig
import torch
pipe = QwenImagePipeline.from_pretrained(
torch_dtype=torch.bfloat16,
device="cuda",
model_configs=[
ModelConfig(model_id="Qwen/Qwen-Image-Edit", origin_file_pattern="transformer/diffusion_pytorch_model*.safetensors", offload_device="cpu", offload_dtype=torch.float8_e4m3fn),
ModelConfig(model_id="Qwen/Qwen-Image", origin_file_pattern="text_encoder/model*.safetensors", offload_device="cpu", offload_dtype=torch.float8_e4m3fn),
ModelConfig(model_id="Qwen/Qwen-Image", origin_file_pattern="vae/diffusion_pytorch_model.safetensors", offload_device="cpu", offload_dtype=torch.float8_e4m3fn),
],
tokenizer_config=None,
processor_config=ModelConfig(model_id="Qwen/Qwen-Image-Edit", origin_file_pattern="processor/"),
)
pipe.enable_vram_management()
prompt = "精致肖像,水下少女,蓝裙飘逸,发丝轻扬,光影透澈,气泡环绕,面容恬静,细节精致,梦幻唯美。"
image = pipe(prompt=prompt, seed=0, num_inference_steps=40, height=1024, width=1024)
image.save("image1.jpg")
prompt = "将裙子改为粉色"
for seed in range(1, 10):
image = pipe(prompt, edit_image=image, seed=seed, num_inference_steps=40, height=1024, width=1024)
image.save(f"image2_{seed}.jpg")

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@@ -0,0 +1,14 @@
accelerate launch --config_file examples/qwen_image/model_training/full/accelerate_config_zero2offload.yaml examples/qwen_image/model_training/train.py \
--edit_model \
--dataset_base_path data/example_image_dataset \
--dataset_metadata_path data/example_image_dataset/metadata_edit.csv \
--max_pixels 1048576 \
--dataset_repeat 50 \
--model_id_with_origin_paths "Qwen/Qwen-Image-Edit:transformer/diffusion_pytorch_model*.safetensors,Qwen/Qwen-Image:text_encoder/model*.safetensors,Qwen/Qwen-Image:vae/diffusion_pytorch_model.safetensors" \
--learning_rate 1e-5 \
--num_epochs 2 \
--remove_prefix_in_ckpt "pipe.dit." \
--output_path "./models/train/Qwen-Image-Edit_full" \
--trainable_models "dit" \
--use_gradient_checkpointing \
--find_unused_parameters

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@@ -0,0 +1,17 @@
accelerate launch examples/qwen_image/model_training/train.py \
--edit_model \
--dataset_base_path data/example_image_dataset \
--dataset_metadata_path data/example_image_dataset/metadata_edit.csv \
--max_pixels 1048576 \
--dataset_repeat 50 \
--model_id_with_origin_paths "Qwen/Qwen-Image-Edit:transformer/diffusion_pytorch_model*.safetensors,Qwen/Qwen-Image:text_encoder/model*.safetensors,Qwen/Qwen-Image:vae/diffusion_pytorch_model.safetensors" \
--learning_rate 1e-4 \
--num_epochs 5 \
--remove_prefix_in_ckpt "pipe.dit." \
--output_path "./models/train/Qwen-Image-Edit_lora" \
--lora_base_model "dit" \
--lora_target_modules "to_q,to_k,to_v,add_q_proj,add_k_proj,add_v_proj,to_out.0,to_add_out,img_mlp.net.2,img_mod.1,txt_mlp.net.2,txt_mod.1" \
--lora_rank 32 \
--use_gradient_checkpointing \
--dataset_num_workers 8 \
--find_unused_parameters

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@@ -11,7 +11,7 @@ class QwenImageTrainingModule(DiffusionTrainingModule):
def __init__(
self,
model_paths=None, model_id_with_origin_paths=None,
tokenizer_path=None,
tokenizer_path=None, processor_path=None, edit_model=False,
trainable_models=None,
lora_base_model=None, lora_target_modules="", lora_rank=32, lora_checkpoint=None,
use_gradient_checkpointing=True,
@@ -27,11 +27,15 @@ class QwenImageTrainingModule(DiffusionTrainingModule):
if model_id_with_origin_paths is not None:
model_id_with_origin_paths = model_id_with_origin_paths.split(",")
model_configs += [ModelConfig(model_id=i.split(":")[0], origin_file_pattern=i.split(":")[1]) for i in model_id_with_origin_paths]
if tokenizer_path is not None:
self.pipe = QwenImagePipeline.from_pretrained(torch_dtype=torch.bfloat16, device="cpu", model_configs=model_configs, tokenizer_config=ModelConfig(tokenizer_path))
else:
self.pipe = QwenImagePipeline.from_pretrained(torch_dtype=torch.bfloat16, device="cpu", model_configs=model_configs)
if edit_model:
tokenizer_config = None
processor_config = ModelConfig(model_id="Qwen/Qwen-Image-Edit", origin_file_pattern="processor/") if processor_path is None else ModelConfig(processor_path)
else:
tokenizer_config = ModelConfig(model_id="Qwen/Qwen-Image", origin_file_pattern="tokenizer/") if tokenizer_path is None else ModelConfig(tokenizer_path)
processor_config = None
self.pipe = QwenImagePipeline.from_pretrained(torch_dtype=torch.bfloat16, device="cpu", model_configs=model_configs, tokenizer_config=tokenizer_config, processor_config=processor_config)
# Reset training scheduler (do it in each training step)
self.pipe.scheduler.set_timesteps(1000, training=True)
@@ -115,6 +119,8 @@ if __name__ == "__main__":
model_paths=args.model_paths,
model_id_with_origin_paths=args.model_id_with_origin_paths,
tokenizer_path=args.tokenizer_path,
processor_path=args.processor_path,
edit_model=args.edit_model,
trainable_models=args.trainable_models,
lora_base_model=args.lora_base_model,
lora_target_modules=args.lora_target_modules,

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@@ -0,0 +1,22 @@
import torch
from PIL import Image
from diffsynth.pipelines.qwen_image import QwenImagePipeline, ModelConfig
from diffsynth import load_state_dict
pipe = QwenImagePipeline.from_pretrained(
torch_dtype=torch.bfloat16,
device="cuda",
model_configs=[
ModelConfig(model_id="Qwen/Qwen-Image-Edit", origin_file_pattern="transformer/diffusion_pytorch_model*.safetensors"),
ModelConfig(model_id="Qwen/Qwen-Image", origin_file_pattern="text_encoder/model*.safetensors"),
ModelConfig(model_id="Qwen/Qwen-Image", origin_file_pattern="vae/diffusion_pytorch_model.safetensors"),
],
tokenizer_config=None,
processor_config=ModelConfig(model_id="Qwen/Qwen-Image-Edit", origin_file_pattern="processor/"),
)
state_dict = load_state_dict("models/train/Qwen-Image-Edit_full/epoch-1.safetensors")
prompt = "将裙子改为粉色"
image = Image.open("data/example_image_dataset/edit/image1.jpg").resize((1024, 1024))
image = pipe(prompt, edit_image=image, seed=0, num_inference_steps=40, height=1024, width=1024)
image.save(f"image.jpg")

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@@ -0,0 +1,21 @@
import torch
from PIL import Image
from diffsynth.pipelines.qwen_image import QwenImagePipeline, ModelConfig
pipe = QwenImagePipeline.from_pretrained(
torch_dtype=torch.bfloat16,
device="cuda",
model_configs=[
ModelConfig(model_id="Qwen/Qwen-Image-Edit", origin_file_pattern="transformer/diffusion_pytorch_model*.safetensors"),
ModelConfig(model_id="Qwen/Qwen-Image", origin_file_pattern="text_encoder/model*.safetensors"),
ModelConfig(model_id="Qwen/Qwen-Image", origin_file_pattern="vae/diffusion_pytorch_model.safetensors"),
],
tokenizer_config=None,
processor_config=ModelConfig(model_id="Qwen/Qwen-Image-Edit", origin_file_pattern="processor/"),
)
pipe.load_lora(pipe.dit, "models/train/Qwen-Image-Edit_lora/epoch-4.safetensors")
prompt = "将裙子改为粉色"
image = Image.open("data/example_image_dataset/edit/image1.jpg").resize((1024, 1024))
image = pipe(prompt, edit_image=image, seed=0, num_inference_steps=40, height=1024, width=1024)
image.save(f"image.jpg")