support qwen-image-layered-control

examples/qwen_image/model_inference/Qwen-Image-Layered-Control.py

@@ -0,0 +1,34 @@
+from diffsynth.pipelines.qwen_image import QwenImagePipeline, ModelConfig
+from modelscope import snapshot_download
+from PIL import Image
+import torch
+
+
+pipe = QwenImagePipeline.from_pretrained(
+    torch_dtype=torch.bfloat16,
+    device="cuda",
+    model_configs=[
+        ModelConfig(model_id="DiffSynth-Studio/Qwen-Image-Layered-Control", 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-Layered", origin_file_pattern="vae/diffusion_pytorch_model.safetensors"),
+    ],
+    processor_config=ModelConfig(model_id="Qwen/Qwen-Image-Edit", origin_file_pattern="processor/"),
+)
+
+snapshot_download(
+    model_id="DiffSynth-Studio/Qwen-Image-Layered-Control",
+    allow_file_pattern="assets/image_1_input.png",
+    local_dir="data/layered_input"
+)
+
+prompt = "A cartoon skeleton character wearing a purple hat and holding a gift box"
+input_image = Image.open("data/layered_input/assets/image_1_input.png").convert("RGBA").resize((1024, 1024))
+images = pipe(
+    prompt,
+    seed=0,
+    num_inference_steps=30, cfg_scale=4,
+    height=1024, width=1024,
+    layer_input_image=input_image,
+    layer_num=0,
+)
+images[0].save("image.png")