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try:
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from transformers import Qwen2_5_VLForConditionalGeneration
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print("✅ 成功导入！")
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except Exception as e:
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print("❌ 导入失败：", e)
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import traceback
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traceback.print_exc()
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen-Image-Edit",trust_remote_code=True)
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tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen-Image-Edit",trust_remote_code=True)
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import os
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from PIL import Image
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import torch
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from diffusers import QwenImageEditPipeline
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pipeline = QwenImageEditPipeline.from_pretrained("Qwen/Qwen-Image-Edit")
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print("pipeline loaded")
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pipeline.to(torch.bfloat16)
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pipeline.to("cuda")
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pipeline.set_progress_bar_config(disable=None)
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image = Image.open("./input.png").convert("RGB")
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prompt = "Change the rabbit's color to purple, with a flash light background."
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inputs = {
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"image": image,
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"prompt": prompt,
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"generator": torch.manual_seed(0),
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"true_cfg_scale": 4.0,
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"negative_prompt": " ",
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"num_inference_steps": 50,
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}
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with torch.inference_mode():
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output = pipeline(**inputs)
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output_image = output.images[0]
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output_image.save("output_image_edit.png")
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print("image saved at", os.path.abspath("output_image_edit.png")) |
