Create app2.py

app2.py

@@ -0,0 +1,60 @@
+import argparse
+import os
+import torch
+from diffusers import DiffusionPipeline
+
+def main():
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--prompt", type=str, required=True, help="输入提示词")
+    parser.add_argument("--seed", type=int, default=42, help="随机种子 (0 表示随机)")
+    parser.add_argument("--width", type=int, default=1664, help="图像宽度")
+    parser.add_argument("--height", type=int, default=928, help="图像高度")
+    args = parser.parse_args()
+
+    model_name = "Qwen/Qwen-Image"
+
+    # Load the pipeline
+    if torch.cuda.is_available():
+        torch_dtype = torch.bfloat16
+        device = "cuda"
+    else:
+        torch_dtype = torch.float32
+        device = "cpu"
+
+    pipe = DiffusionPipeline.from_pretrained(model_name, torch_dtype=torch_dtype)
+    pipe = pipe.to(device)
+
+    positive_magic = {
+        "en": ", Ultra HD, 4K, cinematic composition.",  # for english prompt
+        "zh": ", 超清，4K，电影级构图."  # for chinese prompt
+    }
+
+    negative_prompt = " "  # Recommended if you don't use a negative prompt.
+
+    # 生成器（0 = 随机种子，不固定）
+    generator = None if args.seed == 0 else torch.Generator(device=device).manual_seed(args.seed)
+
+    # Generate image
+    image = pipe(
+        prompt=args.prompt + positive_magic["en"],
+        negative_prompt=negative_prompt,
+        width=args.width,
+        height=args.height,
+        num_inference_steps=50,
+        true_cfg_scale=4.0,
+        generator=generator
+    ).images[0]
+
+    # 输出目录
+    output_dir = os.path.abspath("output")
+    os.makedirs(output_dir, exist_ok=True)
+
+    # 固定文件名
+    output_path = os.path.join(output_dir, "output.png")
+    image.save(output_path)
+
+    seed_info = "random" if args.seed == 0 else args.seed
+    print(f"✅ Image saved at: {output_path} (seed={seed_info}, size={args.width}x{args.height})")
+
+if __name__ == "__main__":
+    main()