Update app.py

app.py

@@ -1,30 +1,31 @@
 import gradio as gr
 
 # 加载模型并配置
-model = gr.load("models/prithivMLmods/SD3.5-Large-Photorealistic-LoRA").launch()
+model = gr.load("models/prithivMLmods/SD3.5-Large-Photorealistic-LoRA")
+# .launch()
 
-# # 定义图像生成函数，添加seed参数
-# def generate_image(prompt, seed):
-#     # 调用模型的predict方法并传递种子
-#     result = model.predict(prompt=prompt, seed=seed)
-#     return result
+# 定义图像生成函数，添加seed参数
+def generate_image(prompt, seed):
+    # 调用模型的predict方法并传递种子
+    result = model.predict(prompt=prompt, seed=seed)
+    return result
 
-# # 创建Gradio界面
-# with gr.Blocks() as demo:
-#     gr.Markdown("## Stable Diffusion Image Generation with Seed Control")
+# 创建Gradio界面
+with gr.Blocks() as demo:
+    gr.Markdown("## Stable Diffusion Image Generation with Seed Control")
 
-#     # 输入框：提示文本
-#     prompt_input = gr.Textbox(label="Prompt", value="Man in the style of dark beige and brown, uhd image, youthful protagonists, nonrepresentational photography")
+    # 输入框：提示文本
+    prompt_input = gr.Textbox(label="Prompt", value="Man in the style of dark beige and brown, uhd image, youthful protagonists, nonrepresentational photography")
 
-#     # 滑块：种子
-#     seed_input = gr.Slider(minimum=0, maximum=100000, step=1, label="Seed", value=42)
+    # 滑块：种子
+    seed_input = gr.Slider(minimum=0, maximum=100000, step=1, label="Seed", value=42)
 
-#     # 输出图像
-#     output_image = gr.Image(type="pil", label="Generated Image")
+    # 输出图像
+    output_image = gr.Image(type="pil", label="Generated Image")
 
-#     # 按钮触发事件
-#     generate_btn = gr.Button("Generate Image")
-#     generate_btn.click(generate_image, inputs=[prompt_input, seed_input], outputs=output_image)
+    # 按钮触发事件
+    generate_btn = gr.Button("Generate Image")
+    generate_btn.click(generate_image, inputs=[prompt_input, seed_input], outputs=output_image)
 
-# # 启动Gradio应用
-# demo.launch()
+# 启动Gradio应用
+demo.launch()