Upload app.py

app.py

@@ -4,8 +4,6 @@ import numpy as np
 import torch
 from PIL import Image
 import gradio as gr
-from gradio_imageslider import ImageSlider
-
 
 # 延迟 CUDA 初始化
 weight_dtype = torch.float32
@@ -59,7 +57,7 @@ def process_image(input_image):
     processed_frame = (processed_frame[0] * 255).astype(np.uint8)
     processed_frame = Image.fromarray(processed_frame)
 
-    return input_image, processed_frame
+    return processed_frame
 
 # 创建 Gradio 界面
 def create_gradio_interface():
@@ -75,20 +73,13 @@ def create_gradio_interface():
                 input_image = gr.Image(label="Input Image", type="numpy")
                 submit_btn = gr.Button("Remove Reflection", variant="primary")
             with gr.Column():
-                image_output_slider = ImageSlider(
-                    label="outputs",
-                    type="filepath",
-                    show_download_button=True,
-                    show_share_button=True,
-                    interactive=False,
-                    elem_classes="slider",
-                )
+                output_image = gr.Image(label="Processed Image")
 
         # 添加示例
         gr.Examples(
             examples=example_images,
             inputs=input_image,
-            outputs=image_output_slider,
+            outputs=output_image,
             fn=process_image,
             cache_examples=False,  # 缓存结果以加快加载速度
             label="Example Images",
@@ -98,7 +89,7 @@ def create_gradio_interface():
         submit_btn.click(
             fn=process_image,
             inputs=input_image,
-            outputs=image_output_slider,
+            outputs=output_image,
         )
 
     return demo