Add application file

app.py

@@ -0,0 +1,44 @@
+import gradio as gr
+import torch
+import os
+import tempfile
+from PIL import Image
+import time
+temp_dir=tempfile.gettempdir()
+
+def process_images(condition_images, input_images):
+    start = time.time()
+    output_images = []
+    for img in input_images:
+        if img is not None:
+            output_images.append(img)  
+    pth_path = os.path.join(temp_dir, "output.pth")
+    temp_data = {"test": "test"}
+    torch.save(temp_data, pth_path)
+    end=time.time()
+    process_time = f"{end-start:.2f} s"
+    return output_images, pth_path, process_time
+
+with gr.Blocks() as demo:
+        gr.Markdown("Title")
+        with gr.Row():
+            with gr.Group():
+                condition_inputs = gr.Files(label="Condition Img", file_types=[".png", ".jpg", ".jpeg"], type='filepath')
+                input_images = gr.Files(label="Input Img", file_types=[".png", ".jpg", ".jpeg"], type='filepath')
+            with gr.Group():
+                output_gallery = gr.Gallery(label="Output Img", show_label=True, columns=2)
+                pth_output = gr.File(label="下载 PTH 文件")
+                process_time = gr.Textbox(label="处理用时",  type="text",interactive=False)
+        button1 = gr.Button("上传并处理")
+        def func1(condition_files, input_files):
+            condition_imgs = [Image.open(f) for f in condition_files] if condition_files else []
+            input_imgs = [Image.open(f) for f in input_files] if input_files else []
+            return process_images(condition_imgs, input_imgs)
+        
+        button1.click(
+            fn=func1,
+            inputs=[condition_inputs, input_images],
+            outputs=[output_gallery, pth_output, process_time]
+        )
+    
+demo.launch()