Update app.py

app.py

@@ -2,7 +2,6 @@ import cv2
 import numpy as np
 import os
 import gradio as gr
-from tqdm import tqdm
 import gc
 
 # 常量配置
@@ -19,30 +18,26 @@ def overlay_image(bg, fg, x, y):
     bg[y:y+fg.shape[0], x:x+fg.shape[1]] = alpha * fg[:, :, :3] + (1 - alpha) * bg[y:y+fg.shape[0], x:x+fg.shape[1]]
     return bg
 
-
 def process_images(fg_files):
     try:
-    progress = gr.Progress() 
-    progress(0, desc="正在准备...")
-    
-    """处理1~250张前景图（动态数量）"""
-    # 检查上传数量
-    if len(fg_files) > MAX_FILES:
-        raise gr.Error(f"最多上传 {MAX_FILES} 张图片！")
+        progress = gr.Progress() 
+        progress(0, desc="正在准备...")
         
-    num_files = len(fg_files)
-    if num_files > MAX_FILES:
-        raise gr.Error(f"最多支持 {MAX_FILES} 张前景图！")
-    if num_files == 0:
-        return []
-
-    # 读取背景图（仅一次）
-    bg = cv2.imread(BG_PATH)
-    if bg is None:
-        raise gr.Error("请先上传背景图！")
-
-    results = []
-    for i, fg_file in enumerate(fg_files, 1):
+        """处理1~250张前景图（动态数量）"""
+        # 检查上传数量
+        num_files = len(fg_files)
+        if num_files > MAX_FILES:
+            raise gr.Error(f"最多支持 {MAX_FILES} 张前景图！")
+        if num_files == 0:
+            return []
+
+        # 读取背景图（仅一次）
+        bg = cv2.imread(BG_PATH)
+        if bg is None:
+            raise gr.Error("请先上传背景图！")
+
+        results = []
+        for i, fg_file in enumerate(fg_files, 1):
             progress(i/len(fg_files), f"合成中 ({i}/{len(fg_files)})")
             # 读取前景图（自动跳过损坏文件）
             fg = cv2.imread(fg_file.name, cv2.IMREAD_UNCHANGED)
@@ -65,13 +60,12 @@ def process_images(fg_files):
             if i % 10 == 0:
                 gc.collect()
 
-    progress(1, "处理完成！")
-    return results
+        progress(1, "处理完成！")
+        return results
 
     except Exception as e:
         raise gr.Error(f"出错啦: {str(e)}")
 
-
 # Gradio界面
 with gr.Blocks() as demo:
     gr.Markdown("## 🖼️ 灵活图片合成工具 (1~250张)")
@@ -90,7 +84,7 @@ with gr.Blocks() as demo:
 
     # 事件绑定
     bg_upload.upload(
-        lambda f: cv2.imwrite(BG_PATH, cv2.imdecode(np.frombuffer(f.read(), np.uint8)) or "背景图已更新！"),
+        lambda f: cv2.imwrite(BG_PATH, cv2.imdecode(np.frombuffer(f.read(), np.uint8)) or "背景图已更新！",
         inputs=bg_upload,
         outputs=log_output
     )