Update app.py

app.py

@@ -53,49 +53,68 @@ def process_upscale(input_img):
 
 # 4. 动漫化 (使用你上传的 face_paint_512_v2_0.onnx)
 def process_anime(input_img):
-    if input_img is None: return None
+if input_img is None: return None
     
-    # 建议换成 shinkai_512.onnx
+    # 确保文件名匹配
     model_path = "AnimeGANv3_Shinkai_37.onnx" 
     
     try:
         if models["anime_session"] is None:
-            models["anime_session"] = ort.InferenceSession(model_path, providers=['CPUExecutionProvider'])
+            # 这里的加载逻辑保持不变
+            models["anime_session"] = ort.InferenceSession(
+                model_path, 
+                providers=['CPUExecutionProvider']
+            )
 
-        # 1. 保持比例缩放，而不是硬挤压
-        img = input_img.convert("RGB")
-        img.thumbnail((512, 512), Image.LANCZOS)
+        # 1. 获取原图尺寸
+        img_pil = input_img.convert("RGB")
+        w, h = img_pil.size
+        
+        # 2. 动态计算尺寸：保持比例，同时确保是 32 的倍数
+        # 限制最大边长为 1024 避免 CPU 内存崩掉
+        max_side = 1024
+        scale = max_side / max(w, h) if max(w, h) > max_side else 1.0
         
-        # 2. 补齐到 32 的倍数 (或者直接 resize 到 512)
-        img = img.resize((512, 512), Image.LANCZOS)
+        target_w = int((w * scale) // 32) * 32
+        target_h = int((h * scale) // 32) * 32
         
-        # 3. 严格执行 RGB 归一化
-        img_np = np.array(img).astype(np.float32)
-        # 注意：这里必须是 (x / 127.5) - 1.0
+        # 如果缩放后尺寸太小，强制设为 32
+        target_w = max(32, target_w)
+        target_h = max(32, target_h)
+
+        # 3. 预处理
+        img_resized = img_pil.resize((target_w, target_h), Image.LANCZOS)
+        img_np = np.array(img_resized).astype(np.float32)
+        
+        # V3 标准归一化
         img_np = (img_np / 127.5) - 1.0
-        img_np = np.transpose(img_np, (2, 0, 1))
-        img_np = np.expand_dims(img_np, axis=0)
+        img_np = np.transpose(img_np, (2, 0, 1)) # HWC -> CHW
+        img_np = np.expand_dims(img_np, axis=0)  # CHW -> NCHW
 
         # 4. 推理
-        inputs = {models["anime_session"].get_inputs()[0].name: img_np}
-        output = models["anime_session"].run(None, inputs)[0]
+        input_name = models["anime_session"].get_inputs()[0].name
+        output = models["anime_session"].run(None, {input_name: img_np})[0]
 
-        # 5. 后处理逻辑修复
-        output = np.squeeze(output).transpose(1, 2, 0)
-        # 关键：先加 1 再乘 127.5，确保回到 0-255 范围
+        # 5. 后处理
+        output = np.squeeze(output)
+        output = np.transpose(output, (1, 2, 0)) # CHW -> HWC
+        
+        # 恢复到 0-255 范围
         output = (output + 1.0) * 127.5
         output = np.clip(output, 0, 255).astype(np.uint8)
         
-        return Image.fromarray(output)
+        # 6. 关键：将结果 Resize 回用户上传的原始比例，解决“拉伸感”
+        result_pil = Image.fromarray(output)
+        return result_pil.resize((w, h), Image.LANCZOS)
 
     except Exception as e:
-        print(f"Error: {e}")
-        return input_img
+        print(f"V3 推理出错: {e}")
+        return input_img # 出错则返回原图，不让 UI 裂开
 
 # --- Gradio 界面设计 ---
 with gr.Blocks(theme=gr.themes.Default()) as demo:
     gr.Markdown("# 🎨 全能 AI 图像处理 API 站")
-    gr.Markdown("当前动漫化模型：`face_paint_512_v2_0.onnx` (AnimeGANv2)")
+    gr.Markdown("当前动漫化模型：`AnimeGANv3_Shinkai_37.onnx` (AnimeGANv3)")
     
     with gr.Tabs():
         with gr.TabItem("🖼️ 抠图 (RMBG)"):