Update app.py

app.py

@@ -90,21 +90,21 @@ def download_file2folder(url: str, folder: str, filesize_max: int, filesize_min:
         return None
 
 async def _process_model(model_input: Union[str, gr.File], tilesize: int, output_dir: str,task_id:int,fp16:bool):
-    log = ('初始化日志记录...')
+    log = ('初始化日志记录...\n')
     print_log(task_id, '初始化日志记录', '开始')
     yield [],[], log
 
     if isinstance(model_input, str):
         input_path = model_input
-        log += f'使用文件: {input_path}'
+        log += f'使用文件: {input_path}\n'
     else:
         input_path = model_input.name
-        log += f'已上传文件: {input_path}'
+        log += f'已上传文件: {input_path}\n'
     print_log(task_id, log.split('\n')[-1], '开始')
     yield [], [], log
 
     if not input_path:
-        log += ( f'未获得正确的模型文件')
+        log += ( f'未获得正确的模型文件\n')
         print_log(task_id, f'未获得正确的模型文件', '错误')
         yield  [],[], log
         return
@@ -112,17 +112,17 @@ async def _process_model(model_input: Union[str, gr.File], tilesize: int, output
 
     if input_path.endswith('.onnx'):
         onnx_path = input_path
-        log += ( '输入已是 ONNX 模型，直接使用...')
-        print_log(task_id, '输入已是 ONNX 模型，直接使用', '开始')
+        log += ( '输入已经是 ONNX 文件\n')
+        print_log(task_id, '输入已经是 ONNX 文件', '跳过')
         yield [],[], log
     else:
         print_log(task_id, f'转换 PTH 模型为 ONNX, folder={output_dir}', '开始')
         onnx_path = convert_pth_to_onnx(input_path, tilesize=tilesize, output_folder=output_dir,use_fp16=fp16)
         if onnx_path:
-            log += ( f'成功生成ONNX模型: {onnx_path}')
+            log += ( f'成功生成ONNX模型: {onnx_path}\n')
             print_log(task_id, f'生成ONNX模型: {onnx_path}', '完成')
         else:
-            log += ( '生成ONNX模型失败')
+            log += ( '生成ONNX模型失败\n')
             print_log(task_id, '生成ONNX模型', '错误')
             yield [], [], log
             return
@@ -132,12 +132,12 @@ async def _process_model(model_input: Union[str, gr.File], tilesize: int, output
     output_name= os.path.splitext(os.path.basename(onnx_path))[0]
     mnn_path = os.path.join(output_dir,  f'{output_name}.mnn')
     try:
-        log += ( '正在将 ONNX 模型转换为 MNN 格式...')
+        log += ( '正在将 ONNX 模型转换为 MNN 格式...\n')
         print_log(task_id, '正在将 ONNX 模型转换为 MNN 格式', '开始')
         convertmnn(onnx_path, mnn_path,fp16)
         yield onnx_path,[], log
     except Exception as e:
-        log += ( f'转换 MNN 模型时出错: {str(e)}')
+        log += ( f'转换 MNN 模型时出错: {str(e)}\n')
         print_log(task_id, f'转换 MNN 模型时出错: {str(e)}', '错误')
         yield onnx_path,[], log
 
@@ -145,9 +145,9 @@ async def _process_model(model_input: Union[str, gr.File], tilesize: int, output
     
     # 转换为 MNN 模型后对文件检查
     if os.path.exists(mnn_path) and os.path.getsize(mnn_path) > 1024:  # 1KB = 1024 bytes
-        log += ( f'MNN 模型已保存到: {mnn_path}')
+        log += ( f'MNN 模型已保存到: {mnn_path}\n')
     else:
-        log += ( 'MNN 模型生成失败或文件大小不足1KB')
+        log += ( 'MNN 模型生成失败或文件大小不足1KB\n')
         mnn_path = None
     
     yield onnx_path, mnn_path, log
@@ -160,7 +160,6 @@ with gr.Blocks() as demo:
             url_input = gr.Textbox(label='模型链接')
             file_input = gr.File(label='上传模型文件', visible=False)
 
-            
             def show_input(input_type):
                 if input_type == '模型链接':
                     return gr.update(visible=True), gr.update(visible=False)
@@ -185,10 +184,11 @@ with gr.Blocks() as demo:
         task_counter += 1
         output_dir = os.path.join(os.getcwd(), f"output_{task_counter}")
         os.makedirs(output_dir, exist_ok=True)
+        log=""
 
         if input_type == '模型链接' and url_input:
             # 新增：下载模型文件到 output_dir
-            log = f'正在下载模型文件: {url_input}'
+            log = f'正在下载模型文件: {url_input}\n'
             print_log(task_counter, f'正在下载模型文件: {url_input}', '开始')
             yield None, None, log
         
@@ -199,7 +199,7 @@ with gr.Blocks() as demo:
                 filesize_min=1024     # 1KB
             )
             model_input = os.path.join(output_dir, filename)
-            log += f'\n模型文件已下载到: {model_input}'
+            log += f'\n模型文件已下载到: {model_input}\n'
             print_log(task_counter, f'模型文件已下载到: {model_input}', '完成')
             yield None, None, log
         elif input_type == '上传模型文件' and file_input:
@@ -216,12 +216,13 @@ with gr.Blocks() as demo:
         # 调用重命名后的函数
         async for result in _process_model(model_input, int(tilesize), output_dir, task_counter, fp16):
             if isinstance(result, tuple) and len(result) == 3:
-                onnx_path, mnn_path, log_box = result
+                onnx_path, mnn_path, process_log = result
+                yield onnx_path, mnn_path, log+process_log
             elif isinstance(result, tuple) and len(result) == 2:
                 # 处理纯日志yield
                 _, process_log = result
-                yield None, None, process_log
-            yield onnx_path, mnn_path, log_box
+                yield None, None, log+process_log
+            # yield onnx_path, mnn_path, log+process_log
 
     convert_btn.click(
         process_model,