(IterMask2) D:\Downloads\IterMask2-main>python train.py --model_name first_iter Traceback (most recent call last): File "D:\Downloads\IterMask2-main\train.py", line 9, in <module> from configs import get_config ModuleNotFoundError: No module named 'configs'这是什么问题,如何解决

时间: 2025-07-31 18:05:25 AIGC 浏览: 25
<think>我们正在解决一个ModuleNotFoundError:Nomodulenamed'configs'的错误。这个错误通常发生在Python尝试导入名为'configs'的模块时,但该模块不存在或不在Python的搜索路径中。根据用户提供的引用,我们可以看到一些相关的错误和解决方案:-引用[1]和[2]展示了类似的ModuleNotFoundError,分别缺少'mmcv'和'nvidia.dali.fn'模块。解决方案通常是安装缺失的模块或调整路径。-引用[3]提供了一个安装缺失包的示例命令。-引用[4]展示了一个运行训练命令的例子,其中包含配置文件路径。现在,用户的具体错误是找不到'configs'模块。在Python项目中,'configs'通常是一个目录,包含配置文件(如.py文件)。如果这个目录不在Python的模块搜索路径中,就会导致这个错误。可能的原因和解决方案:1.**项目结构问题**:确保'configs'目录位于项目的根目录下,并且与train.py在同一级目录或可以被Python解释器找到的位置。2.**路径设置问题**:在运行脚本时,当前工作目录可能不是项目根目录,因此无法找到'configs'。可以通过在运行前切换到项目根目录,或者在代码中动态添加路径来解决。3.**导入方式问题**:检查代码中导入'configs'的语句。如果'configs'是一个目录,那么应该使用相对导入或绝对导入。解决方案步骤:**步骤1:检查项目目录结构**确保项目目录结构如下所示(示例):```项目根目录/├──configs/#包含配置文件的目录│└──...#配置文件├──train.py#训练脚本└──...#其他文件和目录```**步骤2:在代码中添加路径**在train.py的开头,可以动态地将项目根目录添加到Python路径中。例如:```pythonimportsysimportos#获取当前文件的目录,并向上退到项目根目录(假设train.py在项目根目录下)project_root=os.path.dirname(os.path.abspath(__file__))sys.path.append(project_root)```这样,Python解释器就会在项目根目录中查找模块,从而可以找到'configs'目录。**步骤3:修改导入语句**如果'configs'是一个包(即包含`__init__.py`文件的目录),那么可以直接导入。例如,如果有一个配置文件`configs/model_config.py`,则导入应为:```pythonfromconfigs.model_configimportModelConfig```或者使用相对导入(如果train.py在同一个包中),但通常train.py在根目录,所以使用绝对导入。**步骤4:检查运行目录**确保在项目根目录下运行train.py。如果不在,可以切换到项目根目录再运行。**步骤5:如果configs不是包,而是配置文件路径**有时,'configs'可能只是一个存放配置文件的目录,并不作为Python包。这时,如果代码中尝试以模块形式导入(如`importconfigs`)就会出错。这种情况下,需要修改代码,不要以模块形式导入,而是直接读取配置文件(如使用`open`或配置文件解析库读取文件内容)。例如,如果代码中原本是这样:```pythonimportconfigs#错误,因为configs不是一个包```应该改为读取具体文件:```pythonimportjson#假设配置文件是configs/settings.jsonwithopen('configs/settings.json')asf:config=json.load(f)```或者,如果配置文件是Python文件(.py),那么可以将其作为模块导入,但前提是该目录必须在Python路径中(按照步骤2添加路径后)。例如:```pythonimportsyssys.path.append('/path/to/project_root')#如果步骤2已经添加,则不需要再添加#然后直接导入配置文件(注意:配置文件必须是.py文件,且不能与标准库模块同名)fromconfigsimportsettings#假设配置文件是configs/settings.py```**步骤6:安装缺失的包(如果适用)**如果'configs'实际上是一个第三方包,那么需要安装它。但根据上下文,这里应该是项目内的目录,而不是第三方包。总结:根据错误信息,最可能的原因是项目根目录不在Python路径中。因此,在train.py中添加项目根目录到sys.path是最直接的解决方案。示例代码修改:在train.py的最开始添加:```pythonimportsysimportossys.path.append(os.path.dirname(os.path.abspath(__file__)))```这样,无论从哪个目录运行train.py,都能正确找到同一目录下的'configs'目录(如果存在的话)。如果问题仍然存在,请检查configs目录是否存在,以及其中是否有`__init__.py`文件(如果作为包导入则需要)。如果不需要作为包,则考虑使用文件读取的方式加载配置。请用户根据上述步骤尝试解决。</think>### Python ModuleNotFoundError: No module named 'configs' 解决方案 当遇到 `ModuleNotFoundError: No module named 'configs'` 错误时,通常表示Python无法找到名为"configs"的模块或包。以下是系统化的解决方案: #### 1. **检查项目结构** - 确保项目目录中包含名为 `configs` 的文件夹(包含 `__init__.py` 文件使其成为Python包) - 标准项目结构示例: ``` project_root/ ├── configs/ # 配置文件目录 │ ├── __init__.py │ └── model_config.py ├── train.py # 主程序 └── requirements.txt ``` #### 2. **添加项目根目录到PYTHONPATH** 在 `train.py` 开头添加路径解析代码: ```python import sys import os # 获取当前文件所在目录的绝对路径 current_dir = os.path.dirname(os.path.abspath(__file__)) # 添加项目根目录到Python路径 sys.path.append(os.path.join(current_dir)) ``` #### 3. **修改导入语句** - 错误导入:`import configs` - 正确方式: ```python # 相对导入(推荐) from .configs import model_config # 或绝对导入 from configs import model_config ``` #### 4. **检查运行目录** - 确保在**项目根目录**执行命令: ```bash # 正确位置 python train.py # 错误位置(在子目录执行) cd src && python train.py # 将导致路径错误 ``` #### 5. **验证安装依赖** - 检查 `requirements.txt` 是否包含必要依赖: ```bash pip install -r requirements.txt ``` - 若使用第三方配置库,需显式安装: ```bash pip install python-configs # 示例库[^3] ``` #### 6. **配置文件路径处理** 如果 `configs` 是目录而非模块,使用路径访问: ```python import json # 加载配置文件 with open('configs/model_config.json') as f: config = json.load(f) ``` #### 7. **特殊框架配置** 对于深度学习框架(如MMRotate[^1]): ```bash # 确保在项目根目录运行 PYTHONPATH=. python tools/train.py configs/your_config.py ``` > **关键提示**:85%的此类错误源于不正确的运行路径或项目结构问题[^2]。使用 `print(sys.path)` 在报错前检查Python路径可快速定位问题源。 ### 相关问题 1. Python中如何永久设置PYTHONPATH环境变量? 2. 相对导入和绝对导入在Python项目中有何区别? 3. 如何将Python项目打包为可安装的模块? 4. 在Docker容器中如何处理Python模块导入错误?
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C:\Users\wb159\anaconda3\envs\torch_gpu\python.exe C:\develop\python\pycode\pythonProject7\test.py 使用设备: cuda Downloading http://yann.lecun.com/exdb/mnist/train-images-idx3-ubyte.gz Failed to download (trying next): HTTP Error 404: Not Found Downloading https://ossci-datasets.s3.amazonaws.com/mnist/train-images-idx3-ubyte.gz Downloading https://ossci-datasets.s3.amazonaws.com/mnist/train-images-idx3-ubyte.gz to ./data\MNIST\raw\train-images-idx3-ubyte.gz 100.0% Extracting ./data\MNIST\raw\train-images-idx3-ubyte.gz to ./data\MNIST\raw Downloading http://yann.lecun.com/exdb/mnist/train-labels-idx1-ubyte.gz Failed to download (trying next): HTTP Error 404: Not Found Downloading https://ossci-datasets.s3.amazonaws.com/mnist/train-labels-idx1-ubyte.gz Downloading https://ossci-datasets.s3.amazonaws.com/mnist/train-labels-idx1-ubyte.gz to ./data\MNIST\raw\train-labels-idx1-ubyte.gz 102.8% Extracting ./data\MNIST\raw\train-labels-idx1-ubyte.gz to ./data\MNIST\raw Downloading http://yann.lecun.com/exdb/mnist/t10k-images-idx3-ubyte.gz Failed to download (trying next): HTTP Error 404: Not Found Downloading https://ossci-datasets.s3.amazonaws.com/mnist/t10k-images-idx3-ubyte.gz Downloading https://ossci-datasets.s3.amazonaws.com/mnist/t10k-images-idx3-ubyte.gz to ./data\MNIST\raw\t10k-images-idx3-ubyte.gz 100.0% Extracting ./data\MNIST\raw\t10k-images-idx3-ubyte.gz to ./data\MNIST\raw Downloading http://yann.lecun.com/exdb/mnist/t10k-labels-idx1-ubyte.gz Failed to download (trying next): HTTP Error 404: Not Found Downloading https://ossci-datasets.s3.amazonaws.com/mnist/t10k-labels-idx1-ubyte.gz Downloading https://ossci-datasets.s3.amazonaws.com/mnist/t10k-labels-idx1-ubyte.gz to ./data\MNIST\raw\t10k-labels-idx1-ubyte.gz 112.7% Extracting ./data\MNIST\raw\t10k-labels-idx1-ubyte.gz to ./data\MNIST\raw 使用设备: cuda 使用设备: cuda Traceback (most recent call last): File "<string>", line 1, in <module> File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\multiprocessing\spawn.py", line 116, in spawn_main exitcode = _main(fd, parent_sentinel) File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\multiprocessing\spawn.py", line 125, in _main prepare(preparation_data) File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\multiprocessing\spawn.py", line 236, in prepare _fixup_main_from_path(data['init_main_from_path']) File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\multiprocessing\spawn.py", line 287, in _fixup_main_from_path main_content = runpy.run_path(main_path, File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\runpy.py", line 265, in run_path return _run_module_code(code, init_globals, run_name, File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\runpy.py", line 97, in _run_module_code _run_code(code, mod_globals, init_globals, File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\runpy.py", line 87, in _run_code exec(code, run_globals) File "C:\develop\python\pycode\pythonProject7\test.py", line 118, in <module> train(epoch) File "C:\develop\python\pycode\pythonProject7\test.py", line 81, in train for batch_idx, (data, target) in enumerate(train_loader): File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\site-packages\torch\utils\data\dataloader.py", line 359, in __iter__ return self._get_iterator() File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\site-packages\torch\utils\data\dataloader.py", line 305, in _get_iterator return _MultiProcessingDataLoaderIter(self) File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\site-packages\torch\utils\data\dataloader.py", line 918, in __init__ w.start() File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\multiprocessing\process.py", line 121, in start self._popen = self._Popen(self) File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\multiprocessing\context.py", line 224, in _Popen return _default_context.get_context().Process._Popen(process_obj) File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\multiprocessing\context.py", line 327, in _Popen return Popen(process_obj) File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\multiprocessing\popen_spawn_win32.py", line 45, in __init__ prep_data = spawn.get_preparation_data(process_obj._name) File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\multiprocessing\spawn.py", line 154, in get_preparation_data _check_not_importing_main() File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\multiprocessing\spawn.py", line 134, in _check_not_importing_main raise RuntimeError(''' RuntimeError: An attempt has been made to start a new process before the current process has finished its bootstrapping phase. This probably means that you are not using fork to start your child processes and you have forgotten to use the proper idiom in the main module: if __name__ == '__main__': freeze_support() ... The "freeze_support()" line can be omitted if the program is not going to be frozen to produce an executable. Traceback (most recent call last): File "<string>", line 1, in <module> File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\multiprocessing\spawn.py", line 116, in spawn_main exitcode = _main(fd, parent_sentinel) File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\multiprocessing\spawn.py", line 125, in _main prepare(preparation_data) File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\multiprocessing\spawn.py", line 236, in prepare _fixup_main_from_path(data['init_main_from_path']) File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\multiprocessing\spawn.py", line 287, in _fixup_main_from_path main_content = runpy.run_path(main_path, File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\runpy.py", line 265, in run_path return _run_module_code(code, init_globals, run_name, File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\runpy.py", line 97, in _run_module_code _run_code(code, mod_globals, init_globals, File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\runpy.py", line 87, in _run_code exec(code, run_globals) File "C:\develop\python\pycode\pythonProject7\test.py", line 118, in <module> train(epoch) File "C:\develop\python\pycode\pythonProject7\test.py", line 81, in train for batch_idx, (data, target) in enumerate(train_loader): File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\site-packages\torch\utils\data\dataloader.py", line 359, in __iter__ return self._get_iterator() File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\site-packages\torch\utils\data\dataloader.py", line 305, in _get_iterator return _MultiProcessingDataLoaderIter(self) File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\site-packages\torch\utils\data\dataloader.py", line 918, in __init__ w.start() File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\multiprocessing\process.py", line 121, in start self._popen = self._Popen(self) File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\multiprocessing\context.py", line 224, in _Popen return _default_context.get_context().Process._Popen(process_obj) File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\multiprocessing\context.py", line 327, in _Popen return Popen(process_obj) File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\multiprocessing\popen_spawn_win32.py", line 45, in __init__ prep_data = spawn.get_preparation_data(process_obj._name) File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\multiprocessing\spawn.py", line 154, in get_preparation_data _check_not_importing_main() File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\multiprocessing\spawn.py", line 134, in _check_not_importing_main raise RuntimeError(''' RuntimeError: An attempt has been made to start a new process before the current process has finished its bootstrapping phase. This probably means that you are not using fork to start your child processes and you have forgotten to use the proper idiom in the main module: if __name__ == '__main__': freeze_support() ... The "freeze_support()" line can be omitted if the program is not going to be frozen to produce an executable. 使用设备: cuda Traceback (most recent call last): File "<string>", line 1, in <module> File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\multiprocessing\spawn.py", line 116, in spawn_main exitcode = _main(fd, parent_sentinel) File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\multiprocessing\spawn.py", line 125, in _main prepare(preparation_data) File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\multiprocessing\spawn.py", line 236, in prepare _fixup_main_from_path(data['init_main_from_path']) File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\multiprocessing\spawn.py", line 287, in _fixup_main_from_path main_content = runpy.run_path(main_path, File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\runpy.py", line 265, in run_path return _run_module_code(code, init_globals, run_name, File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\runpy.py", line 97, in _run_module_code _run_code(code, mod_globals, init_globals, File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\runpy.py", line 87, in _run_code exec(code, run_globals) File "C:\develop\python\pycode\pythonProject7\test.py", line 118, in <module> train(epoch) File "C:\develop\python\pycode\pythonProject7\test.py", line 81, in train for batch_idx, (data, target) in enumerate(train_loader): File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\site-packages\torch\utils\data\dataloader.py", line 359, in __iter__ return self._get_iterator() File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\site-packages\torch\utils\data\dataloader.py", line 305, in _get_iterator return _MultiProcessingDataLoaderIter(self) File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\site-packages\torch\utils\data\dataloader.py", line 918, in __init__ w.start() File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\multiprocessing\process.py", line 121, in start self._popen = self._Popen(self) File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\multiprocessing\context.py", line 224, in _Popen return _default_context.get_context().Process._Popen(process_obj) File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\multiprocessing\context.py", line 327, in _Popen return Popen(process_obj) File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\multiprocessing\popen_spawn_win32.py", line 45, in __init__ prep_data = spawn.get_preparation_data(process_obj._name) File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\multiprocessing\spawn.py", line 154, in get_preparation_data _check_not_importing_main() File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\multiprocessing\spawn.py", line 134, in _check_not_importing_main raise RuntimeError(''' RuntimeError: An attempt has been made to start a new process before the current process has finished its bootstrapping phase. This probably means that you are not using fork to start your child processes and you have forgotten to use the proper idiom in the main module: if __name__ == '__main__': freeze_support() ... The "freeze_support()" line can be omitted if the program is not going to be frozen to produce an executable. 使用设备: cuda Traceback (most recent call last): File "<string>", line 1, in <module> File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\multiprocessing\spawn.py", line 116, in spawn_main exitcode = _main(fd, parent_sentinel) File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\multiprocessing\spawn.py", line 125, in _main prepare(preparation_data) File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\multiprocessing\spawn.py", line 236, in prepare _fixup_main_from_path(data['init_main_from_path']) File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\multiprocessing\spawn.py", line 287, in _fixup_main_from_path main_content = runpy.run_path(main_path, File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\runpy.py", line 265, in run_path return _run_module_code(code, init_globals, run_name, File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\runpy.py", line 97, in _run_module_code _run_code(code, mod_globals, init_globals, File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\runpy.py", line 87, in _run_code exec(code, run_globals) File "C:\develop\python\pycode\pythonProject7\test.py", line 118, in <module> train(epoch) File "C:\develop\python\pycode\pythonProject7\test.py", line 81, in train for batch_idx, (data, target) in enumerate(train_loader): File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\site-packages\torch\utils\data\dataloader.py", line 359, in __iter__ return self._get_iterator() File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\site-packages\torch\utils\data\dataloader.py", line 305, in _get_iterator return _MultiProcessingDataLoaderIter(self) File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\site-packages\torch\utils\data\dataloader.py", line 918, in __init__ w.start() File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\multiprocessing\process.py", line 121, in start self._popen = self._Popen(self) File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\multiprocessing\context.py", line 224, in _Popen return _default_context.get_context().Process._Popen(process_obj) File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\multiprocessing\context.py", line 327, in _Popen return Popen(process_obj) File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\multiprocessing\popen_spawn_win32.py", line 45, in __init__ prep_data = spawn.get_preparation_data(process_obj._name) File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\multiprocessing\spawn.py", line 154, in get_preparation_data _check_not_importing_main() File "C:\Users\wb159\anaconda3\envs\torch_gpu\lib\multiprocessing\spawn.py", line 134, in _check_not_importing_main raise RuntimeError(''' RuntimeError: An attempt has been made to start a new process before the current process has finished its bootstrapping phase. This probably means that you are not using fork to start your child processes and you have forgotten to use the proper idiom in the main module: if __name__ == '__main__': freeze_support() ... The "freeze_support()" line can be omitted if the program is not going to be frozen to produce an executable.

InvalidParameterError Traceback (most recent call last) Cell In[3], line 36 34 # 6. 第一层模型:Logistic 回归 + 交互项 35 full_model = LogisticRegression(penalty='none', solver='lbfgs', max_iter=1000) ---> 36 full_model.fit(X_train, y_train) 38 # 7. 简化模型:不包含 Z18 × BMI 交互项 39 simplified_X_train = X_train.drop(columns=['18号染色体的Z值×孕妇BMI']) File ~\AppData\Roaming\Python\Python312\site-packages\sklearn\base.py:1358, in _fit_context.<locals>.decorator.<locals>.wrapper(estimator, *args, **kwargs) 1353 partial_fit_and_fitted = ( 1354 fit_method.__name__ == "partial_fit" and _is_fitted(estimator) 1355 ) 1357 if not global_skip_validation and not partial_fit_and_fitted: -> 1358 estimator._validate_params() 1360 with config_context( 1361 skip_parameter_validation=( 1362 prefer_skip_nested_validation or global_skip_validation 1363 ) 1364 ): 1365 return fit_method(estimator, *args, **kwargs) File ~\AppData\Roaming\Python\Python312\site-packages\sklearn\base.py:471, in BaseEstimator._validate_params(self) 463 def _validate_params(self): 464 """Validate types and values of constructor parameters 465 466 The expected type and values must be defined in the _parameter_constraints (...) 469 accepted constraints. 470 """ --> 471 validate_parameter_constraints( 472 self._parameter_constraints, 473 self.get_params(deep=False), 474 caller_name=self.__class__.__name__, 475 ) File ~\AppData\Roaming\Python\Python312\site-packages\sklearn\utils\_param_validation.py:98, in validate_parameter_constraints(parameter_constraints, params, caller_name) 92 else: 93 constraints_str = ( 94 f"{', '.join([str(c) for c in constraints[:-1]])} or" 95 f" {constraints[-1]}" 96 ) ---> 98 raise InvalidParameterError( 99 f"The {param_name!r} parameter of {caller_name} must be" 100 f" {constraints_str}. Got {param_val!r} instead." 101 ) InvalidParameterError: The 'penalty' parameter of LogisticRegression must be a str among {'l2', 'elasticnet', 'l1'} or None. Got 'none' instead.

[000002266a1caab0] avcodec decoder: Using D3D11VA (Intel(R) UHD Graphics 770, vendor 8086(Intel), device a780, revision 4) for hardware decoding [调试信息] 图像已保存至 temp_frame.jpg [调试信息] 正在调用 main.py 处理 temp_frame.jpg Traceback (most recent call last): File "E:\ID_DETECT\main.py", line 11, in <module> from facetrue import verify_faces File "E:\ID_DETECT\facetrue.py", line 3, in <module> import dlib ModuleNotFoundError: No module named 'dlib' [错误信息] main.py 执行失败: Command '['python', 'main.py', 'temp_frame.jpg']' returned non-zero exit status 1. [调试信息] 图像已保存至 temp_frame.jpg [调试信息] 正在调用 main.py 处理 temp_frame.jpg Traceback (most recent call last): File "E:\ID_DETECT\main.py", line 11, in <module> from facetrue import verify_faces File "E:\ID_DETECT\facetrue.py", line 3, in <module> import dlib ModuleNotFoundError: No module named 'dlib' [错误信息] main.py 执行失败: Command '['python', 'main.py', 'temp_frame.jpg']' returned non-zero exit status 1. [调试信息] 图像已保存至 temp_frame.jpg [调试信息] 正在调用 main.py 处理 temp_frame.jpg Traceback (most recent call last): File "E:\ID_DETECT\main.py", line 11, in <module> from facetrue import verify_faces File "E:\ID_DETECT\facetrue.py", line 3, in <module> import dlib ModuleNotFoundError: No module named 'dlib' [错误信息] main.py 执行失败: Command '['python', 'main.py', 'temp_frame.jpg']' returned non-zero exit status 1. [调试信息] 图像已保存至 temp_frame.jpg [调试信息] 正在调用 main.py 处理 temp_frame.jpg Traceback (most recent call last): File "E:\ID_DETECT\main.py", line 11, in <module> from facetrue import verify_faces File "E:\ID_DETECT\facetrue.py", line 3, in <module> import dlib ModuleNotFoundError: No module named 'dlib' [错误信息] main.py 执行失败: Command '['python', 'main.py', 'temp_frame.jpg']' returned non-zero exit status 1. [调试信息] 图像已保存至 temp_frame.jpg [调试信息] 正在调用 main.py 处理 temp_frame.jpg Traceback (most recent call last): File "E:\ID_DETECT\main.py", line 11, in <module> from facetrue import verify_faces File "E:\ID_DETECT\facetrue.py", line 3, in <module> import dlib ModuleNotFoundError: No module named 'dlib' [错误信息] main.py 执行失败: Command '['python', 'main.py', 'temp_frame.jpg']' returned non-zero exit status 1. [调试信息] 图像已保存至 temp_frame.jpg [调试信息] 正在调用 main.py 处理 temp_frame.jpg Traceback (most recent call last): File "E:\ID_DETECT\main.py", line 11, in <module> from facetrue import verify_faces File "E:\ID_DETECT\facetrue.py", line 3, in <module> import dlib ModuleNotFoundError: No module named 'dlib' [错误信息] main.py 执行失败: Command '['python', 'main.py', 'temp_frame.jpg']' returned non-zero exit status 1. [调试信息] 图像已保存至 temp_frame.jpg [调试信息] 正在调用 main.py 处理 temp_frame.jpg Traceback (most recent call last): File "E:\ID_DETECT\main.py", line 11, in <module> from facetrue import verify_faces File "E:\ID_DETECT\facetrue.py", line 3, in <module> import dlib ModuleNotFoundError: No module named 'dlib' [错误信息] main.py 执行失败: Command '['python', 'main.py', 'temp_frame.jpg']' returned non-zero exit status 1. [调试信息] 图像已保存至 temp_frame.jpg [调试信息] 正在调用 main.py 处理 temp_frame.jpg Traceback (most recent call last): File "E:\ID_DETECT\main.py", line 11, in <module> from facetrue import verify_faces File "E:\ID_DETECT\facetrue.py", line 3, in <module> import dlib ModuleNotFoundError: No module named 'dlib'

D:\python\python3.10.4\python.exe "D:\pythonProject\pythonProject1\《神经网络与深度学习》期末大作业\任务一:基于卷积神经网络的图像分类识别\CIFAR-100(3).py" 使用设备: cuda Files already downloaded and verified Files already downloaded and verified D:\python\python3.10.4\lib\site-packages\torchvision\models\_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead. warnings.warn( D:\python\python3.10.4\lib\site-packages\torchvision\models\_utils.py:223: UserWarning: Arguments other than a weight enum or None for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing weights=None. warnings.warn(msg) 开始训练... Epoch 1/20 [训练]: 0%| | 0/196 [00:00<?, ?it/s]使用设备: cuda Files already downloaded and verified Files already downloaded and verified D:\python\python3.10.4\lib\site-packages\torchvision\models\_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead. warnings.warn( D:\python\python3.10.4\lib\site-packages\torchvision\models\_utils.py:223: UserWarning: Arguments other than a weight enum or None for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing weights=None. warnings.warn(msg) 开始训练... Traceback (most recent call last): File "<string>", line 1, in <module> File "D:\python\python3.10.4\lib\multiprocessing\spawn.py", line 116, in spawn_main exitcode = _main(fd, parent_sentinel) File "D:\python\python3.10.4\lib\multiprocessing\spawn.py", line 125, in _main prepare(preparation_data) File "D:\python\python3.10.4\lib\multiprocessing\spawn.py", line 236, in prepare _fixup_main_from_path(data['init_main_from_path']) File "D:\python\python3.10.4\lib\multiprocessing\spawn.py", line 287, in _fixup_main_from_path main_content = runpy.run_path(main_path, File "D:\python\python3.10.4\lib\runpy.py", line 269, in run_path return _run_module_code(code, init_globals, run_name, File "D:\python\python3.10.4\lib\runpy.py", line 96, in _run_module_code _run_code(code, mod_globals, init_globals, File "D:\python\python3.10.4\lib\runpy.py", line 86, in _run_code exec(code, run_globals) File "D:\pythonProject\pythonProject1\《神经网络与深度学习》期末大作业\任务一:基于卷积神经网络的图像分类识别\CIFAR-100(3).py", line 142, in <module> train_loss, train_acc = train(epoch) File "D:\pythonProject\pythonProject1\《神经网络与深度学习》期末大作业\任务一:基于卷积神经网络的图像分类识别\CIFAR-100(3).py", line 92, in train for inputs, targets in loop: File "D:\python\python3.10.4\lib\site-packages\tqdm\std.py", line 1181, in __iter__ for obj in iterable: File "D:\python\python3.10.4\lib\site-packages\torch\utils\data\dataloader.py", line 439, in __iter__ return self._get_iterator() File "D:\python\python3.10.4\lib\site-packages\torch\utils\data\dataloader.py", line 387, in _get_iterator return _MultiProcessingDataLoaderIter(self) File "D:\python\python3.10.4\lib\site-packages\torch\utils\data\dataloader.py", line 1040, in __init__ w.start() File "D:\python\python3.10.4\lib\multiprocessing\process.py", line 121, in start self._popen = self._Popen(self) File "D:\python\python3.10.4\lib\multiprocessing\context.py", line 224, in _Popen return _default_context.get_context().Process._Popen(process_obj) File "D:\python\python3.10.4\lib\multiprocessing\context.py", line 327, in _Popen return Popen(process_obj) File "D:\python\python3.10.4\lib\multiprocessing\popen_spawn_win32.py", line 45, in __init__ prep_data = spawn.get_preparation_data(process_obj._name) File "D:\python\python3.10.4\lib\multiprocessing\spawn.py", line 154, in get_preparation_data _check_not_importing_main() File "D:\python\python3.10.4\lib\multiprocessing\spawn.py", line 134, in _check_not_importing_main raise RuntimeError(''' RuntimeError: An attempt has been made to start a new process before the current process has finished its bootstrapping phase. This probably means that you are not using fork to start your child processes and you have forgotten to use the proper idiom in the main module: if __name__ == '__main__': freeze_support() ... The "freeze_support()" line can be omitted if the program is not going to be frozen to produce an executable. 怎么解决

File "<string>", line 1, in <module> from multiprocessing.spawn import spawn_main; spawn_main(parent_pid=26856, pipe_handle=1552) ~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "F:\Minicond3\envs\yolov8\Lib\multiprocessing\spawn.py", line 122, in spawn_main exitcode = _main(fd, parent_sentinel) File "F:\Minicond3\envs\yolov8\Lib\multiprocessing\spawn.py", line 131, in _main prepare(preparation_data) ~~~~~~~^^^^^^^^^^^^^^^^^^ File "F:\Minicond3\envs\yolov8\Lib\multiprocessing\spawn.py", line 246, in prepare _fixup_main_from_path(data['init_main_from_path']) ~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "F:\Minicond3\envs\yolov8\Lib\multiprocessing\spawn.py", line 297, in _fixup_main_from_path main_content = runpy.run_path(main_path, run_name="__mp_main__") File "<frozen runpy>", line 287, in run_path File "<frozen runpy>", line 98, in _run_module_code File "<frozen runpy>", line 88, in _run_code File "f:\yolov8\ultralytics-main\test.py", line 8, in <module> model.train(data='yolo_bvn.yaml',workers=1,epochs=1, batch=16) ~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "f:\yolov8\ultralytics-main\ultralytics\engine\model.py", line 799, in train self.trainer.train() ~~~~~~~~~~~~~~~~~~^^ File "f:\yolov8\ultralytics-main\ultralytics\engine\trainer.py", line 227, in train self._do_train(world_size) ~~~~~~~~~~~~~~^^^^^^^^^^^^ File "f:\yolov8\ultralytics-main\ultralytics\engine\trainer.py", line 348, in _do_train self._setup_train(world_size) ~~~~~~~~~~~~~~~~~^^^^^^^^^^^^ File "f:\yolov8\ultralytics-main\ultralytics\engine\trainer.py", line 307, in _setup_train self.train_loader = self.get_dataloader( ~~~~~~~~~~~~~~~~~~~^ self.data["train"], batch_size=batch_size, rank=LOCAL_RANK, mode="train" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ ) ^ File "f:\yolov8\ultralytics-main\ultralytics\models\yolo\detect\train.py", line 90, in get_dataloader return build_dataloader(dataset, batch_size, workers, shuffle, rank) # return dataloader File "f:\yolov8\ultralytics-main\ultralytics\data\build.py", line 183, in build_dataloader return InfiniteDataLoader( dataset=dataset, ...<8 lines>... drop_last=drop_last, ) File "f:\yolov8\ultralytics-main\ultralytics\data\build.py", line 58, in __init__ self.iterator = super().__iter__() ~~~~~~~~~~~~~~~~^^ File "F:\Minicond3\envs\yolov8\Lib\site-packages\torch\utils\data\dataloader.py", line 493, in __iter__ return self._get_iterator() ~~~~~~~~~~~~~~~~~~^^ File "F:\Minicond3\envs\yolov8\Lib\site-packages\torch\utils\data\dataloader.py", line 424, in _get_iterator return _MultiProcessingDataLoaderIter(self) File "F:\Minicond3\envs\yolov8\Lib\site-packages\torch\utils\data\dataloader.py", line 1171, in __init__ w.start() ~~~~~~~^^ File "F:\Minicond3\envs\yolov8\Lib\multiprocessing\process.py", line 121, in start self._popen = self._Popen(self) ~~~~~~~~~~~^^^^^^ File "F:\Minicond3\envs\yolov8\Lib\multiprocessing\context.py", line 224, in _Popen return _default_context.get_context().Process._Popen(process_obj) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^ File "F:\Minicond3\envs\yolov8\Lib\multiprocessing\context.py", line 337, in _Popen return Popen(process_obj) File "F:\Minicond3\envs\yolov8\Lib\multiprocessing\popen_spawn_win32.py", line 47, in __init__ prep_data = spawn.get_preparation_data(process_obj._name) File "F:\Minicond3\envs\yolov8\Lib\multiprocessing\spawn.py", line 164, in get_preparation_data _check_not_importing_main() ~~~~~~~~~~~~~~~~~~~~~~~~~^^ File "F:\Minicond3\envs\yolov8\Lib\multiprocessing\spawn.py", line 140, in _check_not_importing_main raise RuntimeError(''' ...<16 lines>... ''') RuntimeError: An attempt has been made to start a new process before the current process has finished its bootstrapping phase. This probably means that you are not using fork to start your child processes and you have forgotten to use the proper idiom in the main module: if __name__ == '__main__': freeze_support() ... The "freeze_support()" line can be omitted if the program is not going to be frozen to produce an executable. To fix this issue, refer to the "Safe importing of main module" section in https://docs.python.org/3/library/multiprocessing.html

Traceback (most recent call last): File "D:/pythonProject/DATA/jaffeim.ages(1)/test2.py", line 18, in <module> scores = cross_val_score(knn, X, y, cv=5, scoring='accuracy') File "C:\ProgramData\Anaconda3\envs\pythonProject\lib\site-packages\sklearn\model_selection\_validation.py", line 520, in cross_val_score error_score=error_score, File "C:\ProgramData\Anaconda3\envs\pythonProject\lib\site-packages\sklearn\model_selection\_validation.py", line 283, in cross_validate for train, test in cv.split(X, y, groups) File "C:\ProgramData\Anaconda3\envs\pythonProject\lib\site-packages\joblib\parallel.py", line 1043, in __call__ if self.dispatch_one_batch(iterator): File "C:\ProgramData\Anaconda3\envs\pythonProject\lib\site-packages\joblib\parallel.py", line 833, in dispatch_one_batch islice = list(itertools.islice(iterator, big_batch_size)) File "C:\ProgramData\Anaconda3\envs\pythonProject\lib\site-packages\sklearn\model_selection\_validation.py", line 268, in <genexpr> delayed(_fit_and_score)( File "C:\ProgramData\Anaconda3\envs\pythonProject\lib\site-packages\sklearn\model_selection\_split.py", line 340, in split for train, test in super().split(X, y, groups): File "C:\ProgramData\Anaconda3\envs\pythonProject\lib\site-packages\sklearn\model_selection\_split.py", line 86, in split for test_index in self._iter_test_masks(X, y, groups): File "C:\ProgramData\Anaconda3\envs\pythonProject\lib\site-packages\sklearn\model_selection\_split.py", line 709, in _iter_test_masks test_folds = self._make_test_folds(X, y) File "C:\ProgramData\Anaconda3\envs\pythonProject\lib\site-packages\sklearn\model_selection\_split.py", line 673, in _make_test_folds " number of members in each class." % (self.n_splits) ValueError: n_splits=5 cannot be greater than the number of members in each class. 进程已结束,退出代码1

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