raceback (most recent call last): File "C:\Users\Administrator\PycharmProjects\pythonProject\test.py", line 72, in <module> rf_analysis = jieba.analyse.extract_tags(reference, topK=20) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "C:\Users\Administrator\AppData\Local\Programs\Python\Python311\Lib\site-packages\jieba\analyse\tfidf.py", line 94, in extract_tags for w in words: File "C:\Users\Administrator\AppData\Local\Programs\Python\Python311\Lib\site-packages\jieba\__init__.py", line 300, in cut sentence = strdecode(sentence) ^^^^^^^^^^^^^^^^^^^ File "C:\Users\Administrator\AppData\Local\Programs\Python\Python311\Lib\site-packages\jieba\_compat.py", line 79, in strdecode sentence = sentence.decode('utf-8') ^^^^^^^^^^^^^^^ File "C:\Users\Administrator\AppData\Local\Programs\Python\Python311\Lib\site-packages\pandas\core\generic.py", line 5989, in __getattr__ return object.__getattribute__(self, name) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ AttributeError: 'Series' object has no attribute 'decode'

时间: 2023-07-22 12:10:36 浏览: 44
根据您提供的错误信息,看起来问题出现在字符串进行解码时。错误指出 `AttributeError: 'Series' object has no attribute 'decode'`,提示 'Series' 对象没有 `decode` 属性。 这个错误通常是因为您正在使用 Pandas 库的 Series 对象,而不是普通的字符串。`jieba` 库所需的输入应为字符串,而不是 Series 对象。 要解决这个问题,您可以将 Series 对象转换为普通的字符串,然后再进行处理。您可以使用 `.tolist()` 方法将 Series 对象转换为列表,然后使用列表索引选择特定的元素。 以下是修改后的示例代码: ```python reference_str = reference.tolist()[0] # 将 Series 对象转换为普通字符串 rf_analysis = jieba.analyse.extract_tags(reference_str, topK=20) print(rf_analysis) ``` 在上述代码中,我使用 `.tolist()[0]` 将 `reference` Series 对象转换为普通字符串,并将其命名为 `reference_str`。 然后,我使用 `jieba.analyse.extract_tags()` 方法对 `reference_str` 进行处理,提取关键词。 请注意,根据您的实际情况,您可能需要调整代码以适应您的数据结构和需求。如果您还有其他疑问,请随时提问。非常抱歉给您带来的困扰。
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Traceback (most recent call last): File "C:\Users\Administrator\PycharmProjects\pythonProject\test.py", line 61, in <module> resul1 = ' '.join(abstract_march).encode('utf-8') # 将文本中的单词转换为UTF-8编码 ^^^^^^^^^^^^^^^^^^^^^^^^ TypeError: sequence item 0: expected str instance, list found

非常抱歉,我之前给出的代码有问题。根您提供的错误提示,错误出现在尝试使用`join()`方法时。它表明`abstract_march`是一个列表而不是字符串,因此无法使用`join()`方法。 为了解决这个问题,您可以将`abstract_march`列表中的单词转换为字符串,然后再对字符串进行编码。 以下是修改后的示例代码: ```python resul1 = ' '.join(abstract_march) # 将文本中的单词连接成一个字符串 resul1_encoded = resul1.encode('utf-8') # 对字符串进行UTF-8编码 resul2 = [word.encode('utf-8') for word in keywords] # 将关键词转换为UTF-8编码 matches = [] for key in resul1_encoded: if key in resul2: matches.append(key) print(matches) ``` 在上述代码中,我首先使用`join()`方法将`abstract_march`列表中的单词连接成一个字符串,并将该字符串命名为`resul1`。然后,我对`resul1`字符串使用`.encode('utf-8')`进行UTF-8编码,并将编码后的结果命名为`resul1_encoded`。 接下来,我将`keywords`中的关键词转换为UTF-8编码,并存储在`resul2`列表中。 最后,我使用循环遍历`resul1_encoded`,并检查每个编码后的单词是否存在于`resul2`中,如果存在则将其添加到`matches`列表中。 请注意,根据您的具体需求,您可能需要根据实际情况修改代码。如果您还有其他疑问,请随时提问。非常抱歉给您带来的困扰。

Traceback (most recent call last): File "D:\XTF\pythonProject\test.py", line 11, in <module> mxd = arcpy.mapping.MapDocument("C:/Users/Administrator/Desktop/python") File "D:\Program Files (x86)\ArcGIS\Desktop10.8\ArcPy\arcpy\arcobjects\mixins.py", line 651, in __init__ assert (os.path.isfile(mxd) or (mxd.lower() == "current")), gp.getIDMessage(89004, "Invalid MXD filename") AssertionError: <exception str() failed>

抱歉,您遇到了一个错误。根据错误信息,看起来是由于指定的地图文档路径无效导致的。 请确保您提供的地图文档路径是正确的,并且指向一个有效的地图文档文件(.mxd)。您可以尝试使用绝对路径来确保路径的准确性。 另外,请确保您有读取和写入指定路径的权限,并且输入的路径使用正确的斜杠方向(在Windows上使用反斜杠\,在Linux或Mac上使用正斜杠/)。 如果问题仍然存在,请提供更详细的错误信息和代码段,以便我能够更好地帮助您解决问题。

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sys:1: FutureWarning: In a future version of pandas all arguments of read_csv except for the argument 'filepath_or_buffer' will be keyword-only Traceback (most recent call last): File "C:/Users/Administrator/Desktop/test/11.py", line 22, in <module> posi = pd.read_csv("C:\\Users\\Administrator\\Desktop\\工作簿1.csv",'r') File "C:\Python37\lib\site-packages\pandas\util\_decorators.py", line 311, in wrapper return func(*args, **kwargs) File "C:\Python37\lib\site-packages\pandas\io\parsers\readers.py", line 586, in read_csv return _read(filepath_or_buffer, kwds) File "C:\Python37\lib\site-packages\pandas\io\parsers\readers.py", line 482, in _read parser = TextFileReader(filepath_or_buffer, **kwds) File "C:\Python37\lib\site-packages\pandas\io\parsers\readers.py", line 811, in __init__ self._engine = self._make_engine(self.engine) File "C:\Python37\lib\site-packages\pandas\io\parsers\readers.py", line 1040, in _make_engine return mapping[engine](self.f, **self.options) # type: ignore[call-arg] File "C:\Python37\lib\site-packages\pandas\io\parsers\c_parser_wrapper.py", line 69, in __init__ self._reader = parsers.TextReader(self.handles.handle, **kwds) File "pandas\_libs\parsers.pyx", line 542, in pandas._libs.parsers.TextReader.__cinit__ File "pandas\_libs\parsers.pyx", line 642, in pandas._libs.parsers.TextReader._get_header File "pandas\_libs\parsers.pyx", line 843, in pandas._libs.parsers.TextReader._tokenize_rows File "pandas\_libs\parsers.pyx", line 1917, in pandas._libs.parsers.raise_parser_error UnicodeDecodeError: 'utf-8' codec can't decode byte 0xd0 in position 0: invalid continuation byte是什么意思

Traceback (most recent call last): File "C:\Users\Administrator\Desktop\轨迹训练\Transformer_V2_radicla_test.py", line 146, in <module> main() File "C:\Users\Administrator\Desktop\轨迹训练\Transformer_V2_radicla_test.py", line 131, in main train_losses, val_losses = train(model, optimizer, criterion, traindataloader, valdataloader, epochs) # 模型训练 File "C:\Users\Administrator\Desktop\轨迹训练\Transformer_V2_radicla_test.py", line 65, in train pred = model(input_data, target) File "D:\anaconda2\lib\site-packages\torch\nn\modules\module.py", line 1130, in _call_impl return forward_call(*input, **kwargs) File "C:\Users\Administrator\Desktop\轨迹训练\Transformer_V2_radicla_test.py", line 42, in forward output = self.decoder(tgt, memory) File "D:\anaconda2\lib\site-packages\torch\nn\modules\module.py", line 1130, in _call_impl return forward_call(*input, **kwargs) File "D:\anaconda2\lib\site-packages\torch\nn\modules\transformer.py", line 291, in forward output = mod(output, memory, tgt_mask=tgt_mask, File "D:\anaconda2\lib\site-packages\torch\nn\modules\module.py", line 1130, in _call_impl return forward_call(*input, **kwargs) File "D:\anaconda2\lib\site-packages\torch\nn\modules\transformer.py", line 577, in forward x = self.norm2(x + self._mha_block(x, memory, memory_mask, memory_key_padding_mask)) File "D:\anaconda2\lib\site-packages\torch\nn\modules\transformer.py", line 594, in _mha_block x = self.multihead_attn(x, mem, mem, File "D:\anaconda2\lib\site-packages\torch\nn\modules\module.py", line 1130, in _call_impl return forward_call(*input, **kwargs) File "D:\anaconda2\lib\site-packages\torch\nn\modules\activation.py", line 1153, in forward attn_output, attn_output_weights = F.multi_head_attention_forward( File "D:\anaconda2\lib\site-packages\torch\nn\functional.py", line 5122, in multi_head_attention_forward k = k.contiguous().view(k.shape[0], bsz * num_heads, head_dim).transpose(0, 1) RuntimeError: shape '[10, 297, 1]' is invalid for input of size 300什么原因,如何解决?

C:\Users\Administrator\AppData\Local\Programs\Python\Python311\Lib\site-packages\pydub\utils.py:170: RuntimeWarning: Couldn't find ffmpeg or avconv - defaulting to ffmpeg, but may not work warn("Couldn't find ffmpeg or avconv - defaulting to ffmpeg, but may not work", RuntimeWarning) C:\Users\Administrator\AppData\Local\Programs\Python\Python311\Lib\site-packages\pydub\utils.py:184: RuntimeWarning: Couldn't find ffplay or avplay - defaulting to ffplay, but may not work warn("Couldn't find ffplay or avplay - defaulting to ffplay, but may not work", RuntimeWarning) Traceback (most recent call last): File "D:\桌面\test\location.py", line 28, in <module> play(audio) File "C:\Users\Administrator\AppData\Local\Programs\Python\Python311\Lib\site-packages\pydub\playback.py", line 71, in play _play_with_ffplay(audio_segment) File "C:\Users\Administrator\AppData\Local\Programs\Python\Python311\Lib\site-packages\pydub\playback.py", line 15, in _play_with_ffplay seg.export(f.name, "wav") File "C:\Users\Administrator\AppData\Local\Programs\Python\Python311\Lib\site-packages\pydub\audio_segment.py", line 867, in export out_f, _ = _fd_or_path_or_tempfile(out_f, 'wb+') ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "C:\Users\Administrator\AppData\Local\Programs\Python\Python311\Lib\site-packages\pydub\utils.py", line 60, in _fd_or_path_or_tempfile fd = open(fd, mode=mode) ^^^^^^^^^^^^^^^^^^^ PermissionError: [Errno 13] Permission denied: 'C:\\Users\\ADMINI~1\\AppData\\Local\\Temp\\tmpg196jawm.wav'

下载别人的数据集在YOLOV5进行训练发现出现报错,请给出具体正确的处理拌饭Plotting labels... C:\ProgramData\Anaconda3\envs\pytorch1\lib\site-packages\seaborn\axisgrid.py:118: UserWarning: The figure layout has changed to tight self._figure.tight_layout(*args, **kwargs) autoanchor: Analyzing anchors... anchors/target = 4.24, Best Possible Recall (BPR) = 0.9999 Image sizes 640 train, 640 test Using 0 dataloader workers Logging results to runs\train\exp20 Starting training for 42 epochs... Epoch gpu_mem box obj cls total labels img_size 0%| | 0/373 [00:00<?, ?it/s][ WARN:0@20.675] global loadsave.cpp:248 cv::findDecoder imread_('C:/Users/Administrator/Desktop/Yolodone/VOCdevkit/labels/train'): can't open/read file: check file path/integrity 0%| | 0/373 [00:00<?, ?it/s] Traceback (most recent call last): File "C:\Users\Administrator\Desktop\Yolodone\train.py", line 543, in <module> train(hyp, opt, device, tb_writer) File "C:\Users\Administrator\Desktop\Yolodone\train.py", line 278, in train for i, (imgs, targets, paths, _) in pbar: # batch ------------------------------------------------------------- File "C:\ProgramData\Anaconda3\envs\pytorch1\lib\site-packages\tqdm\std.py", line 1178, in __iter__ for obj in iterable: File "C:\Users\Administrator\Desktop\Yolodone\utils\datasets.py", line 104, in __iter__ yield next(self.iterator) File "C:\ProgramData\Anaconda3\envs\pytorch1\lib\site-packages\torch\utils\data\dataloader.py", line 633, in __next__ data = self._next_data() File "C:\ProgramData\Anaconda3\envs\pytorch1\lib\site-packages\torch\utils\data\dataloader.py", line 677, in _next_data data = self._dataset_fetcher.fetch(index) # may raise StopIteration File "C:\ProgramData\Anaconda3\envs\pytorch1\lib\site-packages\torch\utils\data\_utils\fetch.py", line 51, in fetch data = [self.dataset[idx] for idx in possibly_batched_index] File "C:\ProgramData\Anaconda3\envs\pytorch1\lib\site-packages\torch\utils\data\_utils\fetch.py", line 51, in data = [self.dataset[idx] for idx in possibly_batched_index] File "C:\Users\Administrator\Desktop\Yolodone\utils\datasets.py", line 525, in __getitem__ img, labels = load_mosaic(self, index) File "C:\Users\Administrator\Desktop\Yolodone\utils\datasets.py", line 679, in load_mosaic img, _, (h, w) = load_image(self, index) File "C:\Users\Administrator\Desktop\Yolodone\utils\datasets.py", line 634, in load_image assert img is not None, 'Image Not Found ' + path AssertionError: Image Not Found C:/Users/Administrator/Desktop/Yolodone/VOCdevkit/labels/train Process finished with exit code 1

--------------------------------------------------------------------------- AttributeError Traceback (most recent call last) Cell In[36], line 5 3 colnm = data_train1.columns.tolist() # 列表头 4 mcorr = data_train1[colnm].corr(method="spearman") # 相关系数矩阵,即给出了任意两个变量之间的相关系数 ----> 5 mask = np.zeros_like(mcorr, dtype=np.bool) # 构造与mcorr同维数矩阵 为bool型 6 mask[np.triu_indices_from(mask)] = True # 角分线右侧为True 7 cmap = sns.diverging_palette(220, 10, as_cmap=True) # 返回matplotlib colormap对象 File c:\Users\Administrator\AppData\Local\Programs\Python\Python38\lib\site-packages\numpy\__init__.py:305, in __getattr__(attr) 300 warnings.warn( 301 f"In the future np.{attr} will be defined as the " 302 "corresponding NumPy scalar.", FutureWarning, stacklevel=2) 304 if attr in __former_attrs__: --> 305 raise AttributeError(__former_attrs__[attr]) 307 # Importing Tester requires importing all of UnitTest which is not a 308 # cheap import Since it is mainly used in test suits, we lazy import it 309 # here to save on the order of 10 ms of import time for most users 310 # 311 # The previous way Tester was imported also had a side effect of adding 312 # the full numpy.testing namespace 313 if attr == 'testing': AttributeError: module 'numpy' has no attribute 'bool'. np.bool was a deprecated alias for the builtin bool. To avoid this error in existing code, use bool by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use np.bool_ here. The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations出现的问题

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