Python库PBar2最新版本安装指南

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0 下载量 124 浏览量 更新于2024-11-23 收藏 19KB ZIP 举报
该库的版本为1.11.4,适用于Python 3,可以在任何操作系统上运行,因为它是全平台的(any)。文件扩展名为.wheel,这是一个Python官方认可的分发格式,它提供了更快的安装性能和更少的安装失败几率。 首先,我们来了解一下什么是wheel格式文件。Wheel是一个PEP 427中定义的Python包的二进制分发格式,目的是为了简化安装过程。Wheel文件可以包含编译后的扩展,同时不需要安装者在安装过程中进行编译。这使得安装过程更加快速和可靠,因为安装者不需要拥有编译环境。 接下来,我们谈谈PBar2库。PBar2是专门为Python设计的一个进度条库,它是pbar库的更新版本,提供了更多的功能和改进。在程序运行时,进度条可以给用户提供视觉反馈,特别是在长时间运行的任务中,进度条可以让用户知道程序正在运行并且可以预测大概还需要多久完成任务。这对于提升用户体验是非常有帮助的。 使用PBar2库需要Python基础,如果你是Python开发者,并且在你的项目中有需要显示进度条的场景,那么PBar2库是一个不错的选择。它拥有简洁的API,可以轻松集成到各种项目中。在安装之前,需要确保你的系统已经安装了Python环境,且Python版本必须符合该库的要求。 该资源的安装方法在描述中给出了一个参考链接,根据该链接提供的方法,我们可以下载并安装PBar2库。安装方法一般是通过Python的包管理器pip来完成。pip是一个可以让你安装和管理Python包的工具。通过一行简单的命令,就可以完成库的安装过程。例如,如果你已经下载了wheel文件,可以通过以下命令来安装: ``` pip install ./PBar2-1.11.4-py3-none-any.whl ``` 这行命令告诉pip在当前目录下找到名为`PBar2-1.11.4-py3-none-any.whl`的文件,并进行安装。 对于需要解压的资源,通常指的是源代码的压缩包,用户需要解压后才能查看或者修改源代码。但对于wheel文件来说,这是不需要的,因为wheel文件已经是一个预编译的二进制分发包,用户不需要解压即可直接使用pip安装。 在标签中,我们看到指定了"python 开发语言 Python库",这明确指出了该资源与Python编程语言和库的关联性。在Python的生态系统中,库(Library)是扩展功能的重要组成部分,它允许开发者复用已有的代码,加快开发速度,提高开发效率。 总结来说,PBar2-1.11.4-py3-none-any.whl是一个Python的进度条显示库,使用起来非常方便。它以wheel格式提供,支持Python 3,可以在多平台操作系统中使用。开发者可以使用pip安装该库,并通过简单的API在项目中实现进度条功能,提升用户交互体验。"
2023-06-12 上传

果然刚才那个代码““best_val_acc = 0.0for epoch in range(training_epochs): model.train() train_loss = 0.0 train_mae = 0.0 with tqdm(total=len(train_loader), desc=f’Epoch {epoch + 1}/{training_epochs}', unit=‘batch’, position=0, leave=True) as pbar: for X_batch, Y_batch in train_loader: X_batch, Y_batch = X_batch.to(device), Y_batch.to(device) optimizer.zero_grad() output = model(X_batch) loss = criterion(output, Y_batch) #训练过程 loss.backward() torch.nn.utils.clip_grad_norm_(model.parameters(), max_norm=1.0) optimizer.step() output_np = output.detach().cpu().numpy() Y_batch_np = Y_batch.detach().cpu().numpy() output_np_flat = output_np.reshape(output_np.shape[0], -1) Y_batch_np_flat = Y_batch_np.reshape(Y_batch_np.shape[0], -1) mae = mean_absolute_error(Y_batch_np_flat, output_np_flat) train_loss += loss.item() train_mae += mae.item() pbar.set_postfix({'loss': f'{loss.item():.4f}', 'mae': f'{mae.item():.4f}'}) pbar.update(1) train_loss /= len(train_loader) train_mae /= len(train_loader) history['train_loss'].append(train_loss) history['train_mae'].append(train_mae) model.eval() val_loss = 0.0 val_mae = 0.0 val_acc = 0.0 with torch.no_grad(): for X_batch, Y_batch in valid_loader: X_batch, Y_batch = X_batch.to(device), Y_batch.to(device) output = model(X_batch) loss = criterion(output, Y_batch) output_np = output.detach().cpu().numpy() Y_batch_np = Y_batch.detach().cpu().numpy() output_np_flat = output_np.reshape(output_np.shape[0], -1) Y_batch_np_flat = Y_batch_np.reshape(Y_batch_np.shape[0], -1) mae = mean_absolute_error(Y_batch_np_flat, output_np_flat) val_loss += loss.item() val_mae += mae.item() acc = precision_score(Y_batch_np_flat, output_np_flat) val_acc += acc.item() val_loss /= len(valid_loader) val_mae /= len(valid_loader) val_acc /= len(valid_loader) history['val_loss'].append(val_loss) history['val_mae'].append(val_mae) print( f'Epoch {epoch + 1}/{training_epochs}, Train Loss: {train_loss:.4f}, Validation Loss: {val_loss:.4f}, Validation MAE: {val_mae:.4f}') if val_acc > best_val_acc: best_val_acc = val_acc torch.save(model.state_dict(), file_weights) print(f'Best model saved at epoch {epoch + 1} with validation loss {val_loss:.4f}')””,出现这个问题"Traceback (most recent call last): File "/home/featurize/work/trainkanmuacc.py", line 205, in <module> acc = precision_score(Y_batch_np_flat, output_np_flat) File "/environment/miniconda3/lib/python3.10/site-packages/sklearn/utils/_param_validation.py", line 214, in wrapper return func(*args, **kwargs) File "/environment/miniconda3/lib/python3.10/site-packages/sklearn/metrics/_classification.py", line 2131, in precision_score p, _, _, _ = precision_recall_fscore_support( File "/environment/miniconda3/lib/python3.10/site-packages/sklearn/utils/_param_validation.py", line 187, in wrapper return func(*args, **kwargs) File "/environment/miniconda3/lib/python3.10/site-packages/sklearn/metrics/_classification.py", line 1724, in precision_recall_fscore_support labels = _check_set_wise_labels(y_true, y_pred, average, labels, pos_label) File "/environment/miniconda3/lib/python3.10/site-packages/sklearn/metrics/_classification.py", line 1501, in _check_set_wise_labels y_type, y_true, y_pred = _check_targets(y_true, y_pred) File "/environment/miniconda3/lib/python3.10/site-packages/sklearn/metrics/_classification.py", line 104, in _check_targets raise ValueError("{0} is not supported".format(y_type)) ValueError: continuous-multioutput is not supported"

2025-03-09 上传
226 浏览量

Yolov5 运行train.py文件时报错,可能是我下载的别人的数据集信息如下,清分析原因给出解决办法: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 <listcomp> 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 D:\PycharmProjects\yolov5-hat\VOCdevkit\images\train\000000.jpg

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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 <listcomp> 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 680, in load_mosaic img, _, (h, w) = load_image(self, index) File "C:\Users\Administrator\Desktop\Yolodone\utils\datasets.py", line 635, in load_image assert img is not None, 'Image Not Found ' + path AssertionError: Image Not Found D:\PycharmProjects\yolov5-hat\VOCdevkit\images\train\000000.jpg

224 浏览量