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AIQuest

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Car_Damage_Detectiion

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• "sklearn.preprocessing._encoders.OneHotEncoder",
• "sklearn.compose._column_transformer.ColumnTransformer",
• "sklearn.preprocessing._encoders.OrdinalEncoder",
• "numpy.float64",
• "builtins.slice",
• "sklearn.tree._tree.Tree",
• "sklearn.impute._base.SimpleImputer",
• "sklearn.preprocessing._function_transformer.FunctionTransformer",
• "numpy.core.multiarray._reconstruct",
• "sklearn.preprocessing._data.StandardScaler",
• "numpy.dtype",
• "numpy.ndarray",
• "sklearn.tree._classes.DecisionTreeRegressor",
• "sklearn.pipeline.Pipeline",
• "numpy.core.multiarray.scalar"

How to fix it?

• "ultralytics.utils.IterableSimpleNamespace",
• "torch.nn.modules.upsampling.Upsample",
• "torch.nn.modules.activation.SiLU",
• "ultralytics.nn.modules.conv.Conv",
• "ultralytics.nn.modules.block.C2f",
• "ultralytics.nn.modules.head.Detect",
• "__builtin__.set",
• "torch.nn.modules.container.Sequential",
• "torch.device",
• "ultralytics.nn.modules.conv.Concat",
• "torch.HalfStorage",
• "ultralytics.utils.tal.TaskAlignedAssigner",
• "ultralytics.nn.modules.block.SPPF",
• "torch._utils._rebuild_tensor_v2",
• "torch._utils._rebuild_parameter",
• "torch.nn.modules.container.ModuleList",
• "torch.FloatStorage",
• "ultralytics.nn.modules.block.Bottleneck",
• "torch.nn.modules.pooling.MaxPool2d",
• "torch.Size",
• "collections.OrderedDict",
• "torch.nn.modules.loss.BCEWithLogitsLoss",
• "torch.nn.modules.conv.Conv2d",
• "ultralytics.utils.loss.v8DetectionLoss",
• "torch.LongStorage",
• "ultralytics.nn.tasks.DetectionModel",
• "ultralytics.utils.loss.BboxLoss",
• "ultralytics.nn.modules.block.DFL",
• "torch.nn.modules.batchnorm.BatchNorm2d"

How to fix it?

• "torch.nn.modules.container.Sequential",
• "ultralytics.utils.loss.v8DetectionLoss",
• "torch.nn.modules.conv.Conv2d",
• "torch.nn.modules.upsampling.Upsample",
• "torch.nn.modules.batchnorm.BatchNorm2d",
• "ultralytics.nn.modules.head.Detect",
• "torch._utils._rebuild_tensor_v2",
• "ultralytics.utils.tal.TaskAlignedAssigner",
• "torch.nn.modules.pooling.MaxPool2d",
• "ultralytics.nn.modules.block.Bottleneck",
• "__builtin__.set",
• "torch.nn.modules.container.ModuleList",
• "torch.HalfStorage",
• "torch.FloatStorage",
• "torch.Size",
• "ultralytics.nn.modules.block.SPPF",
• "ultralytics.utils.loss.BboxLoss",
• "torch.nn.modules.activation.SiLU",
• "torch.device",
• "ultralytics.nn.tasks.DetectionModel",
• "ultralytics.utils.IterableSimpleNamespace",
• "torch._utils._rebuild_parameter",
• "collections.OrderedDict",
• "torch.nn.modules.loss.BCEWithLogitsLoss",
• "ultralytics.nn.modules.conv.Concat",
• "ultralytics.nn.modules.block.C2f",
• "ultralytics.nn.modules.block.DFL",
• "ultralytics.nn.modules.conv.Conv",
• "torch.LongStorage"

How to fix it?

• "torch._utils._rebuild_parameter",
• "torch.FloatStorage",
• "ultralytics.nn.modules.SPPF",
• "torch.nn.modules.activation.SiLU",
• "ultralytics.nn.modules.DFL",
• "ultralytics.nn.modules.Bottleneck",
• "ultralytics.nn.modules.Detect",
• "torch.nn.modules.batchnorm.BatchNorm2d",
• "torch.nn.modules.upsampling.Upsample",
• "torch.LongStorage",
• "ultralytics.nn.modules.C2f",
• "torch.nn.modules.container.ModuleList",
• "collections.OrderedDict",
• "__builtin__.set",
• "ultralytics.nn.tasks.DetectionModel",
• "torch._utils._rebuild_tensor_v2",
• "torch.nn.modules.conv.Conv2d",
• "ultralytics.nn.modules.Conv",
• "ultralytics.nn.modules.Concat",
• "torch.Size",
• "torch.nn.modules.pooling.MaxPool2d",
• "torch.nn.modules.container.Sequential",
• "torch.HalfStorage"

How to fix it?