Datasets:

---

Sim2Real

/

anomaly_detection_experiments

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Sim2Real 8

• "torchvision.transforms.v2._container.Compose",
• "lightning.pytorch.utilities.model_helpers._ModuleMode",
• "lightning.pytorch.trainer.states.TrainerStatus",
• "lightning.pytorch.loops.progress._StartedTracker",
• "torchvision.transforms.v2._deprecated.ToTensor",
• "anomalib.data.utils.path.DirType",
• "torch.FloatStorage",
• "lightning.pytorch.callbacks.rich_model_summary.RichModelSummary",
• "anomalib.post_processing.post_processor.PostProcessor",
• "torch.nn.modules.container.ParameterDict",
• "torchvision.transforms.v2._geometry.CenterCrop",
• "__builtin__.set",
• "lightning.fabric.plugins.io.torch_io.TorchCheckpointIO",
• "pandas._libs.internals._unpickle_block",
• "torch.nn.modules.conv.Conv2d",
• "lightning.pytorch.utilities.combined_loader.CombinedLoader",
• "lightning.pytorch.loops.training_epoch_loop._TrainingEpochLoop",
• "torchvision.datasets.folder.default_loader",
• "rich.text.Text",
• "lightning.fabric.plugins.environments.lightning.LightningEnvironment",
• "torch.amp.grad_scaler.GradScaler",
• "torchmetrics.metric.jit_distributed_available",
• "lightning.fabric.utilities.data.AttributeDict",
• "lightning.pytorch.strategies.strategy._ForwardRedirection",
• "pandas.core.arrays.integer.Int64Dtype",
• "torchvision.datasets.folder.ImageFolder",
• "anomalib.models.image.efficient_ad.torch_model.Decoder",
• "numpy.dtype",
• "pandas.core.indexes.base.Index",
• "lightning.pytorch.loops.fetchers._PrefetchDataFetcher",
• "lightning.pytorch.callbacks.progress.rich_progress.RichProgressBar",
• "torch.nn.modules.dropout.Dropout",
• "anomalib.pre_processing.pre_processor.PreProcessor",
• "lightning.fabric.utilities.seed.pl_worker_init_function",
• "torch._utils._rebuild_parameter",
• "torch._C._VariableFunctionsClass",
• "anomalib.metrics.evaluator.Evaluator",
• "anomalib.visualization.image.visualizer.ImageVisualizer",
• "lightning.pytorch.loggers.wandb.WandbLogger",
• "lightning.pytorch.loops.progress._ProcessedTracker",
• "anomalib.metrics.threshold.f1_adaptive_threshold.F1AdaptiveThreshold",
• "__main__.RawVectorExportCallback",
• "lightning.pytorch.loops.progress._OptimizerProgress",
• "anomalib.metrics.f1_score.F1Score",
• "anomalib.metrics.min_max.MinMax",
• "numpy._core.multiarray._reconstruct",
• "lightning.pytorch.loggers.csv_logs.CSVLogger",
• "lightning.pytorch.callbacks.progress.rich_progress.RichProgressBarTheme",
• "torch.device",
• "anomalib.models.image.efficient_ad.torch_model.EfficientAdModelSize",
• "__builtin__.long",
• "lightning.pytorch.loops.fit_loop._FitLoop",
• "numpy.ndarray",
• "__builtin__.slice",
• "lightning.pytorch.utilities.combined_loader._Sequential",
• "torch.amp.grad_scaler._refresh_per_optimizer_state",
• "torch.utils.data.sampler.SequentialSampler",
• "fsspec.implementations.local.LocalFileSystem",
• "torch.nn.modules.container.ModuleList",
• "lightning.pytorch.strategies.single_device.SingleDeviceStrategy",
• "torchmetrics.utilities.data.dim_zero_max",
• "torch.utils.data.sampler.BatchSampler",
• "anomalib.models.image.efficient_ad.torch_model.SmallPatchDescriptionNetwork",
• "anomalib.data.datamodules.image.folder.Folder",
• "anomalib.callbacks.timer.TimerCallback",
• "lightning.pytorch.trainer.states.RunningStage",
• "functools.partial",
• "__main__.ForceBatchSizeLoggingCallback",
• "torch.utils._pytree.LeafSpec",
• "lightning.pytorch.trainer.connectors.data_connector._DataConnector",
• "lightning.pytorch.trainer.connectors.data_connector._DataHookSelector",
• "lightning.pytorch.loops.progress._ReadyCompletedTracker",
• "anomalib.metrics.auroc.AUROC",
• "lightning.pytorch.trainer.trainer.Trainer",
• "lightning.pytorch.loops.optimization.manual._ManualOptimization",
• "torch.nn.modules.pooling.AvgPool2d",
• "lightning.pytorch.trainer.connectors.logger_connector.result._ResultCollection",
• "lightning.pytorch.trainer.states.TrainerFn",
• "anomalib.models.image.efficient_ad.lightning_model.EfficientAd",
• "torchmetrics.utilities.data.dim_zero_min",
• "lightning.pytorch.utilities.combined_loader._MaxSizeCycle",
• "lightning.pytorch.plugins.precision.amp.MixedPrecision",
• "torchvision.transforms.v2._color.RandomGrayscale",
• "_codecs.encode",
• "anomalib.data.datasets.image.folder.FolderDataset",
• "torch.float32",
• "anomalib.data.dataclasses.torch.image.ImageBatch",
• "lightning.pytorch.loops.prediction_loop._PredictionLoop",
• "lightning.pytorch.loggers.csv_logs.ExperimentWriter",
• "lightning.pytorch.trainer.connectors.logger_connector.result._Metadata",
• "__main__.FolderDataModule",
• "lightning.pytorch.profilers.base.PassThroughProfiler",
• "lightning.pytorch.utilities.types.LRSchedulerConfig",
• "lightning.pytorch.trainer.connectors.signal_connector._SignalConnector",
• "lightning.pytorch.loops.progress._BatchProgress",
• "fsspec.spec.make_instance",
• "torchvision.transforms.v2._geometry.Resize",
• "anomalib.data.utils.split.TestSplitMode",
• "lightning.pytorch.trainer.connectors.logger_connector.logger_connector._LoggerConnector",
• "torchmetrics.utilities.data.dim_zero_sum",
• "anomalib.data.utils.split.ValSplitMode",
• "torch.utils.data._utils.collate.default_collate",
• "anomalib.callbacks.rich_progress_bar.MaxStepsProgressCallback",
• "torchvision.transforms.functional.InterpolationMode",
• "collections.defaultdict",
• "torch._utils._rebuild_tensor_v2",
• "anomalib.models.image.efficient_ad.torch_model.AutoEncoder",
• "lightning.pytorch.loops.progress._OptimizationProgress",
• "lightning.pytorch.loops.optimization.automatic._AutomaticOptimization",
• "anomalib.callbacks.checkpoint.ModelCheckpoint",
• "lightning.pytorch.trainer.states.TrainerState",
• "anomalib.models.image.efficient_ad.torch_model.EfficientAdModel",
• "torch.optim.lr_scheduler.StepLR",
• "lightning.pytorch.loops.progress._SchedulerProgress",
• "pandas.core.frame.DataFrame",
• "__main__.BinDatasetConfig",
• "torch.LongStorage",
• "lightning.pytorch.trainer.connectors.logger_connector.result._Sync",
• "lightning.pytorch.loops.evaluation_loop._EvaluationLoop",
• "lightning.pytorch.trainer.connectors.accelerator_connector._AcceleratorConnector",
• "torchmetrics.utilities.data.dim_zero_cat",
• "anomalib.data.utils.split.Split",
• "lightning.pytorch.accelerators.cuda.CUDAAccelerator",
• "lightning.pytorch.callbacks.progress.rich_progress.MetricsTextColumn",
• "torchvision.datasets.vision.StandardTransform",
• "collections.OrderedDict",
• "lightning.pytorch.loops.progress._Progress",
• "lightning.pytorch.trainer.connectors.callback_connector._CallbackConnector",
• "torch.optim.adam.Adam",
• "pandas.core.indexes.base._new_Index",
• "anomalib.metrics.aupro.AUPRO",
• "lightning.pytorch.trainer.connectors.checkpoint_connector._CheckpointConnector",
• "__builtin__.getattr",
• "lightning.pytorch.trainer.connectors.logger_connector.result._ResultMetric",
• "lightning_utilities.core.rank_zero.WarningCache",
• "pandas.core.indexes.range.RangeIndex",
• "torch.utils.data.dataloader.DataLoader",
• "pandas.core.internals.managers.BlockManager",
• "pathlib.WindowsPath",
• "anomalib.models.image.efficient_ad.torch_model.Encoder",
• "lightning.pytorch.trainer.connectors.data_connector._DataLoaderSource",
• "pandas.core.arrays.integer.IntegerArray",
• "torch.utils.data.sampler.RandomSampler",
• "__builtin__.dict"

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