Datasets:

---

Sim2Real

/

anomaly_detection_experiments

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Sim2Real 8

• "pathlib.WindowsPath",
• "torchvision.transforms.v2._geometry.Resize",
• "anomalib.models.image.reverse_distillation.components.bottleneck.OCBE",
• "anomalib.models.components.backbone.resnet_decoder.ResNetDecoder",
• "torchmetrics.utilities.data.dim_zero_min",
• "torch.device",
• "torch.float32",
• "anomalib.metrics.f1_score.F1Score",
• "torch.LongStorage",
• "torch._utils._rebuild_parameter",
• "anomalib.metrics.auroc.AUROC",
• "anomalib.metrics.evaluator.Evaluator",
• "timm.models._features.FeatureInfo",
• "anomalib.models.image.reverse_distillation.anomaly_map.AnomalyMapGenerator",
• "lightning.fabric.utilities.data.AttributeDict",
• "torchvision.transforms.v2._misc.Normalize",
• "anomalib.models.image.reverse_distillation.anomaly_map.AnomalyMapGenerationMode",
• "torch.nn.modules.activation.ReLU",
• "collections.OrderedDict",
• "torch._utils._rebuild_tensor_v2",
• "anomalib.post_processing.post_processor.PostProcessor",
• "__builtin__.getattr",
• "anomalib.models.image.reverse_distillation.loss.ReverseDistillationLoss",
• "anomalib.models.components.backbone.resnet_decoder.DecoderBottleneck",
• "anomalib.pre_processing.pre_processor.PreProcessor",
• "__builtin__.set",
• "torchmetrics.utilities.data.dim_zero_max",
• "anomalib.models.image.reverse_distillation.lightning_model.ReverseDistillation",
• "timm.models.resnet.Bottleneck",
• "timm.models._features.FeatureListNet",
• "torchmetrics.metric.jit_distributed_available",
• "torchvision.transforms.functional.InterpolationMode",
• "timm.layers.format.Format",
• "torch.nn.modules.conv.Conv2d",
• "anomalib.metrics.threshold.f1_adaptive_threshold.F1AdaptiveThreshold",
• "anomalib.metrics.min_max.MinMax",
• "anomalib.visualization.image.visualizer.ImageVisualizer",
• "torchvision.models.resnet.Bottleneck",
• "torchvision.transforms.v2._container.Compose",
• "torch.nn.modules.batchnorm.BatchNorm2d",
• "anomalib.models.image.reverse_distillation.torch_model.ReverseDistillationModel",
• "torch.nn.modules.container.ModuleList",
• "torch.nn.modules.linear.Identity",
• "anomalib.metrics.aupro.AUPRO",
• "torch.FloatStorage",
• "torch.nn.modules.pooling.MaxPool2d",
• "torch.nn.modules.conv.ConvTranspose2d",
• "anomalib.models.components.feature_extractors.timm.TimmFeatureExtractor",
• "torchmetrics.utilities.data.dim_zero_cat",
• "torchmetrics.utilities.data.dim_zero_sum",
• "torch.nn.modules.container.Sequential"

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