Index _ | A | B | C | D | E | F | G | H | I | K | L | M | N | O | P | R | S | T | U | V | W _ __version__ (in module skself) A accelerator (embedding_benchmark.Config attribute) aggregate_metrics (embedding_benchmark.Config attribute) aggregate_metrics() (embedding_benchmark.Baseline method) anomaly_composition (skself.data.images_from_directory.DatasetBuilder attribute) anomaly_size (skself.data.images_from_directory.DatasetBuilder attribute) arbitrary_types_allowed (skself.data.images_from_directory.DatasetBuilder.Config attribute) args (in module embedding_benchmark) B base_loss (skself.partial_annotations.lazy_model.LazyLossWrapper attribute) base_unet (skself.partial_annotations.lazy_model.LazySegmentationModel attribute) Baseline (class in embedding_benchmark) baseline_id (embedding_benchmark.Config attribute) BaselineMethod (class in embedding_benchmark) batch_size (skself.data.images_from_directory.DatasetBuilder attribute) batch_size_per_device (embedding_benchmark.Config attribute) (embedding_benchmark.LinearClassifier attribute) blend_merge() (in module skself.utils) build_classification_head() (embedding_benchmark.LinearClassifier method) build_critierion() (embedding_benchmark.LinearClassifier method) (embedding_benchmark.SwinL384 method) C calculate_mean_std() (embedding_benchmark.Baseline method) call() (skself.partial_annotations.lazy_model.LazyLossWrapper method) (skself.partial_annotations.lazy_model.LazySegmentationModel method) cfg (embedding_benchmark.BaselineMethod attribute) check_val_every_n_epoch (embedding_benchmark.Config attribute) checkpoint_path (embedding_benchmark.Config attribute) classification_head (embedding_benchmark.LinearClassifier attribute) clear_cache() (in module embedding_benchmark) color_dict (skself.data.images_from_directory.DatasetBuilder attribute) combine_binary_masks() (in module skself.utils) compile() (skself.partial_annotations.lazy_model.LazySegmentationModel method) Config (class in embedding_benchmark) configure_optimizers() (embedding_benchmark.KNNClassifier method) (embedding_benchmark.LinearClassifier method) (embedding_benchmark.SwinL384 method) (embedding_benchmark.ViT_B_16Classifier method) copy_to_folder() (in module skself.utils) create_artificial_anomalies (skself.data.images_from_directory.DatasetBuilder attribute) criterion (embedding_benchmark.LinearClassifier attribute) crop_to_aspect_ratio (skself.data.images_from_directory.DatasetBuilder attribute) D DatasetBuilder (class in skself.data.images_from_directory) DatasetBuilder.Config (class in skself.data.images_from_directory) devices (embedding_benchmark.Config attribute) drop_masks (skself.data.images_from_directory.DatasetBuilder attribute) ds (skself.data.images_from_directory.DatasetBuilder property) E embedding_benchmark module embedding_train_dataset (embedding_benchmark.BaselineMethod attribute) embedding_train_transform (embedding_benchmark.BaselineMethod attribute) embedding_training() (embedding_benchmark.BaselineMethod method) embedding_val_dataset (embedding_benchmark.BaselineMethod attribute) enable_hyper_search_progress_bar() (in module skself) enable_logging (embedding_benchmark.LinearClassifier attribute) (embedding_benchmark.MetricModule attribute) (embedding_benchmark.SwinL384 attribute) epochs (embedding_benchmark.Config attribute) eval_train_transform (embedding_benchmark.BaselineMethod attribute) evaluate() (skself.partial_annotations.lazy_model.LazySegmentationModel method) experiment_result_metrics (embedding_benchmark.Config attribute) F feature_dim (embedding_benchmark.BaselineMethod attribute) (embedding_benchmark.LinearClassifier attribute) (embedding_benchmark.SwinL384Baseline attribute) (embedding_benchmark.ViT_B_16Baseline attribute) feature_dtype (embedding_benchmark.KNNClassifier attribute) fit() (skself.partial_annotations.lazy_model.LazySegmentationModel method) folders_have_subfolders (skself.data.images_from_directory.DatasetBuilder attribute) forward() (embedding_benchmark.LinearClassifier method) (embedding_benchmark.SwinL384 method) (embedding_benchmark.ViTEmbedding method) freeze_model (embedding_benchmark.LinearClassifier attribute) G get_embedding_model() (embedding_benchmark.BaselineMethod method) (embedding_benchmark.ViT_B_16Baseline method) global_transform (skself.data.images_from_directory.DatasetBuilder attribute) H height (skself.data.images_from_directory.DatasetBuilder attribute) I image_directory (skself.data.images_from_directory.DatasetBuilder attribute) K knn_eval() (embedding_benchmark.BaselineMethod method) knn_k (embedding_benchmark.KNNClassifier attribute) knn_predict() (in module embedding_benchmark) knn_t (embedding_benchmark.KNNClassifier attribute) knn_train_dataset (embedding_benchmark.BaselineMethod attribute) knn_val_dataset (embedding_benchmark.BaselineMethod attribute) KNNClassifier (class in embedding_benchmark) L LazyLossWrapper (class in skself.partial_annotations.lazy_model) LazyMetricWrapper (class in skself.partial_annotations.lazy_model) LazySegmentationModel (class in skself.partial_annotations.lazy_model) linear_eval() (embedding_benchmark.BaselineMethod method) linear_train_dataset (embedding_benchmark.BaselineMethod attribute) linear_val_dataset (embedding_benchmark.BaselineMethod attribute) LinearClassifier (class in embedding_benchmark) log_dir (embedding_benchmark.Config attribute) M mask_by_color() (in module skself.utils) mask_directory (skself.data.images_from_directory.DatasetBuilder attribute) mask_index (skself.partial_annotations.lazy_model.LazyLossWrapper attribute) (skself.partial_annotations.lazy_model.LazyMetricWrapper attribute) (skself.partial_annotations.lazy_model.LazySegmentationModel attribute) masking() (in module skself.utils) method_dir (embedding_benchmark.BaselineMethod attribute) method_specific_augmentation (embedding_benchmark.BaselineMethod attribute) (embedding_benchmark.SwinL384Baseline attribute) (embedding_benchmark.ViT_B_16Baseline attribute) methods (embedding_benchmark.Baseline attribute) (embedding_benchmark.Config attribute) MetricCallback (class in embedding_benchmark) MetricModule (class in embedding_benchmark) model (embedding_benchmark.BaselineMethod attribute) (embedding_benchmark.KNNClassifier attribute) (embedding_benchmark.LinearClassifier attribute) (embedding_benchmark.SwinL384Baseline attribute) (embedding_benchmark.ViT_B_16Baseline attribute) (embedding_benchmark.ViT_B_16Classifier attribute) (embedding_benchmark.ViTEmbedding attribute) module embedding_benchmark skself skself.data skself.data.images_from_directory skself.embedding_training skself.gptano skself.partial_annotations skself.partial_annotations.lazy_model skself.test skself.utils N name (embedding_benchmark.BaselineMethod property) normalize (embedding_benchmark.KNNClassifier attribute) normalize_transform (embedding_benchmark.BaselineMethod attribute) num_classes (embedding_benchmark.Config attribute) (embedding_benchmark.KNNClassifier attribute) (embedding_benchmark.LinearClassifier attribute) (embedding_benchmark.MetricModule attribute) (skself.data.images_from_directory.DatasetBuilder property) num_files (skself.data.images_from_directory.DatasetBuilder property) num_workers (embedding_benchmark.Config attribute) O on_train_end() (embedding_benchmark.MetricCallback method) on_train_epoch_end() (embedding_benchmark.MetricModule method) on_train_epoch_start() (embedding_benchmark.KNNClassifier method) (embedding_benchmark.LinearClassifier method) on_validation_end() (embedding_benchmark.KNNClassifier method) (embedding_benchmark.MetricCallback method) on_validation_epoch_end() (embedding_benchmark.MetricModule method) on_validation_epoch_start() (embedding_benchmark.KNNClassifier method) onehot_to_rgb() (in module skself.utils) P pairing_mode (skself.data.images_from_directory.DatasetBuilder attribute) parser (in module embedding_benchmark) peek (skself.data.images_from_directory.DatasetBuilder attribute) peek_dataset() (skself.data.images_from_directory.DatasetBuilder method) pop_channel() (in module skself.partial_annotations.lazy_model) precision (embedding_benchmark.Config attribute) process_deviation (skself.data.images_from_directory.DatasetBuilder attribute) profile (embedding_benchmark.Config attribute) R random_slice() (in module skself.utils) repeat (skself.data.images_from_directory.DatasetBuilder attribute) resize_transform (embedding_benchmark.BaselineMethod attribute) rgb_to_onehot() (in module skself.utils) run() (embedding_benchmark.Baseline method) run_baseline_method() (embedding_benchmark.BaselineMethod method) S sample_more_likely_in_the_middle() (in module skself.utils) seed (skself.data.images_from_directory.DatasetBuilder attribute) segmentation_dataset_from_folders() (in module skself.data) setUp() (skself.test.TestLazySegmentationModel method) shuffle (skself.data.images_from_directory.DatasetBuilder attribute) skip_embedding_training (embedding_benchmark.BaselineMethod attribute) (embedding_benchmark.Config attribute) (embedding_benchmark.SwinL384Baseline attribute) skip_knn_eval (embedding_benchmark.Config attribute) skip_linear_eval (embedding_benchmark.Config attribute) skself module skself.data module skself.data.images_from_directory module skself.embedding_training module skself.gptano module skself.partial_annotations module skself.partial_annotations.lazy_model module skself.test module skself.utils module subset (skself.data.images_from_directory.DatasetBuilder attribute) SwinL384 (class in embedding_benchmark) SwinL384Baseline (class in embedding_benchmark) T test_model_fit() (skself.test.TestLazySegmentationModel method) test_model_fit_andevaluate() (skself.test.TestLazySegmentationModel method) test_run (embedding_benchmark.Config attribute) TestLazySegmentationModel (class in skself.test) timing_decorator() (in module embedding_benchmark) train() (embedding_benchmark.BaselineMethod method) train_metrics (embedding_benchmark.MetricCallback attribute), [1] training_step() (embedding_benchmark.KNNClassifier method) (embedding_benchmark.LinearClassifier method) U underscore_attrs_are_private (skself.data.images_from_directory.DatasetBuilder.Config attribute) update_state() (skself.partial_annotations.lazy_model.LazyMetricWrapper method) update_train_metrics() (embedding_benchmark.MetricModule method) update_val_metrics() (embedding_benchmark.MetricModule method) V val_metrics (embedding_benchmark.MetricCallback attribute), [1] val_transform (embedding_benchmark.BaselineMethod attribute) validate_images() (in module skself.utils) validation_split (skself.data.images_from_directory.DatasetBuilder attribute) validation_step() (embedding_benchmark.KNNClassifier method) (embedding_benchmark.LinearClassifier method) ViT_B_16Baseline (class in embedding_benchmark) ViT_B_16Classifier (class in embedding_benchmark) ViTEmbedding (class in embedding_benchmark) W width (skself.data.images_from_directory.DatasetBuilder attribute)
