Point the anomaly data node at the canonical AnomalyDataNode

dinomaly_bedding_all6.yaml

@@ -1,105 +1,105 @@
-nodes:
-- name: LentilsAnomalyDataNode
-  class_name: cuvis_ai.node.data.LentilsAnomalyDataNode
-  hparams:
-    normal_class_ids:
-    - 0
-    anomaly_class_ids: null
-- name: MinMaxNormalizer
-  class_name: cuvis_ai.node.normalization.MinMaxNormalizer
-  hparams:
-    eps: 1.0e-06
-    use_running_stats: true
-    max_initialization_frames: null
-- name: hyperspectral_selector
-  class_name: cuvis_ai.node.channel_selector.FixedWavelengthSelector
-  hparams:
-    target_wavelengths:
-    - 625.0
-    - 550.0
-    - 450.0
-    - 1450.0
-    - 1200.0
-    - 1050.0
-    normalize_output: false
-    norm_mode: per_frame
-- name: dinomaly_detector
-  class_name: cuvis_ai_dinomaly.node.dinomaly_detector.DinomalyDetector
-  hparams:
-    encoder_name: dinov2reg_vit_base_14
-    bottleneck_dropout: 0.2
-    decoder_depth: 8
-    target_layers: null
-    fuse_layer_encoder: null
-    fuse_layer_decoder: null
-    remove_class_token: false
-    image_size: 672
-    crop_size: 672
-    use_center_crop: false
-    input_channels: 6
-- name: dinomaly_train_loss
-  class_name: cuvis_ai_dinomaly.node.dinomaly_train_loss_bridge.DinomalyTrainLossBridge
-  hparams:
-    weight: 1.0
-- name: decider
-  class_name: cuvis_ai.node.deciders.binary_decider.QuantileBinaryDecider
-  hparams:
-    quantile: 0.995
-    reduce_dims: null
-    threshold: 0.5
-- name: metrics_anomaly
-  class_name: cuvis_ai.node.metrics.AnomalyDetectionMetrics
-  hparams:
-    execution_stages: null
-    ap_thresholds: 200
-- name: TensorBoardMonitorNode
-  class_name: cuvis_ai.node.monitor.TensorBoardMonitorNode
-  hparams:
-    output_dir: /mnt/data/cuvis_ai_outputs/dinomaly_bedding_all6_highres_30ep/tensorboard
-    run_name: dinomaly_bedding_all6
-    comment: ''
-    flush_secs: 120
-- name: metrics_auroc
-  class_name: cuvis_ai_dinomaly.node.auroc_metrics.AnomalyAUROCMetrics
-  hparams: {}
-connections:
-- source: LentilsAnomalyDataNode.outputs.cube
-  target: MinMaxNormalizer.inputs.data
-- source: LentilsAnomalyDataNode.outputs.wavelengths
-  target: hyperspectral_selector.inputs.wavelengths
-- source: LentilsAnomalyDataNode.outputs.mask
-  target: metrics_anomaly.inputs.targets
-- source: LentilsAnomalyDataNode.outputs.mask
-  target: metrics_auroc.inputs.targets
-- source: MinMaxNormalizer.outputs.normalized
-  target: hyperspectral_selector.inputs.cube
-- source: hyperspectral_selector.outputs.rgb_image
-  target: dinomaly_detector.inputs.rgb_image
-- source: dinomaly_detector.outputs.training_loss
-  target: dinomaly_train_loss.inputs.raw_loss
-- source: dinomaly_detector.outputs.scores
-  target: decider.inputs.logits
-- source: dinomaly_detector.outputs.scores
-  target: metrics_anomaly.inputs.logits
-- source: dinomaly_detector.outputs.scores
-  target: metrics_auroc.inputs.scores
-- source: dinomaly_detector.outputs.anomaly_score
-  target: metrics_auroc.inputs.anomaly_score
-- source: decider.outputs.decisions
-  target: metrics_anomaly.inputs.decisions
-- source: metrics_anomaly.outputs.metrics
-  target: TensorBoardMonitorNode.inputs.metrics
-metadata:
-  name: dinomaly_bedding_all6
-  description: Dinomaly (Anomalib) on bedding hyperspectral NPZ, all-6-band selector
-    (625/550/450/1450/1200/1050 nm), input_channels=6 with duplicate-and-halve patch-embed
-    inflation.
-  created: ''
-  tags:
-  - dinomaly
-  - anomalib
-  - bedding
-  - all6
-  - hyperspectral
-  author: cuvis.ai
-  cuvis_ai_version: 0.1.0
+nodes:
+- name: anomaly_data
+  class_name: cuvis_ai.node.data.AnomalyDataNode
+  hparams:
+    normal_class_ids:
+    - 0
+    anomaly_class_ids: null
+- name: MinMaxNormalizer
+  class_name: cuvis_ai.node.normalization.MinMaxNormalizer
+  hparams:
+    eps: 1.0e-06
+    use_running_stats: true
+    max_initialization_frames: null
+- name: hyperspectral_selector
+  class_name: cuvis_ai.node.channel_selector.FixedWavelengthSelector
+  hparams:
+    target_wavelengths:
+    - 625.0
+    - 550.0
+    - 450.0
+    - 1450.0
+    - 1200.0
+    - 1050.0
+    normalize_output: false
+    norm_mode: per_frame
+- name: dinomaly_detector
+  class_name: cuvis_ai_dinomaly.node.dinomaly_detector.DinomalyDetector
+  hparams:
+    encoder_name: dinov2reg_vit_base_14
+    bottleneck_dropout: 0.2
+    decoder_depth: 8
+    target_layers: null
+    fuse_layer_encoder: null
+    fuse_layer_decoder: null
+    remove_class_token: false
+    image_size: 672
+    crop_size: 672
+    use_center_crop: false
+    input_channels: 6
+- name: dinomaly_train_loss
+  class_name: cuvis_ai_dinomaly.node.dinomaly_train_loss_bridge.DinomalyTrainLossBridge
+  hparams:
+    weight: 1.0
+- name: decider
+  class_name: cuvis_ai.node.deciders.binary_decider.QuantileBinaryDecider
+  hparams:
+    quantile: 0.995
+    reduce_dims: null
+    threshold: 0.5
+- name: metrics_anomaly
+  class_name: cuvis_ai.node.metrics.AnomalyDetectionMetrics
+  hparams:
+    execution_stages: null
+    ap_thresholds: 200
+- name: TensorBoardMonitorNode
+  class_name: cuvis_ai.node.monitor.TensorBoardMonitorNode
+  hparams:
+    output_dir: /mnt/data/cuvis_ai_outputs/dinomaly_bedding_all6_highres_30ep/tensorboard
+    run_name: dinomaly_bedding_all6
+    comment: ''
+    flush_secs: 120
+- name: metrics_auroc
+  class_name: cuvis_ai_dinomaly.node.auroc_metrics.AnomalyAUROCMetrics
+  hparams: {}
+connections:
+- source: anomaly_data.outputs.cube
+  target: MinMaxNormalizer.inputs.data
+- source: anomaly_data.outputs.wavelengths
+  target: hyperspectral_selector.inputs.wavelengths
+- source: anomaly_data.outputs.mask
+  target: metrics_anomaly.inputs.targets
+- source: anomaly_data.outputs.mask
+  target: metrics_auroc.inputs.targets
+- source: MinMaxNormalizer.outputs.normalized
+  target: hyperspectral_selector.inputs.cube
+- source: hyperspectral_selector.outputs.rgb_image
+  target: dinomaly_detector.inputs.rgb_image
+- source: dinomaly_detector.outputs.training_loss
+  target: dinomaly_train_loss.inputs.raw_loss
+- source: dinomaly_detector.outputs.scores
+  target: decider.inputs.logits
+- source: dinomaly_detector.outputs.scores
+  target: metrics_anomaly.inputs.logits
+- source: dinomaly_detector.outputs.scores
+  target: metrics_auroc.inputs.scores
+- source: dinomaly_detector.outputs.anomaly_score
+  target: metrics_auroc.inputs.anomaly_score
+- source: decider.outputs.decisions
+  target: metrics_anomaly.inputs.decisions
+- source: metrics_anomaly.outputs.metrics
+  target: TensorBoardMonitorNode.inputs.metrics
+metadata:
+  name: dinomaly_bedding_all6
+  description: Dinomaly (Anomalib) on bedding hyperspectral NPZ, all-6-band selector
+    (625/550/450/1450/1200/1050 nm), input_channels=6 with duplicate-and-halve patch-embed
+    inflation.
+  created: ''
+  tags:
+  - dinomaly
+  - anomalib
+  - bedding
+  - all6
+  - hyperspectral
+  author: cuvis.ai
+  cuvis_ai_version: 0.1.0