def build_objectives(interface_layers): obj_weighted = WeightedSegmentationCrossEntropyObjective( classweights=[10000, 1], input_layer=interface_layers["outputs"]["predicted_segmentation"], target_name="luna:gaussian", ) obj_jaccard = JaccardIndexObjective( smooth=1e-5, input_layer=interface_layers["outputs"]["predicted_segmentation"], target_name="luna:gaussian", ) obj_dice = SoerensonDiceCoefficientObjective( smooth=1e-5, input_layer=interface_layers["outputs"]["predicted_segmentation"], target_name="luna:gaussian", ) obj_precision = PrecisionObjective( smooth=1e-5, input_layer=interface_layers["outputs"]["predicted_segmentation"], target_name="luna:gaussian", ) obj_recall = RecallObjective( smooth=1e-5, input_layer=interface_layers["outputs"]["predicted_segmentation"], target_name="luna:gaussian", ) obj_custom = ClippedFObjective( smooth=1e-5, recall_weight=1.0001, precision_weight=3.0, input_layer=interface_layers["outputs"]["predicted_segmentation"], target_name="luna:gaussian", ) return { "train": { "objective": obj_custom, "jaccard": obj_jaccard, "weighted": obj_weighted, "Dice": obj_dice, "precision": obj_precision, "recall": obj_recall, }, "validate": { "objective": obj_custom, "jaccard": obj_jaccard, "weighted": obj_weighted, "Dice": obj_dice, "precision": obj_precision, "recall": obj_recall, } }
def build_objectives(interface_layers): obj = WeightedSegmentationCrossEntropyObjective( classweights=[3000, 1], input_layer=interface_layers["outputs"]["predicted_segmentation"], target_name="luna:segmentation", ) return { "train": { "objective": obj, }, "validate": { "objective": obj, } }
def build_objectives(interface_layers): obj_weighted = WeightedSegmentationCrossEntropyObjective( classweights=[10000, 1], input_layers=interface_layers["outputs"], target_name="luna", ) obj_jaccard = JaccardIndexObjective( smooth=1e-5, input_layers=interface_layers["outputs"], target_name="luna", ) obj_dice = SoerensonDiceCoefficientObjective( smooth=1., input_layers=interface_layers["outputs"], target_name="luna", ) obj_precision = PrecisionObjective( smooth=1., input_layers=interface_layers["outputs"], target_name="luna", ) obj_recall = RecallObjective( smooth=1., input_layers=interface_layers["outputs"], target_name="luna", ) return { "train": { "objective": obj_jaccard, "weighted": obj_weighted, "Dice": obj_dice, "precision": obj_precision, "recall": obj_recall, }, "validate": { "objective": obj_jaccard, "weighted": obj_weighted, "Dice": obj_dice, "precision": obj_precision, "recall": obj_recall, } }