ImageModelSettingsObjectDetection |
ImageInstanceSegmentation.modelSettings() |
Get the modelSettings property: Settings used for training the model.
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ImageModelSettingsObjectDetection |
ImageObjectDetection.modelSettings() |
Get the modelSettings property: Settings used for training the model.
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ImageModelSettingsObjectDetection |
ImageObjectDetectionBase.modelSettings() |
Get the modelSettings property: Settings used for training the model.
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ImageModelSettingsObjectDetection |
ImageModelSettingsObjectDetection.withAdvancedSettings(String advancedSettings) |
Set the advancedSettings property: Settings for advanced scenarios.
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ImageModelSettingsObjectDetection |
ImageModelSettingsObjectDetection.withAmsGradient(Boolean amsGradient) |
Set the amsGradient property: Enable AMSGrad when optimizer is 'adam' or 'adamw'.
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ImageModelSettingsObjectDetection |
ImageModelSettingsObjectDetection.withAugmentations(String augmentations) |
Set the augmentations property: Settings for using Augmentations.
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ImageModelSettingsObjectDetection |
ImageModelSettingsObjectDetection.withBeta1(Float beta1) |
Set the beta1 property: Value of 'beta1' when optimizer is 'adam' or 'adamw'.
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ImageModelSettingsObjectDetection |
ImageModelSettingsObjectDetection.withBeta2(Float beta2) |
Set the beta2 property: Value of 'beta2' when optimizer is 'adam' or 'adamw'.
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ImageModelSettingsObjectDetection |
ImageModelSettingsObjectDetection.withBoxDetectionsPerImage(Integer boxDetectionsPerImage) |
Set the boxDetectionsPerImage property: Maximum number of detections per image, for all classes.
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ImageModelSettingsObjectDetection |
ImageModelSettingsObjectDetection.withBoxScoreThreshold(Float boxScoreThreshold) |
Set the boxScoreThreshold property: During inference, only return proposals with a classification score greater
than BoxScoreThreshold.
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ImageModelSettingsObjectDetection |
ImageModelSettingsObjectDetection.withCheckpointDatasetId(String checkpointDatasetId) |
Set the checkpointDatasetId property: FileDataset id for pretrained checkpoint(s) for incremental training.
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ImageModelSettingsObjectDetection |
ImageModelSettingsObjectDetection.withCheckpointFilename(String checkpointFilename) |
Set the checkpointFilename property: The pretrained checkpoint filename in FileDataset for incremental training.
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ImageModelSettingsObjectDetection |
ImageModelSettingsObjectDetection.withCheckpointFrequency(Integer checkpointFrequency) |
Set the checkpointFrequency property: Frequency to store model checkpoints.
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ImageModelSettingsObjectDetection |
ImageModelSettingsObjectDetection.withCheckpointRunId(String checkpointRunId) |
Set the checkpointRunId property: The id of a previous run that has a pretrained checkpoint for incremental
training.
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ImageModelSettingsObjectDetection |
ImageModelSettingsObjectDetection.withDistributed(Boolean distributed) |
Set the distributed property: Whether to use distributed training.
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ImageModelSettingsObjectDetection |
ImageModelSettingsObjectDetection.withEarlyStopping(Boolean earlyStopping) |
Set the earlyStopping property: Enable early stopping logic during training.
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ImageModelSettingsObjectDetection |
ImageModelSettingsObjectDetection.withEarlyStoppingDelay(Integer earlyStoppingDelay) |
Set the earlyStoppingDelay property: Minimum number of epochs or validation evaluations to wait before primary
metric improvement is tracked for early stopping.
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ImageModelSettingsObjectDetection |
ImageModelSettingsObjectDetection.withEarlyStoppingPatience(Integer earlyStoppingPatience) |
Set the earlyStoppingPatience property: Minimum number of epochs or validation evaluations with no primary metric
improvement before the run is stopped.
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ImageModelSettingsObjectDetection |
ImageModelSettingsObjectDetection.withEnableOnnxNormalization(Boolean enableOnnxNormalization) |
Set the enableOnnxNormalization property: Enable normalization when exporting ONNX model.
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ImageModelSettingsObjectDetection |
ImageModelSettingsObjectDetection.withEvaluationFrequency(Integer evaluationFrequency) |
Set the evaluationFrequency property: Frequency to evaluate validation dataset to get metric scores.
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ImageModelSettingsObjectDetection |
ImageModelSettingsObjectDetection.withGradientAccumulationStep(Integer gradientAccumulationStep) |
Set the gradientAccumulationStep property: Gradient accumulation means running a configured number of
"GradAccumulationStep"\ steps without updating the model weights while accumulating the gradients of those steps,
and then using the accumulated gradients to compute the weight updates.
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ImageModelSettingsObjectDetection |
ImageModelSettingsObjectDetection.withImageSize(Integer imageSize) |
Set the imageSize property: Image size for train and validation.
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ImageModelSettingsObjectDetection |
ImageModelSettingsObjectDetection.withLayersToFreeze(Integer layersToFreeze) |
Set the layersToFreeze property: Number of layers to freeze for the model.
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ImageModelSettingsObjectDetection |
ImageModelSettingsObjectDetection.withLearningRate(Float learningRate) |
Set the learningRate property: Initial learning rate.
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ImageModelSettingsObjectDetection |
ImageModelSettingsObjectDetection.withLearningRateScheduler(LearningRateScheduler learningRateScheduler) |
Set the learningRateScheduler property: Type of learning rate scheduler.
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ImageModelSettingsObjectDetection |
ImageModelSettingsObjectDetection.withMaxSize(Integer maxSize) |
Set the maxSize property: Maximum size of the image to be rescaled before feeding it to the backbone.
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ImageModelSettingsObjectDetection |
ImageModelSettingsObjectDetection.withMinSize(Integer minSize) |
Set the minSize property: Minimum size of the image to be rescaled before feeding it to the backbone.
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ImageModelSettingsObjectDetection |
ImageModelSettingsObjectDetection.withModelName(String modelName) |
Set the modelName property: Name of the model to use for training.
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ImageModelSettingsObjectDetection |
ImageModelSettingsObjectDetection.withModelSize(ModelSize modelSize) |
Set the modelSize property: Model size.
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ImageModelSettingsObjectDetection |
ImageModelSettingsObjectDetection.withMomentum(Float momentum) |
Set the momentum property: Value of momentum when optimizer is 'sgd'.
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ImageModelSettingsObjectDetection |
ImageModelSettingsObjectDetection.withMultiScale(Boolean multiScale) |
Set the multiScale property: Enable multi-scale image by varying image size by +/- 50%.
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ImageModelSettingsObjectDetection |
ImageModelSettingsObjectDetection.withNesterov(Boolean nesterov) |
Set the nesterov property: Enable nesterov when optimizer is 'sgd'.
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ImageModelSettingsObjectDetection |
ImageModelSettingsObjectDetection.withNmsIouThreshold(Float nmsIouThreshold) |
Set the nmsIouThreshold property: IOU threshold used during inference in NMS post processing.
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ImageModelSettingsObjectDetection |
ImageModelSettingsObjectDetection.withNumberOfEpochs(Integer numberOfEpochs) |
Set the numberOfEpochs property: Number of training epochs.
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ImageModelSettingsObjectDetection |
ImageModelSettingsObjectDetection.withNumberOfWorkers(Integer numberOfWorkers) |
Set the numberOfWorkers property: Number of data loader workers.
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ImageModelSettingsObjectDetection |
ImageModelSettingsObjectDetection.withOptimizer(StochasticOptimizer optimizer) |
Set the optimizer property: Type of optimizer.
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ImageModelSettingsObjectDetection |
ImageModelSettingsObjectDetection.withRandomSeed(Integer randomSeed) |
Set the randomSeed property: Random seed to be used when using deterministic training.
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ImageModelSettingsObjectDetection |
ImageModelSettingsObjectDetection.withSplitRatio(Float splitRatio) |
Set the splitRatio property: If validation data is not defined, this specifies the split ratio for splitting
train data into random train and validation subsets.
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ImageModelSettingsObjectDetection |
ImageModelSettingsObjectDetection.withStepLRGamma(Float stepLRGamma) |
Set the stepLRGamma property: Value of gamma when learning rate scheduler is 'step'.
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ImageModelSettingsObjectDetection |
ImageModelSettingsObjectDetection.withStepLRStepSize(Integer stepLRStepSize) |
Set the stepLRStepSize property: Value of step size when learning rate scheduler is 'step'.
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ImageModelSettingsObjectDetection |
ImageModelSettingsObjectDetection.withTileGridSize(String tileGridSize) |
Set the tileGridSize property: The grid size to use for tiling each image.
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ImageModelSettingsObjectDetection |
ImageModelSettingsObjectDetection.withTileOverlapRatio(Float tileOverlapRatio) |
Set the tileOverlapRatio property: Overlap ratio between adjacent tiles in each dimension.
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ImageModelSettingsObjectDetection |
ImageModelSettingsObjectDetection.withTilePredictionsNmsThreshold(Float tilePredictionsNmsThreshold) |
Set the tilePredictionsNmsThreshold property: The IOU threshold to use to perform NMS while merging predictions
from tiles and image.
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ImageModelSettingsObjectDetection |
ImageModelSettingsObjectDetection.withTrainingBatchSize(Integer trainingBatchSize) |
Set the trainingBatchSize property: Training batch size.
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ImageModelSettingsObjectDetection |
ImageModelSettingsObjectDetection.withValidationBatchSize(Integer validationBatchSize) |
Set the validationBatchSize property: Validation batch size.
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ImageModelSettingsObjectDetection |
ImageModelSettingsObjectDetection.withValidationIouThreshold(Float validationIouThreshold) |
Set the validationIouThreshold property: IOU threshold to use when computing validation metric.
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ImageModelSettingsObjectDetection |
ImageModelSettingsObjectDetection.withValidationMetricType(ValidationMetricType validationMetricType) |
Set the validationMetricType property: Metric computation method to use for validation metrics.
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ImageModelSettingsObjectDetection |
ImageModelSettingsObjectDetection.withWarmupCosineLRCycles(Float warmupCosineLRCycles) |
Set the warmupCosineLRCycles property: Value of cosine cycle when learning rate scheduler is 'warmup_cosine'.
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ImageModelSettingsObjectDetection |
ImageModelSettingsObjectDetection.withWarmupCosineLRWarmupEpochs(Integer warmupCosineLRWarmupEpochs) |
Set the warmupCosineLRWarmupEpochs property: Value of warmup epochs when learning rate scheduler is
'warmup_cosine'.
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ImageModelSettingsObjectDetection |
ImageModelSettingsObjectDetection.withWeightDecay(Float weightDecay) |
Set the weightDecay property: Value of weight decay when optimizer is 'sgd', 'adam', or 'adamw'.
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