sleap.nn.model¶
This module defines the main SLEAP model class for defining a trainable model.
This is a higher level wrapper around tf.keras.Model that holds all the configuration parameters required to construct the actual model. This allows for easy querying of the model configuration without actually instantiating the model itself.
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class
sleap.nn.model.
Model
(backbone: Architecture, heads, keras_model: Optional[tensorflow.python.keras.engine.training.Model] = None)[source]¶ SLEAP model that describes an architecture and output types.
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backbone
¶ An Architecture class that provides methods for building a tf.keras.Model given an input.
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keras_model
¶ The current tf.keras.Model instance if one has been created.
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classmethod
from_config
(config: sleap.nn.config.model.ModelConfig, skeleton: Optional[sleap.skeleton.Skeleton] = None, update_config: bool = False) → sleap.nn.model.Model[source]¶ Create a SLEAP model from configurations.
- Parameters
config – The configurations as a ModelConfig instance.
skeleton – A sleap.Skeleton to use if not provided in the config.
- Returns
An instance of Model built with the specified configurations.
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make_model
(input_shape: Tuple[int, int, int]) → tensorflow.python.keras.engine.training.Model[source]¶ Create a trainable model from the configuration.
- Parameters
input_shape – Tuple of (height, width, channels) specifying the shape of the inputs before preprocessing.
- Returns
An instantiated tf.keras.Model.
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property
maximum_stride
¶ Return the maximum stride of the model backbone.
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