Average Drop and Average Increase Metrics¶
- class image_segmentation.class_activation_maps.average.AveragesCam(model: tensorflow.keras.Model, inputs: tensorflow.Tensor)[source]¶
Set of metrics to measure influence of CAM in the ouput model score.
- model¶
Already trained model.
- Type:
tensorflow.keras.Model
- inputs¶
Instances to predict scores.
- Type:
tf.Tensor
- __init__(model: tensorflow.keras.Model, inputs: tensorflow.Tensor) None[source]¶
- Parameters:
model – Already trained model.
inputs – Instances to predict scores.
- _get_scores(cams: tensorflow.Tensor, score_function: Callable) tuple[source]¶
Calculate scores over inputs and masked inputs with cams.
- Parameters:
cams – Normalized ouput of CAM methods using the model and the inputs
score_function – Same score function used to calculate the CAMs in tf-keras-vis
- Returns:
The fisrt is the scores of the model over the inputs and the second is the scores over the masked input with the cams.
- Return type:
tuple
- average_drop(cams: tensorflow.Tensor, score_function: Callable, return_vector: bool = False) float[source]¶
Calculate average drop.
- Parameters:
cams – Normalized ouput of CAM methods using the model and the inputs
score_function – Same score function used to calculate the CAMs in tf-keras-vis
- Returns:
average drop
- Return type:
float
Note
The equation used is
\[100\frac{1}{N} \sum_{i=1}^N \frac{max(0,Y_i^c - O_i^c)}{Y_i^c}\]
- average_increase(cams: tensorflow.Tensor, score_function: Callable, return_vector: bool = False) float[source]¶
Calculate average increase.
- Parameters:
cams – Normalized ouput of CAM methods using the model and the inputs
score_function – Same score function used to calculate the CAMs in tf-keras-vis
- Returns:
average increase
- Return type:
float
Note
The equation used is
\[100\frac{1}{N} \sum_{i=1}^N Sign(Y_i^c < O_i^c)\]