本文整理匯總了Python中average_precision_calculator.AveragePrecisionCalculator方法的典型用法代碼示例。如果您正苦於以下問題：Python average_precision_calculator.AveragePrecisionCalculator方法的具體用法？Python average_precision_calculator.AveragePrecisionCalculator怎麽用？Python average_precision_calculator.AveragePrecisionCalculator使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類average_precision_calculator的用法示例。
在下文中一共展示了average_precision_calculator.AveragePrecisionCalculator方法的3個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: calculate_gap
# 需要導入模塊: import average_precision_calculator [as 別名]
# 或者: from average_precision_calculator import AveragePrecisionCalculator [as 別名]
def calculate_gap(predictions, actuals, top_k=20):
"""Performs a local (numpy) calculation of the global average precision.
Only the top_k predictions are taken for each of the videos.
Args:
predictions: Matrix containing the outputs of the model.
Dimensions are 'batch' x 'num_classes'.
actuals: Matrix containing the ground truth labels.
Dimensions are 'batch' x 'num_classes'.
top_k: How many predictions to use per video.
Returns:
float: The global average precision.
"""
gap_calculator = ap_calculator.AveragePrecisionCalculator()
sparse_predictions, sparse_labels, num_positives = top_k_by_class(predictions, actuals, top_k)
gap_calculator.accumulate(flatten(sparse_predictions), flatten(sparse_labels), sum(num_positives))
return gap_calculator.peek_ap_at_n() 示例2: __init__
# 需要導入模塊: import average_precision_calculator [as 別名]
# 或者: from average_precision_calculator import AveragePrecisionCalculator [as 別名]
def __init__(self, num_class, top_k):
"""Construct an EvaluationMetrics object to store the evaluation metrics.
Args:
num_class: A positive integer specifying the number of classes.
top_k: A positive integer specifying how many predictions are considered per video.
Raises:
ValueError: An error occurred when MeanAveragePrecisionCalculator cannot
not be constructed.
"""
self.sum_hit_at_one = 0.0
self.sum_perr = 0.0
self.sum_loss = 0.0
self.map_calculator = map_calculator.MeanAveragePrecisionCalculator(num_class)
self.global_ap_calculator = ap_calculator.AveragePrecisionCalculator()
self.top_k = top_k
self.num_examples = 0 示例3: __init__
# 需要導入模塊: import average_precision_calculator [as 別名]
# 或者: from average_precision_calculator import AveragePrecisionCalculator [as 別名]
def __init__(self, num_class):
"""Construct a calculator to calculate the (macro) average precision.
Args:
num_class: A positive Integer specifying the number of classes.
top_n_array: A list of positive integers specifying the top n for each
class. The top n in each class will be used to calculate its average
precision at n.
The size of the array must be num_class.
Raises:
ValueError: An error occurred when num_class is not a positive integer;
or the top_n_array is not a list of positive integers.
"""
if not isinstance(num_class, int) or num_class <= 1:
raise ValueError("num_class must be a positive integer.")
self._ap_calculators = [] # member of AveragePrecisionCalculator
self._num_class = num_class # total number of classes
for i in range(num_class):
self._ap_calculators.append(
average_precision_calculator.AveragePrecisionCalculator())