Python calculate_accuracy示例

示例#1

文件： train.py 项目： Joker316701882/Additive-Margin-Softmax

def evaluate_with_no_cv(emb_array, actual_issame):
    thresholds = np.arange(0, 4, 0.01)
    embeddings1 = emb_array[0::2]
    embeddings2 = emb_array[1::2]

    nrof_thresholds = len(thresholds)
    accuracys = np.zeros((nrof_thresholds))
    
    diff = np.subtract(embeddings1, embeddings2)
    dist = np.sum(np.square(diff),1)

    for threshold_idx, threshold in enumerate(thresholds):
        _, _, accuracys[threshold_idx] = facenet.calculate_accuracy(threshold, dist, actual_issame)

    best_acc = np.max(accuracys)
    best_thre = thresholds[np.argmax(accuracys)]
    return best_acc,best_thre

示例#2

def evaluate_with_no_cv(emb_array, actual_issame):
    thresholds = np.arange(0, 4, 0.01)
    embeddings1 = emb_array[0::2]
    embeddings2 = emb_array[1::2]

    nrof_thresholds = len(thresholds)
    accuracys = np.zeros((nrof_thresholds))
    
    diff = np.subtract(embeddings1, embeddings2)
    dist = np.sum(np.square(diff),1)

    for threshold_idx, threshold in enumerate(thresholds):
        _, _, accuracys[threshold_idx] = facenet.calculate_accuracy(threshold, dist, actual_issame)

    best_acc = np.max(accuracys)
    best_thre = thresholds[np.argmax(accuracys)]
    return best_acc,best_thre