如何用训练好的模型绘制精确度图

import numpy as np
import matplotlib.pyplot as plt

# 加载模型和数据
model = load_model('trained_model.h5')
test_data = load_test_data()

# 进行预测
predictions = model.predict(test_data)

# 计算精确度
true_labels = get_true_labels(test_data)
accuracy = np.sum(predictions == true_labels) / len(true_labels)

# 绘制精确度图
thresholds = np.linspace(0, 1, num=100)  # 设置阈值范围
accuracies = []
for threshold in thresholds:
    binary_predictions = (predictions > threshold).astype(int)
    accuracy = np.sum(binary_predictions == true_labels) / len(true_labels)
    accuracies.append(accuracy)

plt.plot(thresholds, accuracies)
plt.xlabel('Threshold')
plt.ylabel('Accuracy')
plt.title('Accuracy vs. Threshold')
plt.show()