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import json |
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import numpy as np |
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def denormalize_func(normalized_tensor, min_val=0, max_val=200): |
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tensor = (normalized_tensor + 1) / 2 |
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tensor = tensor * (max_val - min_val) + min_val |
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return tensor |
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with open('action_val.json', 'r') as file: |
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data = json.load(file) |
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steering_errors = [] |
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speed_errors = [] |
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for scene_data in data: |
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action_pred = scene_data["action_pred"] |
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action_gt = scene_data["action_gt"] |
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min_length = min(len(action_pred), len(action_gt)) |
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for i in range(min_length): |
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pred_steering, pred_speed = action_pred[i] |
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gt_steering, gt_speed = action_gt[i] |
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steering_error = abs(pred_steering - gt_steering) |
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speed_error = abs(pred_speed - gt_speed) |
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steering_errors.append(steering_error) |
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speed_errors.append(speed_error) |
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mean_steering_error = np.mean(steering_errors) |
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mean_speed_error = np.mean(speed_errors) |
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print("平均转向角L1误差:", mean_steering_error) |
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print("平均速度L1误差:", mean_speed_error) |
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