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@@ -137,7 +137,6 @@ def batch_predict_images(session, image_dir, target_class, batch_size=10, pytorc
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predicted_class = np.argmax(outputs[0][j]) # 假设输出是每类的概率
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results[image_file] = predicted_class
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total_predictions += 1
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- print(f"Image: {image_file}, Predicted: {predicted_class}, Target: {target_class}")
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# 比较预测结果与目标分类
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if predicted_class == target_class:
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@@ -145,6 +144,7 @@ def batch_predict_images(session, image_dir, target_class, batch_size=10, pytorc
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# 计算准确率
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accuracy = correct_predictions / total_predictions if total_predictions > 0 else 0
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+ print(f"Processed {len(image_files)} images, accuracy: {accuracy * 100:.2f}%")
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return accuracy
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