---
license: cc-by-nc-4.0
datasets:
- Continual-Mega/Continual-MEGA-Benchmark
---


# 🧠 Continual-MEGA: A Large-scale Benchmark for Generalizable Continual Anomaly Detection

This repository contains the evaluation code for the **Continual-Mega** benchmark.

We provide the checkpoint files of the proposed model along with the evaluation code for the Continual-Mega benchmark.

The training code will be made publicly available at a later date.

🔗 **Codebase**: [Continual-Mega/Continual-Mega](https://github.com/Continual-Mega/Continual-Mega)

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## 🚀 Overview

Continual-MEGA introduces a realistic and large-scale benchmark for **continual anomaly detection** that emphasizes generalizability across domains and tasks.

The benchmark features:

- ✅ Diverse anomaly types across domains
- 🔁 Class-incremental continual learning setup
- 📈 A large-scale evaluation protocol surpassing previous benchmarks

This repository hosts pretrained **model checkpoints** used in various scenarios defined in the benchmark.

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## 📦 Available Checkpoints

| Model Name                            | Scenario   | Task                    | Description                                              |
|---------------------------------------|------------|-------------------------|----------------------------------------------------------|
| `scenario2/prompt_maker`              | Scenario 2 | Base                    | Prompt maker trained on Scenario 2 base classes          |
| `scenario2/adapters_base`             | Scenario 2 | Base                    | Adapter trained on Scenario 2 base classes         |
| `scenario2/30classes/adapters_task1`  | Scenario 2 | Task 1 (30 classes)     | Adapter trained on Task 1 (30 classes) in Scenario 2     |
| `scenario2/30classes/adapters_task2`  | Scenario 2 | Task 2 (30 classes)     | Adapter trained on Task 2 (30 classes) in Scenario 2     |
| *(More to come)*                      | –          | –                       | –                                                        |


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## 🛠 Usage Example

### Continual Setting Evaluation
``` 
sh eval_continual.sh
``` 
### Zero-Shot Evaluation
``` 
sh eval_zero.s