| ---
|
| license: apache-2.0
|
| base_model: Qwen/Qwen2.5-VL-7B-Instruct
|
| datasets:
|
| - Huang-yating/SID_Set
|
| language:
|
| - en
|
| library_name: transformers
|
| pipeline_tag: image-classification
|
| tags:
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| - image-forensics
|
| - image-manipulation-localization
|
| - multi-agent
|
| - qwen2.5-vl
|
| ---
|
|
|
| # MADL model weights
|
|
|
| This repository is the weight companion for **MADL: Towards Dependable Image
|
| Forgery Detection via Multi-Agent Forensic Reasoning**. The executable code,
|
| configuration files, and evaluation scripts are distributed in the companion
|
| [GitHub code repository](https://github.com/shannima/MADL).
|
|
|
| Model repository: [moindy/MADL](https://huggingface.co/moindy/MADL).
|
|
|
| MADL produces one of three image-level labels—`real`, `synthetic`, or
|
| `tampered`—and returns a binary localization mask only for locally tampered
|
| images. The release contains the trainable components developed for MADL; it
|
| does not redistribute the Qwen base model or SAM ViT-H.
|
|
|
| ## Files
|
|
|
| | Directory | Component | Purpose |
|
| |---|---|---|
|
| | `agent_a_qwen_lora/` | Agent A LoRA adapter | Adapts Qwen2.5-VL-7B-Instruct to three-class semantic verification and region proposals. |
|
| | `agent_b_dualstream/` | Agent B dual-stream checkpoint | RGB/SRM ConvNeXt-Tiny classifier and continuous manipulation heatmap. |
|
| | `agent_b_visual_ranker/` | Agent B visual-ranker checkpoint | Selects a final SAM candidate using RGB, mask, heatmap, and geometry evidence. |
|
| | `MANIFEST.json` | Integrity manifest | Records the byte size and SHA-256 of every released model artifact. |
|
|
|
| The dual-stream release checkpoint contains only the model state, architecture,
|
| class names, and a compact training summary. Optimizer state and local training
|
| paths were intentionally removed. The visual-ranker checkpoint uses the
|
| strict four-field runtime schema required by the companion loader.
|
|
|
| ## External dependencies
|
|
|
| 1. Download `Qwen/Qwen2.5-VL-7B-Instruct` through Transformers or the
|
| Hugging Face Hub. PEFT reads this identifier from `adapter_config.json`.
|
| 2. Download the official SAM ViT-H checkpoint
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| `sam_vit_h_4b8939.pth` from Meta's Segment Anything release.
|
| 3. Place this repository under the runtime weight root and place SAM at
|
| `external/sam_vit_h_4b8939.pth`, or override the relative paths in the MADL
|
| YAML configuration.
|
|
|
| Expected layout:
|
|
|
| ```text
|
| models/
|
| ├── agent_a_qwen_lora/
|
| ├── agent_b_dualstream/
|
| │ └── madl_agent_b_dualstream_v1.pt
|
| ├── agent_b_visual_ranker/
|
| │ └── madl_agent_b_visual_ranker_v1.pt
|
| └── external/
|
| └── sam_vit_h_4b8939.pth
|
| ```
|
|
|
| Verify the files before inference:
|
|
|
| ```bash
|
| python scripts/verify_weights.py /path/to/models
|
| ```
|
|
|
| ## Training data and evaluation scope
|
|
|
| The released components were trained for the SID-Set task, which distinguishes
|
| authentic, fully synthetic, and locally tampered images and provides masks for
|
| the locally tampered class. The release does not include SID-Set images. Users
|
| must obtain the dataset under its own terms.
|
|
|
| ## Intended use
|
|
|
| The weights are intended for academic research on image forgery detection,
|
| localization, evidence interaction, and multi-agent forensic reasoning. They
|
| are not a substitute for human forensic examination and should not be used as
|
| the sole basis for legal, disciplinary, or content-removal decisions.
|
|
|
| ## Limitations
|
|
|
| - Very small, fragmented, or weak-trace manipulations remain difficult.
|
| - Cross-dataset behavior has not been established by the final manuscript.
|
| - Multiple model calls increase latency and GPU memory requirements.
|
| - The natural-language field is a structured evidence trace; the release does
|
| not claim that it has been independently evaluated as explanation quality.
|
| - Results depend on the exact Qwen, SAM, preprocessing, and threshold versions
|
| documented by the companion code.
|
|
|
| ## Licenses and attribution
|
|
|
| The released MADL code and original weight packaging are provided under
|
| Apache-2.0. Qwen2.5-VL, SAM, SID-Set, and other dependencies retain their own
|
| licenses and terms. The [code README](https://github.com/shannima/MADL#third-party-components)
|
| lists the relevant upstream projects. Dataset-derived use should preserve SID-Set attribution.
|
|
|
