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- art
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datasets:
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- deepghs/ai_image_corrupted
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---
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| Name | FLOPS | Params | Accuracy | AUC | Confusion | Labels |
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|:-------------------------:|:-------:|:--------:|:----------:|:------:|:---------------------------------------------------------------------------------------------------------------------:|:---------------------:|
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| caformer_s36_v0_focal | 22.10G | 37.21M | 95.65% | 0.9916 | [confusion](https://huggingface.co/deepghs/ai_image_corrupted/blob/main/caformer_s36_v0_focal/plot_confusion.png) | `corrupted`, `normal` |
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| caformer_s36_v0_sce | 22.10G | 37.21M | 95.77% | 0.9894 | [confusion](https://huggingface.co/deepghs/ai_image_corrupted/blob/main/caformer_s36_v0_sce/plot_confusion.png) | `corrupted`, `normal` |
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| mobilenetv3_v0_focal_dist | 0.63G | 4.18M | 94.02% | 0.9842 | [confusion](https://huggingface.co/deepghs/ai_image_corrupted/blob/main/mobilenetv3_v0_focal_dist/plot_confusion.png) | `corrupted`, `normal` |
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- art
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datasets:
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- deepghs/ai_image_corrupted
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library_name: dghs-imgutils
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---
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This is the classifier model for predicting the anime-style stable-diffusion-generated images are corrupted or not.
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Trained on dataset [deepghs/ai_image_corrupted](https://huggingface.co/datasets/deepghs/ai_image_corrupted).
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## Models
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| Name | FLOPS | Params | Accuracy | AUC | Confusion | Labels |
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|:-------------------------:|:-------:|:--------:|:----------:|:------:|:---------------------------------------------------------------------------------------------------------------------:|:---------------------:|
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| caformer_s36_v0_focal | 22.10G | 37.21M | 95.65% | 0.9916 | [confusion](https://huggingface.co/deepghs/ai_image_corrupted/blob/main/caformer_s36_v0_focal/plot_confusion.png) | `corrupted`, `normal` |
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| caformer_s36_v0_sce | 22.10G | 37.21M | 95.77% | 0.9894 | [confusion](https://huggingface.co/deepghs/ai_image_corrupted/blob/main/caformer_s36_v0_sce/plot_confusion.png) | `corrupted`, `normal` |
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| mobilenetv3_v0_focal_dist | 0.63G | 4.18M | 94.02% | 0.9842 | [confusion](https://huggingface.co/deepghs/ai_image_corrupted/blob/main/mobilenetv3_v0_focal_dist/plot_confusion.png) | `corrupted`, `normal` |
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## How to Use
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You can use this model with [dghs-imgutils](https://dghs-imgutils.deepghs.org/main/api_doc/generic/classify.html).
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```python
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from imgutils.generic import classify_predict_score
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classify_predict_score(
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'sample_image.png',
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repo_id='deepghs/ai_image_corrupted',
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model_name='mobilenetv3_v0_focal_dist',
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)
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# {'corrupted': 0.7807788848876953, 'normal': 0.2192210853099823}
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```
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## Note
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This model is trained on SD1.5 images, generated by 8 different base models.
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So the better solution for this problem is to use some metrics like artstyle embeddings,
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this model will be deprecated as soon as the artstyle embedding model for anime images is completed.
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## Citation
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```
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@misc{Citation,
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title={AI-Corrupt Score for Anime Images},
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author={narugo1992},
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year={2023},
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howpublished={\url{https://huggingface.co/deepghs/ai_image_corrupted}}
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}
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```
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