Migrasi otomatis

README.md

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+---
+license: mit
+datasets:
+- deepghs/monochrome_danbooru
+metrics:
+- accuracy
+pipeline_tag: image-classification
+tags:
+- art
+---
+
+The models used for determining whether an anime image is monochrome have a training size of 384.
+
+|               Model              |  FLOPs | Accuracy |                                                          Confusion Matrix                                                          | Description                                                                                                                                            |
+|:--------------------------------:|:------:|:--------:|:----------------------------------------------------------------------------------------------------------------------------------:|--------------------------------------------------------------------------------------------------------------------------------------------------------|
+|           caformer_s36           | 22.10G |  95.63%  |           [Confusion Matrix](https://huggingface.co/deepghs/monochrome_detect/blob/main/caformer_s36/plot_confusion.png)           | Model: caformer_s36 from timm                                                                                                                          |
+|        caformer_s36_safe2        | 22.10G |  95.52%  |        [Confusion Matrix](https://huggingface.co/deepghs/monochrome_detect/blob/main/caformer_s36_safe2/plot_confusion.png)        | Model: caformer_s36 from timm, which have better precision and lower recall than caformer_s36                                                          |
+|         caformer_s36_plus        | 22.10G |  97.31%  |         [Confusion Matrix](https://huggingface.co/deepghs/monochrome_detect/blob/main/caformer_s36_plus/plot_confusion.png)        | Model: caformer_s36.sail_in22k_ft_in1k_384 pratrained from timm                                                                                        |
+|      caformer_s36_plus_safe2     | 22.10G |  97.09%  |      [Confusion Matrix](https://huggingface.co/deepghs/monochrome_detect/blob/main/caformer_s36_plus_safe2/plot_confusion.png)     | Model: caformer_s36.sail_in22k_ft_in1k_384 pratrained from timm, which have better precision and lower recall than caformer_s36.sail_in22k_ft_in1k_384 |
+|       mobilenetv3_large_100      |  0.63G |  95.40%  |       [Confusion Matrix](https://huggingface.co/deepghs/monochrome_detect/blob/main/mobilenetv3_large_100/plot_confusion.png)      | Model: mobilenetv3_large_100 from timm                                                                                                                 |
+|    mobilenetv3_large_100_dist    |  0.63G |  96.30%  |    [Confusion Matrix](https://huggingface.co/deepghs/monochrome_detect/blob/main/mobilenetv3_large_100_dist/plot_confusion.png)    | Distillated from caformer_s36_plus, using mobilenetv3_large_100                                                                                        |
+|    mobilenetv3_large_100_safe2   |  0.63G |  94.62%  |    [Confusion Matrix](https://huggingface.co/deepghs/monochrome_detect/blob/main/mobilenetv3_large_100_safe2/plot_confusion.png)   | Model: mobilenetv3_large_100 from timm, which have better precision and lower recall than mobilenetv3_large_100                                        |
+| mobilenetv3_large_100_dist_safe2 |  0.63G |  95.85%  | [Confusion Matrix](https://huggingface.co/deepghs/monochrome_detect/blob/main/mobilenetv3_large_100_dist_safe2/plot_confusion.png) | Distillated from caformer_s36_plus_safe2, using mobilenetv3_large_100                                                                                  |

caformer_s36/meta.json

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+{
+    "labels": [
+        "monochrome",
+        "normal"
+    ],
+    "name": "caformer_s36"
+}

caformer_s36/metrics.json

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+{
+    "AUC": 0.9907084785133566,
+    "accuracy": 0.9562780269058296,
+    "loss": 0.042353093779683444,
+    "mAP": 0.9907146862735166,
+    "step": 150
+}

caformer_s36/model.ckpt

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caformer_s36/model.onnx

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caformer_s36_plus/meta.json

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+{
+    "drop_path_rate": 0.4,
+    "labels": [
+        "monochrome",
+        "normal"
+    ],
+    "name": "caformer_s36.sail_in22k_ft_in1k_384",
+    "pretrained": true
+}

caformer_s36_plus/metrics.json

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+{
+    "AUC": 0.9966514321915019,
+    "accuracy": 0.9730941704035875,
+    "loss": 0.021936069169309357,
+    "mAP": 0.9967353129101008,
+    "step": 20
+}

caformer_s36_plus/model.ckpt

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caformer_s36_plus/model.onnx

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caformer_s36_plus_safe2/meta.json

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+{
+    "drop_path_rate": 0.4,
+    "labels": [
+        "monochrome",
+        "normal"
+    ],
+    "name": "caformer_s36.sail_in22k_ft_in1k_384",
+    "pretrained": true
+}

caformer_s36_plus_safe2/metrics.json

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+{
+    "AUC": 0.9955302150424101,
+    "accuracy": 0.9708520179372198,
+    "loss": 0.028756862397946736,
+    "mAP": 0.9956484992485766,
+    "step": 30
+}

caformer_s36_plus_safe2/model.ckpt

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caformer_s36_plus_safe2/model.onnx

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caformer_s36_safe2/meta.json

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+{
+    "labels": [
+        "monochrome",
+        "normal"
+    ],
+    "name": "caformer_s36"
+}

caformer_s36_safe2/metrics.json

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+{
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+    "accuracy": 0.9551569506726457,
+    "loss": 0.06188738217507907,
+    "mAP": 0.9868226986519757,
+    "step": 225
+}

caformer_s36_safe2/model.ckpt

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caformer_s36_safe2/model.onnx

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mobilenetv3_large_100/meta.json

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+{
+    "labels": [
+        "monochrome",
+        "normal"
+    ],
+    "name": "mobilenetv3_large_100"
+}

mobilenetv3_large_100/metrics.json

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+    "loss": 0.033743727342497074,
+    "mAP": 0.9705153386460841,
+    "step": 245
+}

mobilenetv3_large_100/model.ckpt

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mobilenetv3_large_100/model.onnx

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