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@@ -76,10 +76,10 @@ We name the folder to show the abstract information:
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  ## Subset details
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  **HAID-MiniImageNet**
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- Derived from MiniImageNet. Contains 60,000 images across 100 classes. Abstraction levels: **10, 30, 50, 100, 500, 1000** shapes (**Please note that the 500 and 1000 shapes are in the zip file of `HAID_MiniImageNet_500+1000.zip`**), each contains mode **0 and 1**.
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  **HAID-Caltech-256**
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- Derived from Caltech-256. Abstraction levels: **10, 30, 50, 100** shapes, each contains mode **0 and 1**.
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  **HAID-CIFAR-10**
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  Derived from CIFAR-10. Abstraction levels: **10, 30, 50, 100** shapes. Directory first splits by `train_cifar10/` and `test_cifar10/` (matching CIFAR), and each of those contains abstraction-level folders.
 
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  ## Subset details
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  **HAID-MiniImageNet**
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+ Derived from MiniImageNet. Contains 60,000 images across 100 classes. Abstraction levels: **10, 30, 50, 100, 500, 1000** shapes (**Please note that the 500 and 1000 shapes are in the seperate file/folder named `HAID_MiniImageNet_500+1000`**), each contains mode **0, 1, 2, 5, 7 and 8**.
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  **HAID-Caltech-256**
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+ Derived from Caltech-256. Abstraction levels: **10, 30, 50, 100** shapes, each contains mode **0, 1, 2, 5, 7 and 8**.
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  **HAID-CIFAR-10**
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  Derived from CIFAR-10. Abstraction levels: **10, 30, 50, 100** shapes. Directory first splits by `train_cifar10/` and `test_cifar10/` (matching CIFAR), and each of those contains abstraction-level folders.