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 * [**SAM-2**](https://github.com/facebookresearch/sam2) (tiny, small and large): newest and improved version of SAM released by Meta. Not only this version reduces a lot the computation cost, it also improves the performance. To do so, this model uses a new variant of Vision Transofrmer (ViT), the [Hiera ViT](https://github.com/facebookresearch/hiera).
 * [**EfficientSAM**](https://github.com/yformer/EfficientSAM): small Vision Transformer trained by distilling the original SAM Huge transformer using Masked Autoencoders.
 * [**EfficientViTSAM**](https://github.com/mit-han-lab/efficientvit): SAM like model that uses a special lightweigth image encoder, EfficientViT.
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+# Big images
+SAM pre-processing includes re-sizing the image to 1024x1024, thus in images bigger than that, every detail smaller than `original _size / 1024` pixel(s) will become subpixel and thus disappear. In order mantain the performance on big images,SAMJ