a d!@sddlmZddlmZmZmZddlZddlmZer@ddl Z dde ej dddZ edej d d d Zej ej d d dZej ej d ddZdej e ddddZGdddejZeedddZeedddZdS))wraps) TYPE_CHECKINGCallableListNT np.ndarray)imagekeepdimreturncCst|jdkst|jdkr$td|j}t|}t|dkrL|d}nLt|dkrh|ddd}n0t|dkr|dddd}d}ntd||s|dS|S) aConvert a numpy image to a PyTorch 4d tensor image. Args: image: image of the form :math:`(H, W, C)`, :math:`(H, W)` or :math:`(B, H, W, C)`. keepdim: If ``False`` unsqueeze the input image to match the shape :math:`(B, H, W, C)`. Returns: tensor of the form :math:`(B, C, H, W)` if keepdim is ``False``, :math:`(C, H, W)` otherwise. Example: >>> img = np.ones((3, 3)) >>> image_to_tensor(img).shape torch.Size([1, 3, 3]) >>> img = np.ones((4, 4, 1)) >>> image_to_tensor(img).shape torch.Size([1, 4, 4]) >>> img = np.ones((4, 4, 3)) >>> image_to_tensor(img, keepdim=False).shape torch.Size([1, 3, 4, 4]) z9Input size must be a two, three or four dimensional arrayrTz Cannot process image with shape )lenshape ValueErrortorchZ from_numpy unsqueezeZpermute)rr input_shapetensorr[/var/www/html/stable-diffusion-webui/venv/lib/python3.9/site-packages/kornia/utils/image.pyimage_to_tensor s     r)imagesr cCsP|s tdt|djdkr&tdg}|D]}|t|q.t|}|S)aConverts a list of numpy images to a PyTorch 4d tensor image. Args: images: list of images, each of the form :math:`(H, W, C)`. Image shapes must be consistent Returns: tensor of the form :math:`(B, C, H, W)`. Example: >>> imgs = [np.ones((4, 4, 1)), np.zeros((4, 4, 1))] >>> image_list_to_tensor(imgs).shape torch.Size([2, 1, 4, 4]) z#Input list of numpy images is emptyrr z-Input images must be three dimensional arrays)rrrappendrrstack)rZlist_of_tensorsrrrrrimage_list_to_tensor;s r)rr cCst|tjstdt|t|jdkr>> img = torch.ones(1, 3, 3) >>> tensor_to_image(img).shape (3, 3) >>> img = torch.ones(3, 4, 4) >>> tensor_to_image(img).shape (4, 4, 3) rr r z:Input size must be a two, three or four dimensional tensorr rr rz!Cannot process tensor with shape ) r!rr"r#r$rrrcpudetachnumpyZsqueezeZ transpose)rrrrrrrtensor_to_images(         r.cs:eZdZdZd edfdd Zdejddd ZZ S) ImageToTensorzConverts a numpy image to a PyTorch 4d tensor image. Args: keepdim: If ``False`` unsqueeze the input image to match the shape :math:`(B, H, W, C)`. Frcst||_dS)N)super__init__r)selfr __class__rrr2s zImageToTensor.__init__r)xr cCst||jdS)Nr0)rr)r3r6rrrforwardszImageToTensor.forward)F) __name__ __module__ __qualname____doc__boolr2rr"r7 __classcell__rrr4rr/sr/)fr cs ttjdfdd }|S)zA decorator that enable `f` to be applied to an image of arbitrary leading dimensions `(*, C, H, W)`. It works by first viewing the image as `(B, C, H, W)`, applying the function and re-viewing the image as original shape. inputcst|tjstdt||dkr2td|j}t|}|g|Ri|}t |dkrj|d}t |dkr~|d}t |dkr|j |dd|jdd}|S) N,Input input type is not a torch.Tensor. Got r"Invalid input tensor, it is empty.r r rrr r) r!rr"r#r$numelrrr'rr%r@argskwargsroutputr>rr_wrappers      z*perform_keep_shape_image.._wrapperrrr"r>rJrrIrperform_keep_shape_imagesrMcs ttjdfdd }|S)zA decorator that enable `f` to be applied to an image of arbitrary leading dimensions `(*, C, D, H, W)`. It works by first viewing the image as `(B, C, D, H, W)`, applying the function and re-viewing the image as original shape. r?cst|tjstdt||dkr2td|j}t|}|g|Ri|}t |dkrj|d}t |dkr~|d}t |dkr|j |dd|jdd}|S) NrArrBr r rCr(r)) r!rr"r#r$rDrrr*rr%rErIrrrJs      z*perform_keep_shape_video.._wrapperrKrLrrIrperform_keep_shape_videosrN)T)F) functoolsrtypingrrrrZtorch.nnnnr-npr<r"rrr'r*r.Moduler/rMrNrrrrs  07