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| # Copyright (C) 2024-present Naver Corporation. All rights reserved. | |
| # Licensed under CC BY-NC-SA 4.0 (non-commercial use only). | |
| # | |
| # -------------------------------------------------------- | |
| # PatchEmbed implementation for DUST3R, | |
| # in particular ManyAR_PatchEmbed that Handle images with non-square aspect ratio | |
| # -------------------------------------------------------- | |
| import torch | |
| from mini_dust3r.croco.blocks import PatchEmbed | |
| def get_patch_embed(patch_embed_cls, img_size, patch_size, enc_embed_dim): | |
| assert patch_embed_cls in ['PatchEmbedDust3R', 'ManyAR_PatchEmbed'] | |
| patch_embed = eval(patch_embed_cls)(img_size, patch_size, 3, enc_embed_dim) | |
| return patch_embed | |
| class PatchEmbedDust3R(PatchEmbed): | |
| def forward(self, x, **kw): | |
| B, C, H, W = x.shape | |
| assert H % self.patch_size[0] == 0, f"Input image height ({H}) is not a multiple of patch size ({self.patch_size[0]})." | |
| assert W % self.patch_size[1] == 0, f"Input image width ({W}) is not a multiple of patch size ({self.patch_size[1]})." | |
| x = self.proj(x) | |
| pos = self.position_getter(B, x.size(2), x.size(3), x.device) | |
| if self.flatten: | |
| x = x.flatten(2).transpose(1, 2) # BCHW -> BNC | |
| x = self.norm(x) | |
| return x, pos | |
| class ManyAR_PatchEmbed (PatchEmbed): | |
| """ Handle images with non-square aspect ratio. | |
| All images in the same batch have the same aspect ratio. | |
| true_shape = [(height, width) ...] indicates the actual shape of each image. | |
| """ | |
| def __init__(self, img_size=224, patch_size=16, in_chans=3, embed_dim=768, norm_layer=None, flatten=True): | |
| self.embed_dim = embed_dim | |
| super().__init__(img_size, patch_size, in_chans, embed_dim, norm_layer, flatten) | |
| def forward(self, img, true_shape): | |
| B, C, H, W = img.shape | |
| assert W >= H, f'img should be in landscape mode, but got {W=} {H=}' | |
| assert H % self.patch_size[0] == 0, f"Input image height ({H}) is not a multiple of patch size ({self.patch_size[0]})." | |
| assert W % self.patch_size[1] == 0, f"Input image width ({W}) is not a multiple of patch size ({self.patch_size[1]})." | |
| assert true_shape.shape == (B, 2), f"true_shape has the wrong shape={true_shape.shape}" | |
| # size expressed in tokens | |
| W //= self.patch_size[0] | |
| H //= self.patch_size[1] | |
| n_tokens = H * W | |
| height, width = true_shape.T | |
| is_landscape = (width >= height) | |
| is_portrait = ~is_landscape | |
| # allocate result | |
| x = img.new_zeros((B, n_tokens, self.embed_dim)) | |
| pos = img.new_zeros((B, n_tokens, 2), dtype=torch.int64) | |
| # linear projection, transposed if necessary | |
| x[is_landscape] = self.proj(img[is_landscape]).permute(0, 2, 3, 1).flatten(1, 2).float() | |
| x[is_portrait] = self.proj(img[is_portrait].swapaxes(-1, -2)).permute(0, 2, 3, 1).flatten(1, 2).float() | |
| pos[is_landscape] = self.position_getter(1, H, W, pos.device) | |
| pos[is_portrait] = self.position_getter(1, W, H, pos.device) | |
| x = self.norm(x) | |
| return x, pos | |