def extract_backbone_features(self, im: torch.Tensor, dp: torch.Tensor, pos: torch.Tensor, scales, sz: torch.Tensor): im_patches, patch_coords_rgb = sample_patch_multiscale(im, pos, scales, sz, mode=self.params.get('border_mode', 'replicate'), max_scale_change=self.params.get('patch_max_scale_change', None)) dp_patches, patch_coords_d = sample_patch_multiscale(dp, pos, scales, sz, mode=self.params.get('border_mode', 'replicate'), max_scale_change=self.params.get('patch_max_scale_change', None)) with torch.no_grad(): backbone_feat_rgb = self.net_rgb.extract_backbone(im_patches) backbone_feat_d = self.net_d.extract_backbone(dp_patches) return backbone_feat_rgb, backbone_feat_d, patch_coords_rgb, patch_coords_d, im_patches, dp_patches
def extract_backbone_features(self, im: torch.Tensor, pos: torch.Tensor, scales, sz: torch.Tensor): im_patches, patch_coords = sample_patch_multiscale( im, pos, scales, sz, getattr(self.params, 'border_mode', 'replicate')) with torch.no_grad(): backbone_feat = self.net.extract_backbone(im_patches) return backbone_feat, patch_coords
def extract_backbone_features(self, im: torch.Tensor, pos: torch.Tensor, scale, sz: torch.Tensor): im_patches, patch_coords = sample_patch_multiscale( im, pos, scale.unsqueeze(0), sz, mode=self.params.get('border_mode', 'replicate'), max_scale_change=self.params.get('patch_max_scale_change', None)) with torch.no_grad(): backbone_feat = self.net.extract_backbone(im_patches) return backbone_feat, patch_coords[0], im_patches[0]