From 0bb199d9e993499225f1035eccb391a3faddef95 Mon Sep 17 00:00:00 2001 From: Ethan Weber Date: Mon, 30 Jan 2023 19:53:39 +0000 Subject: [PATCH] adjust scale factor logic --- nerfstudio/data/datamanagers/base_datamanager.py | 10 +++++++--- 1 file changed, 7 insertions(+), 3 deletions(-) diff --git a/nerfstudio/data/datamanagers/base_datamanager.py b/nerfstudio/data/datamanagers/base_datamanager.py index c4a6d35e3..c4ea8f1b3 100644 --- a/nerfstudio/data/datamanagers/base_datamanager.py +++ b/nerfstudio/data/datamanagers/base_datamanager.py @@ -432,9 +432,13 @@ class VanillaDataManager(DataManager): # pylint: disable=abstract-method # image_batch["image"].shape == (1, H, W, 3) # this will sample the entire image # we downsample the image so it fits in memory - image_batch["image"] = torch.nn.functional.interpolate( - image_batch["image"].permute(0, 3, 1, 2), scale_factor=scale_factor, mode="bilinear", align_corners=False - ).permute(0, 2, 3, 1) + if scale_factor != 1.0: + image_batch["image"] = torch.nn.functional.interpolate( + image_batch["image"].permute(0, 3, 1, 2), + scale_factor=scale_factor, + mode="bilinear", + align_corners=False, + ).permute(0, 2, 3, 1) batch = self.eval_pixel_sampler.sample(image_batch, sample_all_pixels=True) ray_indices = batch["indices"]