Hello，thank you for sharing the source code. But When I executed the "make" command，such a error occured: /ext/preprocess/preprocess.cpp:272:74: error: converting to ‘std::tuple<pybind11::array_t<float, 16>, pybind11::array_t<float, 16>, pybind11::array_t<float, 16> >’ from initializer list would use explicit constructor ‘constexpr std::tuple< <template-parameter-1-1> >::tuple(_UElements&& ...) [with _UElements = {pybind11::array_t<float, 16>, pybind11::array_t<float, 16>, pybind11::array_t<float, 16>}; <template-parameter-2-2> = void; _Elements = {pybind11::array_t<float, 16>, pybind11::array_t<float, 16>, pybind11::array_t<float, 16>}]’ {n_views, 1, patch_height, patch_width})};

is there some wrong in preprocess.cpp?

Hi, Thank you very much for sharing your code. But when I run your code, the following error occurs:

/FreeViewSynthesis/exp/dataset.py", line 165, in base_getitem sampling_maps, valid_depth_masks, valid_map_masks = ext.preprocess.get_sampling_map( AttributeError: module 'ext.preprocess' has no attribute 'get_sampling_map'

Hope you can help answer, thank you.

Hi Riegler, thank you for this great work in view synthesis. It is really appreciated that you have provided you preprocessed dataset and training/eval code. May I know how to preprocess our customized dataset (a few images) so that we can apply this method directly on it?

Hi @griegler, When I try to modify the Ks.npy/Rs.npy/ts.npy for synthesis new view images, the output results are always the same as the original camera parameters' output, hope you can help, thanks~

while running

python exp.py --net rnn_vgg16unet3_gruunet4.64.3 --cmd eval --iter last --eval-dsets tat-subseq --eval-scale 0.5

I get the error: IndexError: index 221 is out of bounds for axis 0 with size 0

I modified my path to point Playground dataset in config and commented truck, M60 and train eval tracks.

for midx, mod in enumerate(self.vgg): es = mod(es)

for i,mod in enumerate(vgg): ... if i == 3: ... print(mod) ... ReLU(inplace=True)

I can't understand this，why?

Hi! When I tried to test my own image data, I was blocked for the gap between dense file output by Colmap and the downloaded dataset. It seems to be hard for me to make this translation. Could you give me some hits for it? For example, a script. Sincerely thanks. The output of the colmap is as following. The official output describe can be found here: +── images │ +── image1.jpg │ +── image2.jpg │ +── ... +── sparse │ +── cameras.txt │ +── images.txt │ +── points3D.txt +── stereo │ +── consistency_graphs │ │ +── image1.jpg.photometric.bin │ │ +── image2.jpg.photometric.bin │ │ +── ... │ +── depth_maps │ │ +── image1.jpg.photometric.bin │ │ +── image2.jpg.photometric.bin │ │ +── ... │ +── normal_maps │ │ +── image1.jpg.photometric.bin │ │ +── image2.jpg.photometric.bin │ │ +── ... │ +── patch-match.cfg │ +── fusion.cfg +── fused.ply +── meshed-poisson.ply +── meshed-delaunay.ply +── run-colmap-geometric.sh +── run-colmap-photometric.sh

Hi, thanks for your great work. I just want to eval the result by python exp.py --net rnn_vgg16unet3_gruunet4.64.3 --cmd eval --iter last --eval-dsets tat-subseq --eval-scale 0.5 in exp folder. I'm confused about the following code in config.py:

# TODO: adjust path
tat_root = Path("/path/to/colmap_tat/")

And I notice that config.tat_root was used in exp.py

    def get_train_set_tat(self, dset):
        dense_dir = config.tat_root / dset / "dense"
        print(dense_dir,'------------------------------------------------------------')
        ibr_dir = dense_dir / f"ibr3d_pw_{self.train_scale:.2f}"
        dset = self.get_pw_dataset(
            name=f'tat_{dset.replace("/", "_")}',
            ibr_dir=ibr_dir,
            im_size=None,
            pad_width=16,
            patch=(self.train_patch, self.train_patch),
            n_nbs=self.train_n_nbs,
            nbs_mode=self.train_nbs_mode,
            train=True,
        )
        return dset

I'm curious about why exp.py will load tat_train_sets when I try to eval the result with the given pretrained model. It seems that the path list in

tat_train_sets = [
    "training/Barn",
    "training/Caterpillar",
    "training/Church",
    "training/Courthouse",
    "training/Ignatius",
    "training/Meetingroom",
    "intermediate/Family",
    "intermediate/Francis",
    "intermediate/Horse",
    "intermediate/Lighthouse",
    "intermediate/Panther",
    "advanced/Auditorium",
    "advanced/Ballroom",
    "advanced/Museum",
    "advanced/Temple",
    "advanced/Courtroom",
    "advanced/Palace",
]

isn't exist in this rep.

Hi,

Thanks for sharing the preprocessed dataset.

I am wondering if you still have the reconstructed meshes for the dataset produced by COLMAP? Would it be possible to share them?

Thanks a lot.

Hi, This is great work!! Thank you for making your code public :)

I'm trying to use your proxy-geometry generation pipeline using the scripts in co/colmap.py but am not a 100% sure I'm doing it right. Is this how you generated the meshes in your paper? Thanks in advance!

colmap = Colmap(...)
colmap.sparse_reconstruction_unknown_calib()
colmap.dense_reconstruction()
colmap.delaunay_meshing()

Hi @griegler,

When I look into preprocess.cpp to understand how sampling maps are computed, I could not understand why the image coordinate (src_wf, src_wh) is multiplied by 2 in https://github.com/intel-isl/FreeViewSynthesis/blob/master/ext/preprocess/preprocess.cpp#L262-L263. Is there any specific reason to do that? Would you mind to share a few detail on it? Thanks.

.

Hi,

Thanks for the wonderful work. I was wondering about how you obtained your DTU ground truth meshes. Was it the same way you obtained them for tanks and temples? If yes, would it be possible to share them?

Thanks in advance

Hi @griegler, thanks for your generous share, I have succeeded to generate some new view images using your scripts. but I also curious about how to generate some random camera path like pitch angle instead of just interpolate the original camera(def interpolate_waypoints) path so that the new views are more abundant and variable. thanks~

Hey, Thanks for your help and I succeed in run it. But there may exist some little bug. I try to fix this error type: list has no attribute ravel. The error raises if we run the following: python exp.py --net rnn_vgg16unet3_gruunet4.64.3 --cmd eval --iter last --eval-dsets tat-subseq --eval-scale 0.5 Only np array has attribute ravel. But isinstance(v, (np.ndarray, list)) make list operate list.ravel which will cause error.

Sorry for me can't provide the snapshot because I get off work and forget to save.