Closed nitish11 closed 4 years ago
Hi @nitish11 ,
if you only want to run our pretrained models on RGB images, please have a look at our demo. You can further adjust the path to the image in the respective demo config file. Finally, in the default config you can find the config entry
generation:
mesh_extension: ply
which you can use to change the output format
Thanks @m-niemeyer for the hint. I was able to generate good quality of 3D models from random test images just by changing config file, configs/demo/demo_combined.yaml.
inherit_from: configs/single_view_reconstruction/multi_view_supervision/ours_combined_pretrained.yaml
data:
dataset_name: images
path: media/test_images
training:
out_dir: media/out_3D_models
generation:
generation_dir: generation
media/test_images : contains all the images media/out_3D_models : contains all 3D models.
How to generate 3D model from a single 2D image?
The config file mentioned below does't contain parameter test_input image path. https://github.com/autonomousvision/differentiable_volumetric_rendering/blob/master/configs/single_view_reconstruction/single_view_supervision/ours_combined_pretrained.yaml
Which part of the code generate 3D model, how to change the output format of 3D model?