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Tutorial - Fit neural radiance field

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Summary: Implements a simple nerf tutorial.

Reviewed By: nikhilaravi

Differential Revision: D24650983

fbshipit-source-id: b3db51c0ed74779ec9b510350d1675b0ae89422c
This commit is contained in:
David Novotny
2021-01-06 08:24:57 -08:00
committed by Facebook GitHub Bot
parent 01f86ddeb1
commit 9fc661f8b3
2 changed files with 866 additions and 2 deletions
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7
docs/tutorials/utils/generate_cow_renders.py
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@@ -19,12 +19,15 @@ from pytorch3d.renderer import (
look_at_view_transform,
)
# create the default data directory
current_dir = os.path.dirname(os.path.realpath(__file__))
DATA_DIR = os.path.join(current_dir, "..", "data", "cow_mesh")
def generate_cow_renders(num_views: int = 40, data_dir: str = DATA_DIR):
def generate_cow_renders(
num_views: int = 40, data_dir: str = DATA_DIR, azimuth_range: float = 180
):
"""
This function generates `num_views` renders of a cow mesh.
The renders are generated from viewpoints sampled at uniformly distributed
@@ -94,7 +97,7 @@ def generate_cow_renders(num_views: int = 40, data_dir: str = DATA_DIR):
# Get a batch of viewing angles.
elev = torch.linspace(0, 0, num_views) # keep constant
azim = torch.linspace(-180, 180, num_views)
azim = torch.linspace(-azimuth_range, azimuth_range, num_views) + 180.0
# Place a point light in front of the object. As mentioned above, the front of
# the cow is facing the -z direction.