Spaces:
Running
on
L40S
Running
on
L40S
File size: 2,758 Bytes
e3e5f9e 68cd723 e3e5f9e 68cd723 e3e5f9e 68cd723 e3e5f9e 68cd723 e3e5f9e |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 |
import os
from typing import List, Optional
from PIL import Image
import imageio
import time
import torch
from pytorch3d.io import load_objs_as_meshes, load_obj, save_obj
from pytorch3d.ops import interpolate_face_attributes
from pytorch3d.common.datatypes import Device
from pytorch3d.structures import Meshes
from pytorch3d.vis.texture_vis import texturesuv_image_matplotlib
from pytorch3d.renderer import (
look_at_view_transform,
FoVPerspectiveCameras,
PointLights,
DirectionalLights,
AmbientLights,
Materials,
RasterizationSettings,
MeshRenderer,
MeshRasterizer,
SoftPhongShader,
TexturesUV,
TexturesVertex,
camera_position_from_spherical_angles,
BlendParams,
)
def render_func(
obj_filename,
elev=0,
azim=None,
resolution=512,
gif_dst_path='',
n_views=120,
fps=30,
device="cuda:0",
rgb=False
):
'''
obj_filename: path to obj file
gif_dst_path:
if set a path, will render n_views frames, then save it to a gif file
if not set, will render single frame, then return PIL.Image instance
rgb: if set true, will convert result to rgb image/frame
'''
# load mesh
mesh = load_objs_as_meshes([obj_filename], device=device)
meshes = mesh.extend(n_views)
if azim is None:
elev = torch.linspace(elev, elev, n_views+1)[:-1]
azim = torch.linspace(0, 360, n_views+1)[:-1]
# prepare R,T then compute cameras
R, T = look_at_view_transform(dist=1.5, elev=elev, azim=azim)
cameras = FoVPerspectiveCameras(device=device, R=R, T=T, fov=49.1)
# init pytorch3d renderer instance
renderer = MeshRenderer(
rasterizer=MeshRasterizer(
cameras=cameras,
raster_settings=RasterizationSettings(
image_size=resolution,
blur_radius=0.0,
faces_per_pixel=1,
),
),
shader=SoftPhongShader(
device=device,
cameras=cameras,
lights=AmbientLights(device=device),
blend_params=BlendParams(background_color=(1.0, 1.0, 1.0)),
)
)
images = renderer(meshes)
if gif_dst_path != '':
with imageio.get_writer(uri=gif_dst_path, mode='I', duration=1. / fps * 1000, loop=0) as writer:
for i in range(n_views):
frame = images[i, ..., :3] if rgb else images[i, ...]
frame = Image.fromarray((frame.cpu().squeeze(0) * 255).numpy().astype("uint8"))
writer.append_data(frame)
frame = images[..., :3] if rgb else images
frames = [Image.fromarray((fra.cpu().squeeze(0) * 255).numpy().astype("uint8")) for fra in frame]
return frames
|