File size: 6,396 Bytes
0d1388f | 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 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 | import os
import sys
import argparse
import time
import imageio
import numpy as np
from PIL import Image
sys.path.insert(0, './hy3dshape')
os.environ['TORCH_CUDA_ARCH_LIST'] = '9.0'
os.environ['ATTN_BACKEND'] = 'xformers'
os.environ['SPCONV_ALGO'] = 'native'
from trellis.pipelines import NeARImageToRelightable3DPipeline
from hy3dshape.pipelines import Hunyuan3DDiTFlowMatchingPipeline
def main():
parser = argparse.ArgumentParser(description='NeAR: from image or SLaT to relightable 3D')
parser.add_argument('--checkpoint', type=str, default='checkpoints',
help='Pipeline weights directory (contains pipeline.yaml)')
parser.add_argument('--image', type=str, default="assets/example_image/T.png",
help='Input image path (one of --slat or --image)')
parser.add_argument('--slat', type=str, default=None,
help='SLaT .npz path (one of --image or --slat)')
parser.add_argument('--hdri', type=str, default="assets/hdris/studio_small_03_1k.exr",
help='HDRI .exr path')
parser.add_argument('--out_dir', type=str, default='relight_out',
help='Output directory')
parser.add_argument('--yaw', type=float, default=0.0, help='View yaw (degrees) ')
parser.add_argument('--pitch', type=float, default=0.0, help='View pitch (degrees)')
parser.add_argument('--hdri_rot', type=float, default=0.0,
help='HDRI rotation angle (degrees)')
parser.add_argument('--video_frames', type=int, default=40,
help='Render additional spiral camera path video frames')
parser.add_argument('--seed', type=int, default=42, help='Random seed')
parser.add_argument('--save_slat', type=str, default=None,
help='When generating from image, save SLaT to this .npz path')
parser.add_argument('--no_cuda', action='store_true', help='Do not use CUDA')
args = parser.parse_args()
if (args.image is None) == (args.slat is None):
parser.error('Please specify --image or --slat, one of them')
from_image = args.image is not None
os.makedirs(args.out_dir, exist_ok=True)
device = 'cuda' if not args.no_cuda else 'cpu'
total_t0 = time.perf_counter()
t0 = time.perf_counter()
hyshape_model_id = 'tencent/Hunyuan3D-2.1'
hyshape_pipe = Hunyuan3DDiTFlowMatchingPipeline.from_pretrained(hyshape_model_id)
hyshape_pipe.to(device)
pipeline = NeARImageToRelightable3DPipeline.from_pretrained(args.checkpoint)
pipeline.to(device)
print(f" [OK] Pipeline loaded, +{time.perf_counter() - t0:.1f}s")
if from_image:
image = Image.open(args.image).convert('RGB')
image_prep = pipeline.preprocess_image(image)
t0 = time.perf_counter()
mesh = hyshape_pipe(image=image_prep)[0]
mesh_path = os.path.join(args.out_dir, 'initial_3d_shape.glb')
mesh.export(mesh_path)
print(f" [OK] Geometry mesh generated, +{time.perf_counter() - t0:.1f}s, saved to {mesh_path}")
t0 = time.perf_counter()
slat = pipeline.run_with_shape(
image_prep,
mesh,
seed=args.seed,
preprocess_image=False,
)
print(f" [OK] Image → SLaT generated, +{time.perf_counter() - t0:.1f}s")
if args.save_slat:
np.savez(
args.save_slat,
feats=slat.feats.cpu().numpy(),
coords=slat.coords.cpu().numpy(),
)
print(f" [OK] Saved SLaT to: {args.save_slat}")
else:
t0 = time.perf_counter()
slat = pipeline.load_slat(args.slat)
print(f" [OK] Loaded SLaT, +{time.perf_counter() - t0:.1f}s")
t0 = time.perf_counter()
hdri_np = pipeline.load_hdri(args.hdri)
print(f" [OK] Loaded HDRI, +{time.perf_counter() - t0:.1f}s")
t0 = time.perf_counter()
pipeline.renderer.ssaa = 1
pipeline.renderer.resolution = 1024
views = pipeline.render_view(
slat, hdri_np,
yaw_deg=args.yaw, pitch_deg=args.pitch,
fov=40.0, radius=2.0, hdri_rot_deg=args.hdri_rot,
resolution=512
)
color_path = os.path.join(args.out_dir, 'relight_color.png')
base_color_path = os.path.join(args.out_dir, 'base_color.png')
metallic_path = os.path.join(args.out_dir, 'metallic.png')
roughness_path = os.path.join(args.out_dir, 'roughness.png')
shadow_path = os.path.join(args.out_dir, 'shadow.png')
views['color'].save(color_path)
views['base_color'].save(base_color_path)
views['metallic'].save(metallic_path)
views['roughness'].save(roughness_path)
views['shadow'].save(shadow_path)
print(f" [OK] Single view rendering completed, +{time.perf_counter() - t0:.1f}s, saved to {color_path}, {base_color_path}, {metallic_path}, {roughness_path}, {shadow_path}")
if args.video_frames > 0:
t0 = time.perf_counter()
frames = pipeline.render_camera_path_video(
slat, hdri_np, num_views=args.video_frames,
fov=40.0, radius=2.0, hdri_rot_deg=args.hdri_rot,
verbose=True, full_video=True, shadow_video=True
)
video_path = os.path.join(args.out_dir, 'relight_camera_path.mp4')
imageio.mimsave(video_path, frames, fps=24)
print(f" [OK] Camera path video completed, +{time.perf_counter() - t0:.1f}s, saved to {video_path}")
print("Done.")
if args.video_frames > 0:
t0 = time.perf_counter()
hdri_roll_frames, render_frames = pipeline.render_hdri_rotation_video(
slat, hdri_np, num_frames=args.video_frames,
yaw_deg=args.yaw, pitch_deg=args.pitch,
fov=40.0, radius=2.0,
verbose=True, full_video=True, shadow_video=True
)
hdri_video_path = os.path.join(args.out_dir, 'hdri_roll.mp4')
render_video_path = os.path.join(args.out_dir, 'relight_hdri_rotation.mp4')
imageio.mimsave(hdri_video_path, hdri_roll_frames, fps=24)
imageio.mimsave(render_video_path, render_frames, fps=24)
print(
f" [OK] HDRI rotation videos completed, +{time.perf_counter() - t0:.1f}s, "
f"saved to {hdri_video_path} and {render_video_path}"
)
print(f" [OK] Total time: {time.perf_counter() - total_t0:.1f}s")
if __name__ == '__main__':
main()
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