import pytorch3d import torch import imageio import numpy as np import os from pytorch3d.io import load_objs_as_meshes from pytorch3d.renderer import ( AmbientLights, PerspectiveCameras, RasterizationSettings, look_at_view_transform, TexturesVertex, MeshRenderer, Materials, MeshRasterizer, SoftPhongShader, PointLights ) import trimesh from tqdm import tqdm from pytorch3d.transforms import RotateAxisAngle from shader import MultiOutputShader def render_video_from_obj(input_obj_path, output_video_path, num_frames=60, image_size=512, fps=15, device="cuda"): if not os.path.exists(input_obj_path): raise FileNotFoundError(f"Input OBJ file not found: {input_obj_path}") scene_data = trimesh.load(input_obj_path) if isinstance(scene_data, trimesh.Scene): mesh_data = trimesh.util.concatenate([geom for geom in scene_data.geometry.values()]) else: mesh_data = scene_data if not hasattr(mesh_data, 'vertex_normals') or mesh_data.vertex_normals is None: mesh_data.compute_vertex_normals() vertices = torch.tensor(mesh_data.vertices, dtype=torch.float32, device=device) faces = torch.tensor(mesh_data.faces, dtype=torch.int64, device=device) if mesh_data.visual.vertex_colors is None: vertex_colors = torch.ones_like(vertices)[None] else: vertex_colors = torch.tensor(mesh_data.visual.vertex_colors[:, :3], dtype=torch.float32)[None] textures = TexturesVertex(verts_features=vertex_colors) textures.to(device) mesh = pytorch3d.structures.Meshes(verts=[vertices], faces=[faces], textures=textures) lights = AmbientLights(ambient_color=((2.0,)*3,), device=device) # lights = PointLights(device=device, location=[[0.0, 0.0, 3.0]], ambient_color=[[0.5, 0.5, 0.5]], diffuse_color=[[1.0, 1.0, 1.0]]) raster_settings = RasterizationSettings( image_size=image_size, blur_radius=0.0, faces_per_pixel=1, ) frames = [] camera_distance = 6.5 elevs = 0.0 center = (0.0, 0.0, 0.0) materials = Materials( device=device, diffuse_color=((1.0, 1.0, 1.0),), ambient_color=((1.0, 1.0, 1.0),), specular_color=((1.0, 1.0, 1.0),), shininess=0.0, ) rasterizer = MeshRasterizer(raster_settings=raster_settings) for i in tqdm(range(num_frames)): azims = 360.0 * i / num_frames R, T = look_at_view_transform( dist=camera_distance, elev=elevs, azim=azims, at=(center,), degrees=True ) # 手动设置相机的旋转矩阵 cameras = PerspectiveCameras(device=device, R=R, T=T, focal_length=5.0) cameras.znear = 0.0001 cameras.zfar = 10000000.0 shader=MultiOutputShader( device=device, cameras=cameras, lights=lights, materials=materials, choices=["rgb", "mask", "normal"] ) renderer = MeshRenderer(rasterizer=rasterizer, shader=shader) render_result = renderer(mesh, cameras=cameras) rgb_image = render_result["rgb"] * render_result["mask"] + (1 - render_result["mask"]) * torch.ones_like(render_result["rgb"]) * 255.0 normal_map = render_result["normal"] rgb = rgb_image[0, ..., :3].cpu().numpy() normal_map = torch.nn.functional.normalize(normal_map, dim=-1) # Normal map normal_map = (normal_map + 1) / 2 normal_map = normal_map * render_result["mask"] + (1 - render_result["mask"]) * torch.ones_like(render_result["normal"]) normal = normal_map[0, ..., :3].cpu().numpy() # Normal map rgb = np.clip(rgb, 0, 255).astype(np.uint8) normal = np.clip(normal*255, 0, 255).astype(np.uint8) combined_image = np.concatenate((rgb, normal), axis=1) frames.append(combined_image) imageio.mimsave(output_video_path, frames, fps=fps) print(f"Video saved to {output_video_path}") if __name__ == '__main__': input_obj_path = "/hpc2hdd/home/jlin695/code/github/Kiss3DGen/outputs/a_owl_wearing_a_hat/ISOMER/rgb_projected.obj" output_video_path = "output.mp4" render_video_from_obj(input_obj_path, output_video_path)