new

shader.py

@@ -3,6 +3,8 @@ from pytorch3d.renderer.mesh.shader import ShaderBase
 from pytorch3d.renderer import (
     SoftPhongShader,
 )
+from pytorch3d.renderer import BlendParams
+
 
 class MultiOutputShader(ShaderBase):
     def __init__(self, device, cameras, lights, materials, ccm_scale=1.0, choices=None):
@@ -17,12 +19,13 @@ class MultiOutputShader(ShaderBase):
             self.choices = ["rgb", "mask", "depth", "normal", "albedo", "ccm"]
         else:
             self.choices = choices
-
+        blend_params = BlendParams(sigma=1e-4, gamma=1e-4)  
         self.phong_shader = SoftPhongShader(
             device=self.device,
             cameras=self.cameras,
             lights=self.lights,
-            materials=self.materials
+            materials=self.materials,
+            blend_params=blend_params
         )
 
     def forward(self, fragments, meshes, **kwargs):

video_render.py

@@ -26,57 +26,44 @@ def render_video_from_obj(input_obj_path, output_video_path, num_frames=60, imag
     if not os.path.exists(input_obj_path):
         raise FileNotFoundError(f"Input OBJ file not found: {input_obj_path}")
 
-    # 加载3D模型
     scene_data = trimesh.load(input_obj_path)
 
-    # 提取或合并网格
     if isinstance(scene_data, trimesh.Scene):
         mesh_data = trimesh.util.concatenate([geom for geom in scene_data.geometry.values()])
     else:
         mesh_data = scene_data
 
-    # 确保顶点法线存在
     if not hasattr(mesh_data, 'vertex_normals') or mesh_data.vertex_normals is None:
         mesh_data.compute_vertex_normals()
 
-    # 获取顶点坐标、法线和面
     vertices = torch.tensor(mesh_data.vertices, dtype=torch.float32, device=device)
     faces = torch.tensor(mesh_data.faces, dtype=torch.int64, device=device)
-    vertex_normals = torch.tensor(mesh_data.vertex_normals, dtype=torch.float32)
 
-    # 获取顶点颜色
     if mesh_data.visual.vertex_colors is None:
-        # 如果没有顶点颜色，可以给定一个默认值（例如，白色）
         vertex_colors = torch.ones_like(vertices)[None]
     else:
         vertex_colors = torch.tensor(mesh_data.visual.vertex_colors[:, :3], dtype=torch.float32)[None]
-    # 创建纹理并分配顶点颜色
     textures = TexturesVertex(verts_features=vertex_colors)
     textures.to(device)
-    # 创建Mesh对象
     mesh = pytorch3d.structures.Meshes(verts=[vertices], faces=[faces], textures=textures)
 
-    # 设置渲染器
     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,  # 渲染图像的尺寸
-        blur_radius=0.0,  # 默认无模糊
-        faces_per_pixel=1,  # 每像素渲染一个面
-        # background_color=(1.0, 1.0, 1.0)
+        image_size=image_size,
+        blur_radius=0.0,
+        faces_per_pixel=1,
     )
 
-    # 设置旋转和渲染参数
     frames = []
     camera_distance = 6.5
     elevs = 0.0
     center = (0.0, 0.0, 0.0)
-    # 渲染每一帧
     materials = Materials(
             device=device,
-            diffuse_color=((0.0, 0.0, 0.0),),
+            diffuse_color=((1.0, 1.0, 1.0),),
             ambient_color=((1.0, 1.0, 1.0),),
-            specular_color=((0.0, 0.0, 0.0),),
+            specular_color=((1.0, 1.0, 1.0),),
             shininess=0.0,
     )
         
@@ -91,7 +78,6 @@ def render_video_from_obj(input_obj_path, output_video_path, num_frames=60, imag
             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
@@ -105,32 +91,26 @@ def render_video_from_obj(input_obj_path, output_video_path, num_frames=60, imag
             )
 
         renderer = MeshRenderer(rasterizer=rasterizer, shader=shader)
-        # 渲染RGB图像和Normal图像
         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"]
 
-        # 提取RGB和Normal map
-        rgb = rgb_image[0, ..., :3].cpu().numpy()  # RGB图像
+        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)
-        # 将RGB和Normal map合并为一张图，左边RGB，右边Normal map
         combined_image = np.concatenate((rgb, normal), axis=1)
 
-        # 将合并后的图像加入到帧列表
         frames.append(combined_image)
 
-    # 使用imageio保存视频
     imageio.mimsave(output_video_path, frames, fps=fps)
 
     print(f"Video saved to {output_video_path}")
 
 if __name__ == '__main__':
-    # 示例调用
     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)