Prevent reference error on dc

gaussian_renderer/__init__.py

@@ -15,7 +15,7 @@
 from scene.gaussian_model import GaussianModel
 from utils.sh_utils import eval_sh
 
-def render(viewpoint_camera, pc : GaussianModel, pipe, bg_color : torch.Tensor, scaling_modifier = 1.0, separate_sh = False, override_color = None, use_trained_exp=False):
+def render(viewpoint_camera, pc : GaussianModel, pipe, bg_color : torch.Tensor, scaling_modifier = 1.0, separate_sh = False, override_color = None, use_trained_exp=False, orthographic=True):
     """
     Render the scene. 
 
@@ -33,21 +33,48 @@ def render(viewpoint_camera, pc : GaussianModel, pipe, bg_color : torch.Tensor,
     tanfovx = math.tan(viewpoint_camera.FoVx * 0.5)
     tanfovy = math.tan(viewpoint_camera.FoVy * 0.5)
 
+    # raster_settings = GaussianRasterizationSettings(
+    #     image_height=int(viewpoint_camera.image_height),
+    #     image_width=int(viewpoint_camera.image_width),
+    #     tanfovx=tanfovx,
+    #     tanfovy=tanfovy,
+    #     bg=bg_color,
+    #     scale_modifier=scaling_modifier,
+    #     viewmatrix=viewpoint_camera.world_view_transform,
+    #     projmatrix=viewpoint_camera.full_proj_transform,
+    #     sh_degree=pc.active_sh_degree,
+    #     campos=viewpoint_camera.camera_center,
+    #     prefiltered=False,
+    #     debug=pipe.debug,
+    #     antialiasing=pipe.antialiasing
+    # )
+
+      # Set up rasterization configuration
+    if not orthographic:
+        tanfovx = math.tan(viewpoint_camera.FoVx * 0.5)
+        tanfovy = math.tan(viewpoint_camera.FoVy * 0.5)
+        full_proj_transform = viewpoint_camera.get_full_proj_transform(orthographic)
+    else:
+        tanfovx, tanfovy, full_proj_transform = viewpoint_camera.get_full_proj_transform(orthographic)
+
+
     raster_settings = GaussianRasterizationSettings(
-        image_height=int(viewpoint_camera.image_height),
-        image_width=int(viewpoint_camera.image_width),
-        tanfovx=tanfovx,
-        tanfovy=tanfovy,
-        bg=bg_color,
-        scale_modifier=scaling_modifier,
-        viewmatrix=viewpoint_camera.world_view_transform,
-        projmatrix=viewpoint_camera.full_proj_transform,
-        sh_degree=pc.active_sh_degree,
-        campos=viewpoint_camera.camera_center,
-        prefiltered=False,
-        debug=pipe.debug,
-        antialiasing=pipe.antialiasing
-    )
+      image_height=int(viewpoint_camera.image_height),
+      image_width=int(viewpoint_camera.image_width),
+      tanfovx=tanfovx,
+      tanfovy=tanfovy,
+      bg=bg_color,
+      scale_modifier=scaling_modifier,
+      viewmatrix=viewpoint_camera.world_view_transform,
+      projmatrix=full_proj_transform,
+      sh_degree=pc.active_sh_degree,
+      campos=viewpoint_camera.camera_center,
+      prefiltered=False,
+      debug=pipe.debug,
+      antialiasing=pipe.antialiasing,
+      orthographic=orthographic
+  )
+
 
     rasterizer = GaussianRasterizer(raster_settings=raster_settings)
 
@@ -71,6 +98,7 @@ def render(viewpoint_camera, pc : GaussianModel, pipe, bg_color : torch.Tensor,
     # from SHs in Python, do it. If not, then SH -> RGB conversion will be done by rasterizer.
     shs = None
     colors_precomp = None
+    dc = None
     if override_color is None:
         if pipe.convert_SHs_python:
             shs_view = pc.get_features.transpose(1, 2).view(-1, 3, (pc.max_sh_degree+1)**2)

scene/cameras.py

@@ -87,6 +87,14 @@ def __init__(self, resolution, colmap_id, R, T, FoVx, FoVy, depth_params, image,
         self.projection_matrix = getProjectionMatrix(znear=self.znear, zfar=self.zfar, fovX=self.FoVx, fovY=self.FoVy).transpose(0,1).cuda()
         self.full_proj_transform = (self.world_view_transform.unsqueeze(0).bmm(self.projection_matrix.unsqueeze(0))).squeeze(0)
         self.camera_center = self.world_view_transform.inverse()[3, :3]
+
+    def get_full_proj_transform(self, orthographic=False):
+        if not orthographic:
+            return self.full_proj_transform
+        else:
+            tanfovx, tanfovy, projection_matrix = getProjectionMatrix(znear=self.znear, zfar=self.zfar, fovX=self.FoVx, fovY=self.FoVy, orthographic=True)
+            full_proj_transform = (self.world_view_transform.unsqueeze(0).bmm(projection_matrix.transpose(0,1).cuda().unsqueeze(0))).squeeze(0)
+            return tanfovx, tanfovy, full_proj_transform
 
 class MiniCam:
     def __init__(self, width, height, fovy, fovx, znear, zfar, world_view_transform, full_proj_transform):
@@ -101,3 +109,11 @@ def __init__(self, width, height, fovy, fovx, znear, zfar, world_view_transform,
         view_inv = torch.inverse(self.world_view_transform)
         self.camera_center = view_inv[3][:3]
 
+    def get_full_proj_transform(self, orthographic=False):
+        if not orthographic:
+            return self.full_proj_transform
+        else:
+            tanfovx, tanfovy, projection_matrix = getProjectionMatrix(znear=self.znear, zfar=self.zfar, fovX=self.FoVx, fovY=self.FoVy, orthographic=True)
+            full_proj_transform = (self.world_view_transform.unsqueeze(0).bmm(projection_matrix.transpose(0,1).cuda().unsqueeze(0))).squeeze(0)
+            return tanfovx, tanfovy, full_proj_transform
+

utils/graphics_utils.py

@@ -48,27 +48,47 @@ def getWorld2View2(R, t, translate=np.array([.0, .0, .0]), scale=1.0):
     Rt = np.linalg.inv(C2W)
     return np.float32(Rt)
 
-def getProjectionMatrix(znear, zfar, fovX, fovY):
-    tanHalfFovY = math.tan((fovY / 2))
-    tanHalfFovX = math.tan((fovX / 2))
-
-    top = tanHalfFovY * znear
-    bottom = -top
-    right = tanHalfFovX * znear
-    left = -right
-
-    P = torch.zeros(4, 4)
-
-    z_sign = 1.0
-
-    P[0, 0] = 2.0 * znear / (right - left)
-    P[1, 1] = 2.0 * znear / (top - bottom)
-    P[0, 2] = (right + left) / (right - left)
-    P[1, 2] = (top + bottom) / (top - bottom)
-    P[3, 2] = z_sign
-    P[2, 2] = z_sign * zfar / (zfar - znear)
-    P[2, 3] = -(zfar * znear) / (zfar - znear)
-    return P
+def getProjectionMatrix(znear, zfar, fovX, fovY, orthographic=False):
+  if not orthographic:
+      tanHalfFovY = math.tan((fovY / 2))
+      tanHalfFovX = math.tan((fovX / 2))
+
+      top = tanHalfFovY * znear
+      bottom = -top
+      right = tanHalfFovX * znear
+      left = -right
+
+      P = torch.zeros(4, 4)
+
+      z_sign = 1.0
+
+      P[0, 0] = 2.0 * znear / (right - left)
+      P[1, 1] = 2.0 * znear / (top - bottom)
+      P[0, 2] = (right + left) / (right - left)
+      P[1, 2] = (top + bottom) / (top - bottom)
+      P[3, 2] = z_sign
+      P[2, 2] = z_sign * zfar / (zfar - znear)
+      P[2, 3] = -(zfar * znear) / (zfar - znear)
+
+      return P
+
+  else:
+      left, right = -fovX, fovX
+      bottom, top = -fovY, fovY
+
+      P = torch.zeros(4, 4)
+
+      z_sign = 1.0
+      P[0, 0] = 2.0 / (right - left)
+      P[0, 3] = - (right + left) / (right - left)
+      P[1, 1] = 2.0 / (top - bottom)
+      P[1, 3] = - (top + bottom) / (top - bottom)
+      P[2, 2] = -2.0 / (zfar - znear)
+      P[2, 3] = - (zfar + znear) / (zfar - znear)
+      P[3, 3] = z_sign
+
+      # tanfovx, tanfovy, P
+      return (right - left) / 2, (top - bottom) / 2, P
 
 def fov2focal(fov, pixels):
     return pixels / (2 * math.tan(fov / 2))