draft(not working) for mlp color per pixel #123
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yanzhoupan
approved these changes
Sep 9, 2023
| point_id_list: ti.types.ndarray(ti.i32, ndim=1), | ||
| camera_intrinsics: ti.types.ndarray(ti.f32, ndim=2), # (3, 3) | ||
| pointcloud: ti.types.ndarray(ti.f32, ndim=2), # (N, 3) | ||
| # (N, 56) 56 features (cov_rotation, xxx, r, g, b) |
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Not 56 features after using the MLP. Maybe change to:
#(N, feature_num), feature_num features (cov_rotation, ..., mlp weights and bias)
| @@ -534,6 +577,13 @@ def gaussian_point_rasterisation_backward( | |||
| ): | |||
| camera_intrinsics_mat = ti.Matrix( | |||
| [[camera_intrinsics[row, col] for col in ti.static(range(3))] for row in ti.static(range(3))]) | |||
| # K: [fx, 0, cx; 0, fy, cy; 0, 0, 1] | |||
| # inv_K: [1/fx, 0, -cx/fx; 0, 1/fy, -cy/fy; 0, 0, 1] | |||
| inv_camera_intrinsics_mat = ti.math.mat3([ | |||
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camera_intrinsics_mat and inv_camera_intrinsics_mat seems to be constent vectors. Maybe wrap them in somewhere like CameraInfo to avoid the repeated code and repeated calculation?
| [[camera_intrinsics[row, col] for col in ti.static(range(3))] for row in ti.static(range(3))]) | ||
| # K: [fx, 0, cx; 0, fy, cy; 0, 0, 1] | ||
| # inv_K: [1/fx, 0, -cx/fx; 0, 1/fy, -cy/fy; 0, 0, 1] | ||
| inv_camera_intrinsics_mat = ti.math.mat3([ |
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See comment in the backward func.
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Overall lgtm. Some small comments are left.
Looking forward to see the results after updating the place where gaussian_point_rasterisation and gaussian_point_rasterisation_backward are called.
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