UniqAI/gaussian-splatting
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Merge pull request #62 from HrsPythonix/improve-robustness-ply-loading

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Add sort to ensure right order of properties read from ply file
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Snosixtyboo 2023-07-27 11:04:35 +02:00 committed by GitHub
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scene/gaussian_model.py
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@ -226,6 +226,7 @@ class GaussianModel:
features_dc[:, 2, 0] = np.asarray(plydata.elements[0]["f_dc_2"]) features_dc[:, 2, 0] = np.asarray(plydata.elements[0]["f_dc_2"])
extra_f_names = [p.name for p in plydata.elements[0].properties if p.name.startswith("f_rest_")] extra_f_names = [p.name for p in plydata.elements[0].properties if p.name.startswith("f_rest_")]
extra_f_names = sorted(extra_f_names, key = lambda x: int(x.split('_')[-1]))
assert len(extra_f_names)==3*(self.max_sh_degree + 1) ** 2 - 3 assert len(extra_f_names)==3*(self.max_sh_degree + 1) ** 2 - 3
features_extra = np.zeros((xyz.shape[0], len(extra_f_names))) features_extra = np.zeros((xyz.shape[0], len(extra_f_names)))
for idx, attr_name in enumerate(extra_f_names): for idx, attr_name in enumerate(extra_f_names):
@ -234,11 +235,13 @@ class GaussianModel:
features_extra = features_extra.reshape((features_extra.shape[0], 3, (self.max_sh_degree + 1) ** 2 - 1)) features_extra = features_extra.reshape((features_extra.shape[0], 3, (self.max_sh_degree + 1) ** 2 - 1))
scale_names = [p.name for p in plydata.elements[0].properties if p.name.startswith("scale_")] scale_names = [p.name for p in plydata.elements[0].properties if p.name.startswith("scale_")]
scale_names = sorted(scale_names, key = lambda x: int(x.split('_')[-1]))
scales = np.zeros((xyz.shape[0], len(scale_names))) scales = np.zeros((xyz.shape[0], len(scale_names)))
for idx, attr_name in enumerate(scale_names): for idx, attr_name in enumerate(scale_names):
scales[:, idx] = np.asarray(plydata.elements[0][attr_name]) scales[:, idx] = np.asarray(plydata.elements[0][attr_name])
rot_names = [p.name for p in plydata.elements[0].properties if p.name.startswith("rot")] rot_names = [p.name for p in plydata.elements[0].properties if p.name.startswith("rot")]
rot_names = sorted(rot_names, key = lambda x: int(x.split('_')[-1]))
rots = np.zeros((xyz.shape[0], len(rot_names))) rots = np.zeros((xyz.shape[0], len(rot_names)))
for idx, attr_name in enumerate(rot_names): for idx, attr_name in enumerate(rot_names):
rots[:, idx] = np.asarray(plydata.elements[0][attr_name]) rots[:, idx] = np.asarray(plydata.elements[0][attr_name])