How to train blender dataset with nerfstudio? about zipnerf-pytorch HOT 3 OPEN

I also have a dataset exported from Meshroom: photos and tranforms.json with all the camera alignment. I think that is the same as Blender format, right? I would like to be able to run it as well. Does it need a dedicated importer? I assumed any method inside of nerfstudio would be able to access some internal dataset representation of nerfstudio, so this should not be an issue. But maybe I am wrong.

zipnerf_datamanager.py 45 __init__
super().__init__(

base_datamanager.py 404 __init__
self.train_dataparser_outputs: DataparserOutputs = self.dataparser.get_dataparser_outputs(split="train")

base_dataparser.py 165 get_dataparser_outputs
dataparser_outputs = self._generate_dataparser_outputs(split, **kwargs)

colmap_dataparser.py 254 _generate_dataparser_outputs
assert colmap_path.exists(), f"Colmap path {colmap_path} does not exist."

AssertionError:
Colmap path sparse/0 does not exist.

from zipnerf-pytorch.

I also have a dataset exported from Meshroom: photos and tranforms.json with all the camera alignment. I think that is the same as Blender format, right? I would like to be able to run it as well. Does it need a dedicated importer? I assumed any method inside of nerfstudio would be able to access some internal dataset representation of nerfstudio, so this should not be an issue. But maybe I am wrong.

zipnerf_datamanager.py 45 __init__
super().__init__(

base_datamanager.py 404 __init__
self.train_dataparser_outputs: DataparserOutputs = self.dataparser.get_dataparser_outputs(split="train")

base_dataparser.py 165 get_dataparser_outputs
dataparser_outputs = self._generate_dataparser_outputs(split, **kwargs)

colmap_dataparser.py 254 _generate_dataparser_outputs
assert colmap_path.exists(), f"Colmap path {colmap_path} does not exist."

AssertionError:
Colmap path sparse/0 does not exist.

For the Blender dataset, I changed the "Dataparser" to the dataparser named "Blender". It seems that this error log is because "ColmapDataParser" is used.

In my scenario, I can make it run, but the model would converge in the wrong direction. After training, the model cannot render correct images.

from zipnerf-pytorch.

Previously, the gradients during training are always zero. I've changed the floating precision from float16 to float32 and float64, the gradients become non-zero but are extremely small, and the model is still unable to converge rightly.

from zipnerf-pytorch.