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Fix readme training example (issue: 639) #641

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Fix readme training example (issue: 639) #641

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20 changes: 20 additions & 0 deletions README.md
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Original file line number Diff line number Diff line change
Expand Up @@ -186,6 +186,26 @@ Similar as for inference, pipelines provide an interface for training a model on
a dataset.

```python
import ml3d
from open3d import _ml3d
from ml3d.torch import RandLANet, SemanticSegmentation

dataset_path = "/media/nikste/SSD_030_06/semantic_kitti/"
cfg_path = "ml3d/configs/randlanet_semantickitti.yml"
# '/path/to/SemanticKITTI/'
cfg = _ml3d.utils.Config.load_from_file(cfg_path)
dataset = ml3d.datasets.SemanticKITTI(dataset_path=dataset_path, use_cache=True)

# create the model with random initialization.
model = RandLANet(**cfg.model)

pipeline = SemanticSegmentation(model=model, dataset=dataset, **cfg.pipeline)

# prints training progress in the console.
pipeline.run_train()



# use a cache for storing the results of the preprocessing (default path is './logs/cache')
dataset = ml3d.datasets.SemanticKITTI(dataset_path='/path/to/SemanticKITTI/', use_cache=True)

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