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Fix bug of multiple pre-processing when segmentation (PyTorch) #645

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Fix bug of multiple pre-processing when segmentation (PyTorch) #645

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222ffe9
Fix bug of multiple pre-processing when segmentation (PyTorch)
Lionelsy Mar 21, 2024
2ea4d03
Merge branch 'main' into main
Lionelsy Jul 24, 2024
16d3744
Merge branch 'main' into main
Lionelsy Nov 28, 2024
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7 changes: 3 additions & 4 deletions ml3d/torch/dataloaders/torch_dataloader.py
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Original file line number Diff line number Diff line change
Expand Up @@ -22,6 +22,7 @@ def __init__(self,
sampler=None,
use_cache=True,
steps_per_epoch=None,
cache_convert=None,
**kwargs):
"""Initialize.

Expand All @@ -38,6 +39,7 @@ def __init__(self,
self.dataset = dataset
self.preprocess = preprocess
self.steps_per_epoch = steps_per_epoch
self.cache_convert = cache_convert

if preprocess is not None and use_cache:
cache_dir = getattr(dataset.cfg, 'cache_dir')
Expand All @@ -59,10 +61,7 @@ def __init__(self,
continue
data = dataset.get_data(idx)
# cache the data
self.cache_convert(name, data, attr)

else:
self.cache_convert = None
self.cache_convert(name, data, attr)

self.transform = transform

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8 changes: 7 additions & 1 deletion ml3d/torch/pipelines/semantic_segmentation.py
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Original file line number Diff line number Diff line change
Expand Up @@ -136,6 +136,11 @@ def run_inference(self, data):
model.device = device
model.eval()

preprocess_func = model.preprocess
processed_data = preprocess_func(data, {'split': 'test'})
def get_cache(attr):
return processed_data

batcher = self.get_batcher(device)
infer_dataset = InferenceDummySplit(data)
self.dataset_split = infer_dataset
Expand All @@ -144,7 +149,8 @@ def run_inference(self, data):
preprocess=model.preprocess,
transform=model.transform,
sampler=infer_sampler,
use_cache=False)
use_cache=False,
cache_convert=get_cache)
infer_loader = DataLoader(infer_split,
batch_size=cfg.batch_size,
sampler=get_sampler(infer_sampler),
Expand Down