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Update has_mask method for mmdet models (handle ConcatDataset) #1092

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Nov 22, 2024
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32 changes: 24 additions & 8 deletions sahi/models/mmdet.py
Original file line number Diff line number Diff line change
Expand Up @@ -188,15 +188,31 @@ def num_categories(self):
@property
def has_mask(self):
"""
Returns if model output contains segmentation mask
Returns if model output contains segmentation mask.
Considers both single dataset and ConcatDataset scenarios.
"""
# has_mask = self.model.model.with_mask
train_pipeline = self.model.cfg["train_dataloader"]["dataset"]["pipeline"]
has_mask = any(
isinstance(item, dict) and any("mask" in key and value is True for key, value in item.items())
for item in train_pipeline
)
return has_mask

def check_pipeline_for_mask(pipeline):
return any(
isinstance(item, dict) and any("mask" in key and value is True for key, value in item.items())
for item in pipeline
)

# Access the dataset from the configuration
dataset_config = self.model.cfg["train_dataloader"]["dataset"]

if dataset_config["type"] == "ConcatDataset":
# If using ConcatDataset, check each dataset individually
datasets = dataset_config["datasets"]
for dataset in datasets:
if check_pipeline_for_mask(dataset["pipeline"]):
return True
else:
# Otherwise, assume a single dataset with its own pipeline
if check_pipeline_for_mask(dataset_config["pipeline"]):
return True

return False

@property
def category_names(self):
Expand Down