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

Co-authored-by: fatih c. akyon <[email protected]>

sahi/models/mmdet.py

@@ -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):