Add mask_filter and detection_threshold options to the GroundedSAMInvocation.

invokeai/backend/grounded_sam/grounding_dino_pipeline.py

@@ -1,6 +1,7 @@
 from typing import Optional
 
 import torch
+from PIL import Image
 from transformers.pipelines import ZeroShotObjectDetectionPipeline
 
 
@@ -12,8 +13,8 @@ class GroundingDinoPipeline:
     def __init__(self, pipeline: ZeroShotObjectDetectionPipeline):
         self._pipeline = pipeline
 
-    def __call__(self, *args, **kwargs):
-        return self._pipeline(*args, **kwargs)
+    def detect(self, image: Image.Image, candidate_labels: list[str], threshold: float = 0.1):
+        return self._pipeline(image=image, candidate_labels=candidate_labels, threshold=threshold)
 
     def to(self, device: Optional[torch.device] = None, dtype: Optional[torch.dtype] = None) -> "GroundingDinoPipeline":
         self._pipeline.model.to(device=device, dtype=dtype)

invokeai/backend/grounded_sam/segment_anything_model.py

@@ -30,6 +30,9 @@ class SegmentAnythingModel:
             masks=outputs.pred_masks,
             original_sizes=inputs.original_sizes,
             reshaped_input_sizes=inputs.reshaped_input_sizes,
-        )[0]
+        )
 
+        # There should be only one batch.
+        assert len(masks) == 1
+        masks = masks[0]
         return masks