add params to florence2sam2 model

vision_agent/tools/tools.py

@@ -473,7 +473,11 @@ def florence2_sam2_image(
 
 
 def florence2_sam2_video_tracking(
- prompt: str, frames: List[np.ndarray], chunk_length: Optional[int] = None
+ prompt: str,
+ frames: List[np.ndarray],
+ chunk_length: Optional[int] = None,
+ iou_threshold: Optional[float] = None,
+ nms_threshold: Optional[float] = None,
 ) -> List[List[Dict[str, Any]]]:
  """'florence2_sam2_video_tracking' is a tool that can segment and track multiple
  entities in a video given a text prompt such as category names or referring
@@ -486,6 +490,10 @@ def florence2_sam2_video_tracking(
  frames (List[np.ndarray]): The list of frames to ground the prompt to.
  chunk_length (Optional[int]): The number of frames to re-run florence2 to find
  new objects.
+ iou_threshold (Optional[float]): Value between 0.1 and 1.0.
+ The IoU threshold value used to compare last_predictions and new_predictions objects.
+ nms_threshold (Optional[float]): Value between 0.1 and 1.0.
+ The non-maximum suppression threshold value used to filter the Florencev2 predictions.
 
  Returns:
  List[List[Dict[str, Any]]]: A list of list of dictionaries containing the label
@@ -520,6 +528,10 @@ def florence2_sam2_video_tracking(
  }
  if chunk_length is not None:
  payload["chunk_length"] = chunk_length # type: ignore
+ if iou_threshold is not None:
+ payload["iou_threshold"] = iou_threshold # type: ignore
+ if nms_threshold is not None:
+ payload["nms_threshold"] = nms_threshold # type: ignore
  data: Dict[str, Any] = send_inference_request(
  payload, "florence2-sam2", files=files, v2=True
  )