🚨🚨🚨 changing default threshold and applying threshold before the rescale (#25608)

changing position of score threshold and its default value

src/transformers/models/owlvit/image_processing_owlvit.py

@@ -503,7 +503,7 @@ class OwlViTImageProcessor(BaseImageProcessor):
         return results
 
     # TODO: (Amy) Make compatible with other frameworks
-    def post_process_image_guided_detection(self, outputs, threshold=0.6, nms_threshold=0.3, target_sizes=None):
+    def post_process_image_guided_detection(self, outputs, threshold=0.0, nms_threshold=0.3, target_sizes=None):
         """
         Converts the output of [`OwlViTForObjectDetection.image_guided_detection`] into the format expected by the COCO
         api.
@@ -511,7 +511,7 @@ class OwlViTImageProcessor(BaseImageProcessor):
         Args:
             outputs ([`OwlViTImageGuidedObjectDetectionOutput`]):
                 Raw outputs of the model.
-            threshold (`float`, *optional*, defaults to 0.6):
+            threshold (`float`, *optional*, defaults to 0.0):
                 Minimum confidence threshold to use to filter out predicted boxes.
             nms_threshold (`float`, *optional*, defaults to 0.3):
                 IoU threshold for non-maximum suppression of overlapping boxes.
@@ -564,11 +564,13 @@ class OwlViTImageProcessor(BaseImageProcessor):
             if not query_scores.nonzero().numel():
                 continue
 
+            # Apply threshold on scores before scaling
+            query_scores[query_scores < threshold] = 0.0
+
             # Scale box alpha such that the best box for each query has alpha 1.0 and the worst box has alpha 0.1.
             # All other boxes will either belong to a different query, or will not be shown.
             max_score = torch.max(query_scores) + 1e-6
             query_alphas = (query_scores - (max_score * 0.1)) / (max_score * 0.9)
-            query_alphas[query_alphas < threshold] = 0.0
             query_alphas = torch.clip(query_alphas, 0.0, 1.0)
             alphas[idx] = query_alphas