From ce87dca1d7336a46747bf32645b93712c95d0606 Mon Sep 17 00:00:00 2001
From: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
Date: Mon, 13 May 2024 16:47:58 +0200
Subject: [PATCH] [Object detection pipeline] Lower threshold (#30710)

* Lower threshold

* Address comment
---
 src/transformers/pipelines/object_detection.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/src/transformers/pipelines/object_detection.py b/src/transformers/pipelines/object_detection.py
index d6ae63f4bd..36946cbf8a 100644
--- a/src/transformers/pipelines/object_detection.py
+++ b/src/transformers/pipelines/object_detection.py
@@ -83,7 +83,7 @@ class ObjectDetectionPipeline(Pipeline):
 
                 The pipeline accepts either a single image or a batch of images. Images in a batch must all be in the
                 same format: all as HTTP(S) links, all as local paths, or all as PIL images.
-            threshold (`float`, *optional*, defaults to 0.9):
+            threshold (`float`, *optional*, defaults to 0.5):
                 The probability necessary to make a prediction.
             timeout (`float`, *optional*, defaults to None):
                 The maximum time in seconds to wait for fetching images from the web. If None, no timeout is set and
@@ -120,7 +120,7 @@ class ObjectDetectionPipeline(Pipeline):
             model_outputs["bbox"] = model_inputs["bbox"]
         return model_outputs
 
-    def postprocess(self, model_outputs, threshold=0.9):
+    def postprocess(self, model_outputs, threshold=0.5):
         target_size = model_outputs["target_size"]
         if self.tokenizer is not None:
             # This is a LayoutLMForTokenClassification variant.