diff --git a/poetry.lock b/poetry.lock
index 1ee8c59cd6..810c406c29 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -2436,14 +2436,14 @@ numpy = {version = ">=2,<2.3.0", markers = "python_version >= \"3.9\""}
 
 [[package]]
 name = "openfoodfacts"
-version = "3.3.0"
+version = "3.4.0"
 description = "Official Python SDK of Open Food Facts"
 optional = false
 python-versions = ">=3.10"
 groups = ["main"]
 files = [
-    {file = "openfoodfacts-3.3.0-py3-none-any.whl", hash = "sha256:cdca761569a17266a80d2e93bdc863090bfa51c1c5548c6c8582c3351abc24a3"},
-    {file = "openfoodfacts-3.3.0.tar.gz", hash = "sha256:656dd98a4e620dc70899528359e75b7a773773cf8e420edcc352c31f5fa2aec1"},
+    {file = "openfoodfacts-3.4.0-py3-none-any.whl", hash = "sha256:a50093e4285ab6e5e46bdc4e6702b68ee3961eff220485eb095108cc4d190db2"},
+    {file = "openfoodfacts-3.4.0.tar.gz", hash = "sha256:532594916ea7dea5fc3328a31c4050cb866b66fa25893e5cc49444433fc0b6ff"},
 ]
 
 [package.dependencies]
@@ -5118,4 +5118,4 @@ watchdog = ["watchdog (>=2.3)"]
 [metadata]
 lock-version = "2.1"
 python-versions = "^3.11"
-content-hash = "f07ca17ff16d89ee725fdbeae82be8f81b4acfffb5f0b78e0323069009a76e81"
+content-hash = "4cb9c081b0a634586a0ec87aaf828b539ef74d1b98c778dbd653fb694c3cc420"
diff --git a/pyproject.toml b/pyproject.toml
index 789ff0eb1a..c0b7839b6f 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -74,7 +74,7 @@ lark = "~1.1.4"
 h5py = "~3.13.0"
 opencv-python-headless = "~4.12.0.88"
 toml = "~0.10.2"
-openfoodfacts = "3.3.0"
+openfoodfacts = "3.4.0"
 imagehash = "~4.3.1"
 peewee-migrate = "~1.12.2"
 diskcache = "~5.6.3"
diff --git a/robotoff/app/api.py b/robotoff/app/api.py
index 97a3146459..793b6c2bd1 100644
--- a/robotoff/app/api.py
+++ b/robotoff/app/api.py
@@ -809,7 +809,7 @@ def on_get(self, req: falcon.Request, resp: falcon.Response):
             "nms_threshold", default=None
         )
         nms_eta: float | None = req.get_param_as_float("nms_eta", default=None)
-
+        nms: bool = req.get_param_as_bool("nms", default=True)
         available_object_detection_models = list(
             ObjectDetectionModel.__members__.keys()
         )
@@ -868,6 +868,7 @@ def on_get(self, req: falcon.Request, resp: falcon.Response):
                     threshold=threshold,
                     nms_threshold=nms_threshold,
                     nms_eta=nms_eta,
+                    nms=nms,
                 )
 
                 if output_image:
diff --git a/robotoff/prediction/object_detection/core.py b/robotoff/prediction/object_detection/core.py
index 5772b2d0c2..c5b2dd7534 100644
--- a/robotoff/prediction/object_detection/core.py
+++ b/robotoff/prediction/object_detection/core.py
@@ -92,6 +92,7 @@ class ModelConfig(BaseModel):
         triton_model_name="price_tag_detection",
         image_size=960,
         label_names=["price-tag"],
+        default_threshold=0.25,
     ),
 }
 
@@ -110,6 +111,8 @@ def add_boxes_and_labels(image_array: np.ndarray, result: ObjectDetectionResult)
         instance_masks=None,
         use_normalized_coordinates=True,
         line_thickness=5,
+        max_boxes_to_draw=len(result.detection_boxes),
+        min_score_thresh=0.0,
     )
     image_with_boxes = Image.fromarray(image_array)
     result.boxed_image = image_with_boxes
@@ -127,6 +130,7 @@ def detect_from_image(
         threshold: float | None = None,
         nms_threshold: float | None = None,
         nms_eta: float | None = None,
+        nms: bool = True,
     ) -> ObjectDetectionResult:
         """Run an object detection model on an image.
 
@@ -144,6 +148,7 @@ def detect_from_image(
             defaults to None (0.7 will be used).
         :param nms_eta: the NMS eta parameter to use, defaults to None (1.0 will be
             used).
+        :param nms: whether to use NMS, defaults to True.
         :return: the detection result
         """
         threshold = threshold or self.config.default_threshold
@@ -158,6 +163,7 @@ def detect_from_image(
             threshold=threshold,
             nms_threshold=nms_threshold,
             nms_eta=nms_eta,
+            nms=nms,
         )
         for metric_name, duration in result.metrics.items():
             ml_metrics_logger.info(
diff --git a/tests/integration/insights/test_extraction.py b/tests/integration/insights/test_extraction.py
index 26171acfa8..85da30a7ee 100644
--- a/tests/integration/insights/test_extraction.py
+++ b/tests/integration/insights/test_extraction.py
@@ -30,6 +30,7 @@ def detect_from_image(
         threshold: float | None = 0.5,
         nms_threshold: float | None = None,
         nms_eta: float | None = None,
+        nms: bool = True,
     ) -> ObjectDetectionResult:
         return self.raw_result