fix docs example, add object_detection to DETR docs (#19377)

docs/source/en/model_doc/detr.mdx

@@ -171,6 +171,7 @@ mean Average Precision (mAP) and Panoptic Quality (PQ). The latter objects are i
 [[autodoc]] DetrFeatureExtractor
     - __call__
     - pad_and_create_pixel_mask
+    - post_process_object_detection
     - post_process_semantic_segmentation
     - post_process_instance_segmentation
     - post_process_panoptic_segmentation

src/transformers/models/detr/modeling_detr.py

@@ -1605,11 +1605,11 @@ class DetrForSegmentation(DetrPreTrainedModel):
 
         >>> # Use the `post_process_panoptic_segmentation` method of `DetrFeatureExtractor` to retrieve post-processed panoptic segmentation maps
         >>> # Segmentation results are returned as a list of dictionaries
-        >>> result = feature_extractor.post_process_panoptic_segmentation(outputs, target_size=[(300, 500)])
+        >>> result = feature_extractor.post_process_panoptic_segmentation(outputs, target_sizes=[(300, 500)])
 
-        >>> # A tensor of shape (height, width) where each value denotes a segment id
+        >>> # A tensor of shape (height, width) where each value denotes a segment id, filled with -1 if no segment is found
         >>> panoptic_seg = result[0]["segmentation"]
-        >>> # Get mapping of segment ids to semantic class ids
+        >>> # Get prediction score and segment_id to class_id mapping of each segment
         >>> panoptic_segments_info = result[0]["segments_info"]
         ```"""